METHOD FOR DIRECTIONAL TRANSMISSION OF ENERGY IN THE FORM OF AT LEAST ONE ENERGY PACKET

Abstract

The present invention relates to a method for directional transmission of power in the form of energy packets via a transmission network. The power to be transmitted is adjustable at at least one location x of each edge by a data and computer network. A data packet is biuniquely assigned to each energy packet, which data packet is formed in a control instance of the data and computer network by means of predictions. This data packet describes an optimized transport path via which optimized transport path a source transmits the physical power in a fixed transmission period T to a load for partial demand coverage. Furthermore, the data packet describes the power class of the energy packet, wherein this power class is defined by the temporal course of a nominal power P.sub.nom(t) determined by predictions and by a remainder R(t) in the transmission period determined by a function of an uncertainty of the predictions. For the transmission of the energy packet, the transmitted power equal to P.sub.nom(t) plus a fraction of R(t) is set for each point in time t within T at at least one location x of each edge of the transport path.

Claims

1. A method for directional transmission of energy in the form of at least one energy packet from a plurality of sources Q via at least two nodes, one of which is a supply node K.sub.Q connected via a supply edge to one of the plurality of sources Q and one of which is a demand node K.sub.S connected via a demand edge to a load S, and via a plurality of edges to a plurality of loads S in a transmission network, the transmission network being controllable by means of a data and computer network in such a way that for at least one location x on each of the plurality of edges an actually flowing physical power p.sub.φ(x,t) is controllable by a control instance of the data and computer network, which method comprises the steps of: A) forming a data packet for each energy packet, wherein the data packet is biuniquely assigned to exactly one energy packet, wherein the data packet defines the respective energy packet, and wherein the data packet describes i. a transmission period T of the energy packet with a duration DT and an execution time t.sub.0, which execution time t.sub.0 identifies the start of the transmission period T, ii. a predetermined transport path of a transport graph of the transmission network for the directed transmission of the energy packet, which transport path connects at least one of the plurality of sources Q with exactly one of the plurality of loads, wherein the exactly one of the plurality of sources Q is connected to a supply node K.sub.Q of the predetermined transport path via exactly one supply edge and the exactly one load S is connected to the demand node K.sub.S via a demand edge of the predetermined transport path, and iii. an equivalence class {p.sub.nom(t), R(t),T} of the energy packet, wherein the equivalence class is given by a nominal power p.sub.nom(t) of the energy packet as a function of time, wherein the nominal power p.sub.nom(t) is determined beforehand by at least one prediction, and a remainder R(t) as a function of time and as a function of a prediction uncertainty of the at least one prediction, wherein for each point in time t within the transmission period T of the energy packet there is a μ(t), with −1≤μ(t)<1 or with −1<μ(t)≤1 for with −1≤μ(t)≤1, such that the physical power p.sub.φ(x,t) during the transmission of the energy packet at each point in time t and at at least one location x on each edge of the transport path is fixed as the sum of the nominal power p.sub.nom(t) and the product of μ(t) and the remainder R(t), wherein the equivalence class is defined by an equivalence relation, according to which equivalence relation, for any point in time t of the transmission period T, a first physical power t) at any location {circumflex over (x)} of an edge of the transport path and a second physical power p.sub.φ(x,t) at any location x of an edge of the transport path are equivalent only if there is a predetermined remainder R(t) greater than or equal to zero and less than or equal to a limit value R.sub.max and a μ(t), with −1≤μ(t)<1 or with −1<μ(t)≤1 or with −1≤μ(t)≤1, such that the first physical power t) is equal to the sum of the second physical power p.sub.φ(x,t) and the product of and the remainder R(t), B) prior to the execution time t, transmitting the data packet to all control instances of at least all nodes or all edges on the transport path, C) beginning with the execution time t.sub.0 transmitting the energy packet biuniquely assigned to the data packet, wherein for all points in time t within the transmission period T of the energy packet, the physical power p.sub.φ(x,t) flowing on the transport path between the supply node K.sub.Q and the demand node K.sub.S set at at least one location x of each edge of the transport path in such a way that the physical power fed into the demand nodes K.sub.S is an element of the equivalence class {p.sub.nom(t),R(t),T} described by the data packet.

2. The method according to claim 1, wherein the data packet furthermore describes iv) a predetermined compensation path of the transport graph of the electrical transmission network connecting a predetermined compensation node K.sub.SAS node to the demand node via a plurality of edges, wherein the compensation node K.sub.SAS at any point in time t of the transmission period T of the energy packet either can receive a physical power up to a predetermined maximum compensation power C(t), wherein the predetermined maximum compensation power C(t) as a function of the remainder R(t), or can deliver a physical power up to the maximum compensation power C(t), optionally increased by a loss drop determined by a prediction, via the compensation path, and wherein, in step C), the physical power flowing between the compensation node K.sub.SAS and at least the demand node K, and is controlled for at least one location x on the plurality of edges of the compensation path such that the physical power at the at least one location is at any point in time t within the transmission period T an element of an equivalence class {p.sub.nom(t)=0,R(t)=C(t),T} with a nominal power p.sub.nom(t) of zero and a remainder having the value of the previously determined maximum compensation power C(t) and such that at at least one location x of the demand edge the physical power p.sub.φ(x,t) flowing through the demand edge between the demand node K.sub.S and the load S connected to this demand node is equal to the nominal power p.sub.nom(t) of the energy packet plus a compensation power δ′(t) as a function of the prediction, and/or the data packet describes v) a previously determined balancing path of the transport graph of the transmission network, which via a plurality of edges connects a previously determined balancing node K.sub.Aus and the supply node K.sub.Q, wherein the balancing node K.sub.Aus at any point in time t of the transmission period T of the energy packet can receive a physical power up to a predetermined maximum balancing power, wherein the predetermined maximum balancing power D(t) is determined as a function of the remainder R(t), or provide a physical power up to the maximum balancing power D(t), optionally increased by the loss drop determined by a prediction, via the balancing path, and wherein, in step C), the physical power flowing between the balancing node K.sub.Aus and the supply node K.sub.Q for at least one location x on the plurality of edges of the balancing path is controlled such that at this at least one location x the physical power at any point in time t within the transmission period T is an element of an equivalence class {p.sub.nom(t)=0, R(t)=D(t),T} with a nominal power p.sub.nom(t) of zero and a remainder with the value of the predetermined maximum balancing power D(t) and such that the physical power p.sub.φ(x,t) flowing between the supply node K.sub.Q and the demand node K.sub.S for at least one location x on the plurality of edges of the transport path is an element of the equivalence class {p.sub.nom(t),R(t),T} of the energy packet.

3. The method according to claim 1, wherein the method for an arbitrary prediction period T.sub.prog with a prediction start t.sub.0prog and a prediction duration DT.sub.prog further comprising the steps of, at a prediction point in time t.sup.0, which is prior to the prediction start t.sub.0prog, D) generating of a supply prediction for a supply power p.sub.progEin(t) to be supplied at any point in time t in the prediction period T.sub.prog from the respective source, wherein the supply prediction has a supply prediction uncertainty, and E) generating a demand prediction for a power demand (t) predicted to be required by the respective load at any point in time t in the prediction period T.sub.prog, wherein the demand prediction has a demand prediction uncertainty, wherein the temporal course of the nominal power p.sub.nom(t) of the energy packet is determined at least from the supply prediction and the demand prediction, and wherein the temporal course of the remainder R(t) is a function of at least the supply prediction uncertainty and the demand prediction uncertainty.

4. The method according to claim 3, the method comprising the steps of F) forming a demand data packet {p.sub.progBed(t),R(t),T.sub.prog} of the load, the demand data packet describing the predicted temporal course of the nominal power required by the load p.sub.nomBed(t) at any point in time t within the prediction period T.sub.prog and the temporal course of a remainder R(t) as a function of the demand prediction uncertainty of the demand prediction at any point in time t within the prediction period T.sub.prog, G) forming a supply data packet of the source, the supply data packet describing the predicted temporal course of the nominal power p.sub.nomEin(t) to be supplied by the source at any point in time t within the prediction period T.sub.prog and the temporal course of a remainder R(t) as a function of the supply prediction uncertainty of the supply prediction at any point in time t within the prediction period T.sub.prog and wherein forming of the equivalence class of an energy packet for transmission from a source to a load comprises at least one allocation of a sub-packet of the supply data packet to a sub-packet of the demand data packet at least to meet the demand of the load.

5. The method according to claim 1, wherein, when a plurality of energy packets is transmitted simultaneously via exactly one edge of the transmission network, the following steps are carried out H) superpositioning the simultaneously transmitted energy packets to exactly one simultaneous energy packet with a superpositioned simultaneous data packet, I) adjusting the physical power flowing via the exactly one edge, so that the physical power at at least one location of the exactly one edge is an element of the equivalence class {p.sub.nom(t),R(t),T} of the superpositioned simultaneous data packet of the exactly one simultaneous power packet formed by the superpositioning in step H), wherein the nominal power p.sub.nom(t) of this equivalence class {p.sub.nom(t),R(t),T} is the sum of the nominal powers of the simultaneously transmitted energy packets, wherein in the summation for the nominal power p.sub.nom(t) the flow directions of the power is taken into account, and wherein the remainder R of the equivalence class {p.sub.nom(t),R(t),T} is the sum of the remainders of the simultaneously transmitted energy packets and wherein for the summation of the remainder the flow direction is disregarded.

6. The method according to claim 5, the method further comprising the steps of J) at each node on the transmission network determining the fractions of energy packets pending at each edge of the respective node in an arbitrary test period for simultaneous transmission to the next node based on the data packets, K) for the duration of the test period, adjusting the power supply to each edge of the respective node so that the physical power t at at least one location x of the respective edge is an element of an equivalence class {p.sub.nom(t),R (t),T} whose nominal power p.sub.nom(t) is the sum of the nominal powers of the simultaneously transmitted energy packets, the flow directions of the electrical power being taken into account in the summation for the nominal power, and the remainder of which is the sum of the remainders of the simultaneously transmitted energy packets, the flow direction being disregarded for the summation of the remainder, wherein the flow direction for an electrical power fed out via an edge of the node being counted with the opposite sign compared to the flow direction of an electrical power supplied via an edge.

7. The method according to claim 3, wherein the method at a reservation point in time t.sup.00 and for a reservation period T.sub.res, wherein the time t.sup.00 is prior to the start of the reservation period T.sub.res, which reservation period has a start time t.sub.0res and a reservation duration DT.sub.res, and wherein the reservation period T.sub.res is within the prediction period T.sub.prog, further comprises the steps of, L) for each load, determining the amount of all transport graphs, each of which transport graphs is connected to the load, such that for each of these transport graphs, each source connected to the transport graph is connected to the load via a transport path of the transport graph and, for the reservation period T.sub.res via a sub-packet E′.sub.Ein of a supply packet defined by the supply data packet for the reservation period, wherein this available sub-packet E′.sub.Ein is formed by a coverage packet defined by a coverage data packet E.sub.D and a loss packet E.sub.ν, the coverage packets of the sources Q of the transport graph together cover a maximized portion of a demand packet of the load S defined by the demand data packet and wherein the respective loss data packet describes the loss determined by a prediction during the transmission of the respective coverage packet defined by the coverage data packet via the corresponding transport path, M) associating a loss data packet E.sub.ν to each of the coverage data packets, wherein each of the coverage packets defined by the coverage data packets is transmitted via a transport path assigned thereto as a subgraph of a transport graph out of the amount of transport graphs formed according to the preceding step L), wherein a nominal power of the equivalence class of a loss packet defined by the loss data packet is determined by a prediction of the loss and the remainder of the equivalence class of the loss packet defined by the loss data packet is determined as a function of a prediction uncertainty of a loss prediction, wherein the nominal power of the loss is the power predicted to be lost in the transmission of the cover packet via the transport path from the source Q to the load S by the loss prediction, and wherein for the loss prediction all energy packets to be transmitted via the considered transport path during the reservation period are taken into account, and the transport path has an available transmission capacity to transmit the sub-packet E′.sub.Ein which is composed of the coverage packet defined by the coverage data packet E.sub.D and the loss packet defined by the loss data packet E.sub.ν, wherein the coverage packet E.sub.D defined by the coverage data packet and the loss packet E.sub.ν defined by the loss data packet have the same transmission direction, N) wherein the equivalence class of the sub-packet E′.sub.Ein is formed by adding the nominal powers of the coverage packet and the loss packet and the remainders, and wherein the loss packet has the same flow direction as the coverage packet and the transmission period T is set equal to the reservation period T.sub.res, O) for each load, determining the optimized transport paths as subgraphs of the transport graph optimizedly determined with respect to a selected metric, wherein each source of each transport path so optimizedly determined, connecting that source Q with the load S of the transport graph for the transmission of a sub-packet of the supply packet, at any point in time t within the reservation period T.sub.res provides an available power which is an element of the equivalence class of the sub-packet determined in accordance with step N) above, P) forming in each case a reservation data packet for defining a reservation packet of the transport path from step O), wherein the reservation data packet of the reservation packet describes the equivalence class of the respective sub-packet of the supply packet as an equivalence class of the reservation packet, the supply edge of the respective sub-packet of the supply packet as the supply edge of the reservation packet, the transport path and the reservation period T.sub.res, Q) for each source of the transport graph determining a sub-packet of the supply packet of each source that is still available, so that the supply packet is formed by superposition of all reservation packets and this available sub-packet for the reservation period, R) for each load for the reservation period T.sub.res determining the not yet covered sub-packet of the demand packet, so that the demand packet is formed from the coverage packets according to step N), the reservation packets being assigned to the load and the not covered sub-packet, S) for each time t in the reservation period T.sub.res determining the remaining available transmission capacity of the transmission network, such that the given transmission capacity of the transmission network is the sum of the remaining available transmission capacity and the sum of the nominal powers plus the remainders of the reservation packets, T) for each supply prediction, demand prediction and loss prediction by which at least one of the values determined by them is changed, repeating the preceding steps, U) for each reservation packet formed in steps L) to O) at an arbitrary booking time t.sub.Buch, which is prior to the start time t.sub.0res of the reservation packet, bindingly booking the reservation data packet of the reservation packet as the data packet of the energy packet, wherein the transmission period of the energy packet is the reservation period, wherein the equivalence class {p.sub.nom(t),R(t),T=T.sub.res} is the equivalence class of the reservation packet, wherein the supply edge of the reservation packet is the supply edge of the energy packet, and wherein the transport path of the reservation packet is the transport path of the energy packet, and V) at the execution time t.sub.0 transmitting of the respective energy packet according to the data packet of the energy packet.

8. The method according to claim 2, the method, for a reservation period T.sub.res, further comprising the steps of, at the reservation point in time t.sup.00, W) for each load, determining the set of transport graphs each connected to the load such that, for each one of this set of transport graphs, each source connected to the transport graph is connected to the load via a transport path of the transport graph and has an available sub-packet of the remaining available supply packet of the source, the available sub-packet being formed from a coverage packet defined by a coverage data packet and a loss packet defined by a loss data packet, wherein the coverage packets of the sources Q.sub.i of the transport graph together cover a maximized portion of the demand data packet of the load S and wherein the loss packet describes the loss in the transmission of the respective coverage packet over the corresponding path, which loss is determined by a prediction, X) for each load and each transport graph determined according to step W), extending the respective transport graph to an extended transport graph by determining the compensation nodes of the respective extended transport graph such that for each source of the extended transport graph the compensation nodes are determined, wherein each of these compensation nodes is connected via at least one compensation path, as a subgraph of the extended transport graph, to the load S and the compensation nodes together provide a maximum total compensation power C(t) determined beforehand in order to receive a physical power up to the maximum total compensation power C(t) at each point in time t within the reservation period T.sub.res, wherein the maximum total compensation power C(t) is a function of the remainders of the coverage packets of the respective source Q and in order to supply via the compensation paths in sum a physical power up to this maximum total compensation power C(t), which is increased by the power losses determined by prediction, which power losses drop during the transmission of the sub-packets from the compensation nodes via the compensation paths into the demand node K.sub.S, Y) for each load determining exactly one extended transport graph optimized according to a given metric from the set of all extended transport graphs determined according to steps W) and X), each of the extended transport graphs being connected to the load via a demand edge, Z) for the optimized extended transport graph of step Y) forming the reservation data packets for defining the reservation packets of the energy packets to be transmitted over the optimized extended transport graph, wherein the reservation data packet of each reservation packet includes the equivalence class of the respective available supply packet as the equivalence class of the reservation packet, the supply edge of the respective supply packet as the supply edge of the corresponding source node K.sub.Q of the reservation packet, the corresponding transport path connecting the source to the load, the reservation period T.sub.res, as well as the compensation nodes with the corresponding compensation potentials and the compensation paths connecting the compensation nodes with the load node K.sub.S to which the load is connected via the demand edge, AA) determining the still available sub-packets of the supply packets and the not yet covered portions of the demand packet of the still available transmission capacities according to step O), reducing the still available capacity of the reserved compensation nodes by the reserved maximum powers for receiving and for delivering the corresponding powers, reducing the still available transmission capacities of the compensation paths by the reserved potentials for delivering power of the reserved compensation nodes increased by the power loss, BB) for each supply prediction, demand prediction and loss prediction by which at least one of the values determined by the respective prediction is changed, repeat the previous steps, CC) for each reservation packet of an optimized extended transport graph formed in the preceding steps, at an arbitrary booking point in time t.sub.Buch, which booking point in time t.sub.Buch is prior to the start time t.sub.0res of the reservation packet, bindingly booking the reservation data packets of the reservation packets as the data packets of the energy packets, wherein for each of these data packets the transmission period of the energy packet is the reservation period, wherein the equivalence class is {p.sub.nom(t),R(t),T} is the equivalence class of the reservation packet and the supply edge of the reservation packet is the supply edge of the energy packet, and bindingly booking the reserved transmission capacities on the optimal extended transport graph, and at the execution time t.sub.0 transmission of the respective energy packet according to the data packet of the energy packet via the booked capacities of the booked extended transport graph, and/or DD) for each load, extending the possible transport graphs and/or possible extended transport graphs previously determined in steps W) and X) by the possible balancing nodes and the possible balancing paths, such that each of these balancing nodes is connected via a balancing path to one of the sources of the transport graph and/or extended transport graph, for which the associated supply data packet requires a balancing, and these balancing nodes can individually or collectively provide a balancing for the corresponding sources and can balance the losses determined by at least one loss prediction occurring during the transmission of the balancing packet from the balancing node to the source, EE) according to a predetermined metric, determining an optimized transport graph with balancing or an extended transport graph with compensation with a balancing out of the set of possible transport graphs with a balancing determined according to step DD) or a transport graph with compensation extended by the compensation, and FF) for the optimized transport graph with balancing determined in this way or a transport graph with balancing extended by the compensation carrying out steps Z) to CC).

9. The method according to claim 3, wherein the method for a real-time prediction period T.sub.RT with a real-time prediction start t.sub.0RT and a real-time prediction duration DT.sub.RT, wherein the realtime prediction period T.sub.RT is a sub-period of the reservation period T.sub.res of the reservation packet, further comprises the steps of, at a real-time prediction point in time in time t.sup.000 after the reservation point in time in time t.sup.00 of the reservation period T.sub.res and prior to the real-time prediction start t.sub.0RT, GG) measuring at least one parameter, HH) creating a real-time prediction p.sub.RT(x,t) of the physical power p.sub.φ(x,t) at any point in time t within the real-time prediction period T.sub.RT at a location x of the transmission network, the real-time prediction p.sub.RT(x,t) having negligible real-time prediction uncertainty and being created with consideration of the at least one parameter, wherein the physical power p.sub.φ(x,t) is a function of the at least one parameter, and II) forming a real time energy packet for transmission over a subgraph of the transmission network by using the real time data packet associated with the real time energy packet, which real time data packet defines the real time energy packet, which real time data packet describes the time history of the nominal power p.sub.nomRT(x,t)=p.sub.RT(x,t) at at least one location x of each edge of the subgraph as a function of the predicted time history of the physical power supplied into that subgraphs p.sub.φ(x,t) at the location x, wherein the remainder R(t) is set equal to constant zero and the transmission period T is set equal to the real-time prediction period T.

10. The method according to claim 5, wherein transmitting the energy packet associated with the data packet over a directed transport path of the booked transport graph connecting the source for the energy packet to the load, for each real-time prediction time period T.sub.RT, which is a part of an overlap of the transmission period by real-time prediction periods and for each point in time t within the respective real-time prediction period T.sub.RT comprises the following steps JJ) creating a real-time prediction for the temporal course of the physical power p.sub.φ(x,t) for at least one location x on at least each edge of the transport path according to step ii. of claim 9, including at least one measurement of the physical power fed into the respective transport graph at the real-time prediction point in time t.sup.000, supplied into the transport graph, KK) forming a real-time energy packet for the supply via the supply edge into this transport path according to step II), in that in the associated real-time data packet the temporal course of the nominal power over the real-time prediction period T.sub.RT at at least one location x on each edge of the transport paths, over which transport paths the transfer of the power packet from the source supply edge to the corresponding load demand edge occurs is set equal to the corresponding predictions from steps HH) and II), and the remainder for all points in time t within the real-time prediction period T.sub.res and all subgraphs is constantly set equal to zero, LL) transmitting the real-time data packet to the control instances of the transport graph; and MM) setting the physical power p.sub.φ(x,t) for at least one location x on each edge of the transport path, such that the physical power p.sub.φ(x,t) is a function of the nominal power p.sub.normRT(x,t) described in the real-time data packet for that location x, and the physical power p.sub.φ(x,t) at any point in time t within the transmission period T satisfies the equivalence relation described in the data packet of the energy packet, and NN) for simultaneous transmission of energy packets via a single edge of a node for each transmission period T setting the physical power p.sub.φ(x,t) for at least one location A on this edge, so that the physical power p.sub.φ(x,t) is a function of the sum of the nominal powers of the real-time packets associated with the simultaneously transmitted energy packets at that location x taking into account the direction of flow, so that the physical power p.sub.φ(x,t) at any point in time t within the transmission period T is an element of the equivalence class formed for the simultaneous energy packet according to claim 5.

11. The method according to claim 8, wherein the method for the real-time prediction period T.sub.RT further comprising the steps of, for each real-time prediction period T.sub.RT, which is a part of an overlap of the transmission period by real-time prediction periods, and for each point in time t within the respective real-time prediction period T.sub.RT OO) for each supply node K.sub.Q.sub.i to which a source is connected via a booked transport path of the booked transport graph extended by compensation, whereby the source Q.sub.i is booked to cover the demand of the load S, determining a power supplied by the source via the edge of the transport path, via which edged the load node K.sub.S of the load S is connected, at at least one location on x of that edge by a real-time supply prediction, PP) determining the difference δ(t) between the sum of the physical power supplied into all booked transport paths which connect all sources Q with the load S from the real-time supply predictions, and the physical power taken by the load S, which load S is connected to the demand node K, via the demand edge, at a location x of the demand edge from the real-time prediction, QQ) for each point in time t within the real-time prediction period T.sub.RT forming a maximum total compensation power C(t) as the sum of all maximum compensation powers C.sub.i(t) of all booked sources Q.sub.i and the load S and for each booked compensation node K.sub.SAS.sub.i determining of a quotient γ.sub.i(t) of the maximum compensation power C.sub.i(t) of the respective compensation node K.sub.SAS.sub.i and the maximum total compensation power C(t), RR) determining real-time compensation packets for transmission on the compensation graph as a subgraph of the booked extended transport graph, which includes the compensation nodes K.sub.SAS.sub.i and the load S, by adding, for each compensation path of the booked compensation graph connecting a compensation node K.sub.SAS.sub.i with the load, in the associated real-time compensation data packets, the nominal power p.sub.nomKomRT(x,t) for at least one location x of each edge of the respective compensation path a function of the product of the difference δ(t) determined in step PP) with the quotient γ.sub.i(t) but only up to a maximum of the value of the maximum compensation power C.sub.i(t) and the remainder R(t) is constantly set equal to zero, wherein if the product γ.sub.i(t).Math.δ(t) is negative, the product γ.sub.i(t).Math.δ(t) is increased by an amount determined by a real-time prediction for a location x of the edge of the compensation path via which edge the demand node K.sub.S is connected to the compensation node to compensate for the losses incurred in the transmission from the compensation node to the corresponding load 5, SS) transmitting the real-time compensation data packets to the control instances, and TT) transmitting the real-time compensation packets by, at any point in time t within the transmission period, at at least one location x on the edges of the compensation paths, setting the physical power p.sub.φ(x,t) such that the physical power p.sub.φ(x,t) is equal to the nominal power p.sub.nomKomRT(x,t) of the real-time compensation packets for this location x, and by simultaneously at any point in time within the transmission period T setting the physical powers p.sub.φ(x,t) to be equal to the nominal powers of the real-time energy packets p.sub.nomRT(x,t) at the locations x on the transport graph previously selected by the real-time predictions, so that the physical power p.sub.φ(x,t) at a location x selected by the real-time prediction for the demand on the demand edge is equal to the sum of the nominal powers of the energy packets sent from the supply nodes K.sub.Q.sub.i to the demand node K.sub.S plus the compensation power δ′(t), wherein the compensation power δ′(t) is equal to the difference between the physical power p.sub.φ(x,t) of the power taken by the load according to the real-time demand prediction and the sum of the nominal powers of the energy packets transmitted to the load S.

12. The method according to claim 8, the method comprising, for each real-time prediction period T.sub.RT, which is part of the overlap of the transmission period by real-time prediction periods with the real-time prediction point in time t.sup.000 further comprising the steps of, for each point in time t within the respective real-time prediction period T.sub.RT UU) for each supply node K.sub.Q.sub.i to which a source Q.sub.i is connected via a supply edge wherein the source Q.sub.i is to cover the demand of the load S for each point in time t within the real-time prediction period, determining a fraction ρ(t) of the supplied physical power p.sub.φ(x,t) from the real-time supply predictions at at least one location x of the respective supply edges, which fraction ρ(t) exceeds or falls below the limits defined by the equivalence relation of the power to be transmitted from the source node K.sub.Q.sub.i to the load S, VV) for each point in time r within the real-time prediction period T.sub.RT forming a maximum total balancing power D(t) as the sum of all maximum balancing powers D.sub.i(t) of the balancing nodes booked for the sources Q.sub.i and for each balancing node K.sub.Aus.sub.i determining a quotient g.sub.i(t) from the maximum balancing power D.sub.i(t) of the respective balancing node K.sub.Aus.sub.i and the maximum total balancing power D(t), WW) determining real-time balancing packets for transmission on all booked balancing paths that include the balancing nodes K.sub.Aus.sub.i and the source Q.sub.1, wherein in the associated real-time balancing data packets the nominal power p.sub.nomAusRT(x,t) for at least one location x of each edge of the respective balancing path is a function of the product of the deviation μ(t) determined in step UU) with the quotient g.sub.i(t) but only up to a maximum of the value of the maximum compensation power D.sub.i(t), and the remainder R.sub.i(t) is constantly set equal to zero, wherein if the product g.sub.i(t).Math.ρ(t) is negative, this product g.sub.i(t).Math.ρ(t) is increased by the amount determined by a real time prediction for a location x of the edge of the balancing path via which edge the supply node K.sub.Q.sub.i is connected to the balancing node K.sub.Aus.sub.i to compensate for losses incurred during transmission from the balancing node to the corresponding source, XX) transmitting the real-time balancing data packets to the control instances associated with the nodes on the balancing graphs, YY) transmitting the real-time balancing packets by at any point time t within the transmission period T for at least one location x on each edge of the balancing graph setting the physical power p.sub.φ(x,t) to be equal to the nominal power p.sub.nomAusRT(x,t) of the real-time compensation packets for the location x, and ZZ) at any point in time t within the transmission period T setting the physical power p.sub.φ(x,t) for at least one location x of each edge of the transport path, so that the physical power p.sub.φ(x,t) is equal to the nominal power p.sub.nomRT(x,t) of the real-time energy data packets for the location x and the physical power p.sub.φ(x,t) is an element of the power class of the energy packet to be transmitted.

13. A system for directional transmission of energy in the form of at least one energy packet with a transmission network and a data and computer network, wherein the transmission network comprises at least two nodes, one of which is a supply node K.sub.Q and one of which is a demand node K.sub.S, at least one edge, wherein each edge connects exactly two nodes, at least one power controller, wherein the at least one power controller is arranged and located such that, by means of the at least one power controller for at least one location x on each edge, a physical power p.sub.φ(x,t) actually flowing via the respective edge is settable, a plurality of sources Q, wherein each of the sources Q is connected to a supply node via a supply edge K.sub.Q, and a plurality of loads S, wherein each of the loads S is connected to a demand node K.sub.S via a demand edge, wherein the data and computer network comprises at least one computer node and at least one control instance executed on the at least one computer node, wherein the data and computer network is configured and operatively connected to the at least one power controller such that, during operation of the system, the physical power p.sub.φ(x,t) is controllable by the at least one power controller for at least one location on each edge by the control instance, wherein the at least one control instance of the at least one computer node is configured such that, during operation of the system, the control instance executes a method comprising the steps of: A) forming a data packet, wherein the data packet is biuniquely assigned to exactly one energy packet, wherein the data packet defines the respective energy packet and wherein the data packet describes i) a transmission period T of the energy packet with a duration DT and an execution time t.sub.0, which marks the beginning of the transmission period T, ii) a predetermined transport path of a transport graph of the transmission network for the directed transmission of the energy packet, which transport path connects at least one of the plurality of sources Q with exactly one of the plurality of loads S, wherein the exactly one of the plurality of sources Q is connected via exactly one supply edge to a supply node K.sub.Q of the previously determined transport path and the exactly one load S is connected via a demand edge of the predetermined transport path to the demand node K.sub.S, and iii) an equivalence class {p.sub.nom(t),R(t),T} of the energy packet, wherein the equivalence class {p.sub.nom(t),R,T} is given by a nominal power p.sub.nom(t) of the energy packet as a function of time, wherein the nominal power p.sub.nom(t) is determined beforehand by at least one prediction, and a remainder R(t) as a function of time and as a function of a prediction uncertainty of the at least one prediction, wherein for each point in time t within the transmission period T of the energy packet there is a μ(t), with −1≤μ(t)<1 or with −1<μ(t)≤1 or with −1≤μ(t)≤1 so that the physical power p.sub.φ(x,t) during the transmission of the energy packet at any point in time t and at at least one location on each edge of the transport path is fixed as the sum of the nominal power p.sub.nom(t) and the product of μ(t) and the remainder R(t), wherein the equivalence class is defined by an equivalence relation, according to which equivalence relation, for each point in time t of the transmission period T, a first physical power p′.sub.φ({circumflex over (x)},t) at any location {circumflex over (x)} of an edge of the transport path and a second physical power p.sub.φ(x,t) at any location x of an edge of the transport path are equivalent only if there is a predetermined remainder R(t) greater than or equal to zero and less than or equal to a limit value R.sub.max and a μ(t), with −1≤μ(t)<1 or with −1<μ(t)≤1 or with −1≤μ(t)≤1 so that the first physical power p′.sub.φ(x,t) is equal to the sum of the second physical power p.sub.φ(x,t) and the product of μ(t) and the remainder R(t), B) prior to the execution time t.sub.0 transmitting the data packet to all control instances of the data and computer network to which the power controllers are connected for controlling the physical power, so that all data necessary for transmitting an energy packet are coherent on the control instances, and C) beginning with the execution time t.sub.0 transmitting the energy packet biuniquely assigned to the data packet, wherein for all points in time t within the transmission period T of the energy packet, the physical power p.sub.φ(x,t) flowing on the transport path between the supply node K.sub.Q and the demand node K.sub.S is set at at least one location x of each edge of the transport path in such a way that the physical power fed into the demand nodes K.sub.S is an element of the equivalence class {p.sub.nom(t),R(t),T} described by the data packet.

14. A method for directional transmission of energy in the form of at least one energy packet from a plurality of sources Q via at least two nodes, one of which is a supply node K.sub.Q connected via a supply edge to one of the plurality of sources Q and one of which is a demand node K.sub.S connected via a demand edge to a load S, and via a plurality of edges to a plurality of loads S in a transmission network, the transmission network being controllable by means of a data and computer network in such a way that for at least one location x on each of the plurality of edges an actually flowing physical power p.sub.φ(x,t) is controllable by a control instance of the data and computer network, which method comprises the steps of: A) forming a data packet for each energy packet, wherein the data packet is biuniquely assigned to exactly one energy packet, wherein the data packet defines the respective energy packet, and wherein the data packet describes i. a transmission period T of the energy packet with a duration DT and an execution time t.sub.0, which execution time t.sub.0 identifies the start of the transmission period T, ii. a predetermined transport path of a transport graph of the transmission network for the directed transmission of the energy packet, which transport path connects at least one of the plurality of sources Q with exactly one of the plurality of loads, wherein the exactly one of the plurality of sources Q is connected to a supply node K.sub.Q of the predetermined transport path via exactly one supply edge and the exactly one load S is connected to the demand node K.sub.S via a demand edge of the predetermined transport path, iii. an equivalence class {p.sub.nom(t),R(t),T} of the energy packet, wherein the equivalence class is given by a nominal power p.sub.nom(t) of the energy packet as a function of time, wherein the nominal power p.sub.nom(t) is determined beforehand by at least one prediction, and a remainder R(t) as a function of time and as a function of a prediction uncertainty of the at least one prediction, and iv. a predetermined compensation path of the transport graph of the electrical transmission network connecting a predetermined compensation node K.sub.SAS node to the demand node via a plurality of edges, wherein the compensation node K.sub.SAS at any point in time t of the transmission period T of the energy packet either can receive a physical power up to a predetermined maximum compensation power C(t), wherein the predetermined maximum compensation power C(t) as a function of the remainder R(t), or can deliver a physical power up to the maximum compensation power C(t), optionally increased by a loss drop determined by a prediction, via the compensation path, wherein for each point in time t within the transmission period T of the energy packet there is a μ(t), with −1≤μ(t)<1 or with −1<μ(t)≤1 or with −1≤μ(t)≤1, such that the physical power p t) during the transmission of the energy packet at each point in time t and at at least one location x on each edge of the transport path is fixed as the sum of the nominal power p.sub.nom(t) and the product of μ(t) and the remainder R(t), wherein the equivalence class is defined by an equivalence relation, according to which equivalence relation, for any point in time t of the transmission period T, a first physical power p′.sub.φ({circumflex over (x)},t) at any location of an edge of the transport path and a second physical power p.sub.φ(x,t) at any location x of an edge of the transport path are equivalent only if there is a predetermined remainder R(t) greater than or equal to zero and less than or equal to a limit value R.sub.max and a μ(t), with −1≤μ(t)<1 or with −1<μ(t)≤1 or with −1≤μ(t)≤1, such that the first physical power p′.sub.φ({circumflex over (x)},t) is equal to the sum of the second physical power p.sub.φ(x,t) and the product of μ(t) and the remainder R(t), B) prior to the execution time t.sub.0 transmitting the data packet to all control instances of at least all nodes or all edges on the transport path, C) beginning with the execution time t.sub.0 transmitting the energy packet biuniquely assigned to the data packet, wherein for all points in time t within the transmission period T of the energy packet, the physical power p.sub.φ(x,t) flowing on the transport path between the supply node K.sub.Q and the demand node K.sub.S is set at at least one location x of each edge of the transport path in such a way that the physical power fed into the demand nodes K, is an element of the equivalence class {p.sub.nom(t),R(t),T} described by the data packet, wherein, in step C), the physical power flowing between the compensation node K.sub.SAS and at least the demand node K.sub.S and is controlled for at least one location on the plurality of edges of the compensation path such that the physical power at the at least one location x is at any point in time t within the transmission period T an element of an equivalence class {p.sub.nom(t)=0,R(t)=C(t),T} with a nominal power p.sub.nom(t) of zero and a remainder having the value of the previously determined maximum compensation power C(t) and such that at at least one location x of the demand edge the physical power p.sub.nom(x,t) flowing through the demand edge between the demand node K.sub.S and the load S connected to this demand node is equal to the nominal power p.sub.nom(t) of the energy packet plus a compensation power δ′(t) as a function of the prediction, the method for directional transmission of energy for an arbitrary prediction period T.sub.prog with a prediction start t.sub.0prog and a prediction duration DT.sub.prog further comprising the steps of, at a prediction point in time which is prior to the prediction start t.sub.0prog, D) generating of a supply prediction for a supply power p.sub.progEin(t) to be supplied at any point in time t in the prediction period T.sub.prog from the respective source, wherein the supply prediction has a supply prediction uncertainty, and E) generating a demand prediction for a power demand p.sub.progBed(t) predicted to be required by the respective load at any point in time t in the prediction period T.sub.prog, wherein the demand prediction has a demand prediction uncertainty, wherein the temporal course of the nominal power p.sub.nom(t) of the energy packet is determined at least from the supply prediction and the demand prediction, and wherein the temporal course of the remainder R(t) is a function of at least the supply prediction uncertainty and the demand prediction uncertainty.

Description

BRIEF DESCRIPTION OF THE DRAWING

[0370] Further advantages, features and possible applications of the present invention will become apparent from the following description of an embodiment and the accompanying figures. In the figures, identical elements are denoted by identical reference signs.

[0371] FIG. 1 is a schematic representation of the energy transmission system according to the invention with an exemplary transport graph.

[0372] FIG. 2 is a schematic representation of a transmission network extended by compensation and balancing.

[0373] FIG. 3 is a schematic representation of the data and computer network comprising a control instance.

[0374] FIG. 4 is a schematic representation of an ohm node.

[0375] FIG. 5 is a schematic representation of a QFC node.

[0376] FIG. 1 shows a schematic representation of a possible embodiment of the system according to the invention for the directed transmission of energy using the example of an electrical supply network consisting of a transmission network 100.000 and a data and computer network 200.000. The data connections between the supply nodes 1.800, demand nodes 1.900, supply QFCs, demand QFCs, QFC nodes 2.000, ohm nodes 1.000 and edges 5.000 of the transmission network as well as the data connection of the data and computer network to other data networks such as the Internet are not shown. Furthermore, FIG. 1 schematically shows the control instances executed on the computer nodes of the data and computer network for setting the physical powers at locations of the edges of the transmission network. The representation of the transmission network schematically comprises the representation of two transport graphs consisting of edges and ohm and QFC nodes, such that sources are connected to a load for the transmission of energy packets. A node of 100.000 to whose edge 5.000 of 100.000 a source 6.000 is connected is referred to as a supply node 1.800 for the purposes of this application. A QFC 2001, see FIG. 4, of an active supply edge 2.800, which is both permanently connected to the source 6.000 and permanently connected to the supply node 1.800, is referred to as supply QFC 2.800. A node of 100.000 to whose edge 5.000 a load 7.000 is connected is referred to as a demand node 1.900 for the purposes of this application. This edge in this embodiment is an active edge and is referred to as a supply edge. The QFC 2.001 of this supply edge connected to this demand node 1.900 and to the load 7.000 is referred to as the demand QFC 2.900. In FIG. 1 the supply edge is shown in the embodiment of an active edge consisting of the supply edge 5810 connecting the source to the supply QFC 2.800 and the supply edge 5.820 connecting this QFC to the supply node. Here, an active edge has two connecting points at each of its end points for flexible connection. Accordingly, the demand edge 5.900 in the embodiment is shown as an active edge consisting of the demand edge 5.910 connecting the load to the demand QFC 2.900 and the demand edge 5.920 connecting this QFC to the demand node. Furthermore, FIG. 1 shows a schematic representation of a transmission network according to a first embodiment and the representation of two transport paths of the present invention. The transmission network can be formed from several autonomous transmission networks that are interconnected. Similarly, the data and computer network can be formed from autonomous, interconnected data and computer networks. FIG. 1 shows the possible transmission of a first energy packet E.sub.1 from a wind generator 6.100 to a private household 7.100 as a load via a transport path 101.000 and the transmission of a second energy packet E.sub.2 from a solar generator 6.200 via a second transport graph 102.000, also to the private household 7.100, Here, the private household is a prosumer that can also form a source in other operating states of the transmission network. The transport path 101.000 consists of the supply edge 5.810 which connects the wind generator 6.100 with the supply QFC 2.800. The latter is connected to the supply node 1.800 via the supply edge 5.820. This supply node 1.800 in turn is connected to a QFC 2.000 via an edge 5.000, which in turn is connected to the demand node 1.900 via a sequence of edges 5.000, which are connected to QFCs 2.000 and ohm nodes 1.000. This demand node is then connected to demand QFC 2.900 via demand edge 5.910. The transport path 101.000 then terminates with the connection of 2.900 via 5.920 at the private household in the role of a load 7.100 in this transmission. The structure of one embodiment of an ohm node 1.000 and a QFC node 2.000 is shown in FIGS. 4 and 5. The edges are active supply and demand edges and edges that are the lines for transmitting the corresponding physical power. In the case of an electrical transmission network, these are electrical lines. In the case of a gas network, they are corresponding pipelines.

[0377] To cover the demand of 7.100, a second energy packet E.sub.2 must be transmitted simultaneously in this example. The routing procedure has booked the solar generator 6.200 and the transport path 102.000 for this purpose; the transport graph 110.000 is formed from the union of the two transport paths 101.000 and 102.000. FIG. 1 shows that the two transport paths only have the demand node 1.900 and the demand partial edges 5.910 and 5.920 as well as the demand QFC 2.900 in common, thus the transport graph 110.000 as part of the transmission network 100.000 consists of these and of all other nodes and edges of the two transport paths. Furthermore, FIG. 1 shows that a third energy packet being transferred from SynBio source 6.300 to load 7.001 via a further transport path TP3. This transport path is connected to the supply node 1.800 of the transport path 102.000, designated TP2. This means that node 1.800 is also the supply node for transport path TP3. The transport path TP3 thus has the route in TP2 from 1.800 to the ohm node 1.000 in common with TP2. The ohm node 1.000 of TP2 is also the load node of TP3.

[0378] FIG. 2 shows the transmission of a packet from a source 6.100 via a transport graph 101.000 to a load 7.000, wherein the booking requires both compensation and balancing. In addition to the transport path, which in this case is identically equal to the transport graph, the booking procedure has booked both the compensation node 4.401, with the capacities given by the energy packet, and the compensation path 106.000 which connects 4.401 to the demand node 2.900. Since balancing is also required, the routing procedure booked the balancing node 4.401 and the balancing path 108.000, wherein 108.000 connects the balancing node 4.401 with the demand node 2.800, with the corresponding capacities accordingly. The compensation path has in common with the transport path, the demand node and the connection to the load; and the balancing path has in common the supply node and its connection to the load. FIG. 2 thus shows the extended transport graph 120.000 with compensation and balancing.

[0379] FIG. 3 shows the schematic design of the data and computer network 200.000 as well as the logical functions that are executed on this data and computer network. FIG. 3 is used to explain the structure and the logical functions. The data and computer network 200.000 consists of computer nodes networked with each other via a data network as at least a logical sub-network of 200.000. This data networking can be implemented via a dedicated line-based and/or radio-based data network or as a virtual private network via a third-party data infrastructure. On each of these computers, the correspondingly required data networking functions can be provided via a virtual router and/or virtual switches. Furthermore, the computers of 200.000 can have virtual computers for the execution of a control instance 220.000. At least one of these nodes is a so-called CPS node 205.000, on which the corresponding Cyber Physical System (CPS) operates for controlling and regulating the power controllers of the QFC nodes, the acquisition of measured values and the data communication with 200.000 are executed. These CPS 205.000 together form the so-called CPS network as a sub-network of 200.000. In one embodiment, at least one CPS node is assigned to each node of the transmission network 100.000. These CPS nodes have a corresponding data connection to the sensors 1.300 of the ohm nodes and sensors 2.300 of the QFCs as well as to the actuator 2400 of the QFC nodes for controlling the setting of the physical power by the respective QFC node or QFCs. Furthermore, in one embodiment, each sensor of the perimeter network, i.e. sensors at locations outside the transmission network, is assigned to at least one CPS node and connected to 200.000 via a data link. These sensors of the perimeter network, together with the CPS nodes assigned to them, form the perimeter network 210.000 and serve to record additional measured values as input variables for the various predictions, in particular for the real-time predictions of the power generation of the sources and the power demand. In one embodiment, a CPS node may be a particularly designed computing node with its own design, size and power consumption, and with connections for analogue and digital data communications. The coherently coupled control instances 220.000 together form a virtual control instance network by executing the corresponding task-specific control instances 220.000 on the corresponding virtual computers of the data and computer network. The data and computer network also has at least one wired and/or radio-based data connection to third-party data networks, such as the Internet. In one embodiment, the various tasks of the method according to the invention, such as performing the supply, demand and realtime predictions, the routing procedure comprising the reservation and booking procedure and the optimised determination of the transport and extended transport graphs, as well as the control of the QFCs for setting the physical power for the transmission of the packets, can be performed as a distributed application on different coherently coupled control instances. The control instances are executed on the computing nodes of 200.000. In one embodiment, for example, at least one control instance can be responsible for assigning the execution of the corresponding process steps to one or more control instances in dependence on subnetworks or also on specific nodes, or for initialising the corresponding control instances for execution on the virtual computers of the computer nodes. This can be, for example, the localisation, i.e. derivation of a weather prediction modified for the location of the source, from a general weather prediction obtained from third parties via the external data connection. The execution of demand predictions, real-time predictions and the routing procedure can also be divided accordingly for sub-networks or for subsets of 100.000 and assigned to corresponding control instances. These assignments can be made dynamically depending on the load situation. Thus, each element of 100.000 comprising a data connection to 200.000 has a control instance responsible for it.

[0380] FIG. 4 schematically shows the internal structure of an ohm node 1.000. This ohm node consists of the bus, the inner edges which are connected to the bus on one side and to the ports on the other side, i.e. the connection points for connecting outer edges, and the sensors 1.300 for measuring the physical power at the various points in the ohm node. These are divided into the sensors for measuring the power at the measuring points of the inner edges and for measuring the power at the measuring point of the bus. The sensors 1.300 are connected to the CPS 205.000 via data links. The CPS 205.000 is in turn connected to the data connection 1.200 to 200.000 for data exchange with the responsible control instance 220.000.

[0381] FIG. 5 schematically shows the internal structure of a QFC node. The QFC node consists of the two ports a and b which are each connected to the QFC via inner edges. The QFC is structured as follows. The inner edge 2.310 of 2.000 is connected on one side to the bidirectional power controller 2.300 and a sensor 2.310 for power measurement and on the other side to port a) for connecting an outer edge. On the other connection side of 2.300, the inner edge 2.320 with the sensor 2.320 and the port b) is connected.

[0382] The bidirectional power controller 2.300 is connected to an actuator 2.400. The sensors 2.310 and 2.320 as well as the actuator 2.400 are equipped with a connection for transmitting data to the corresponding CPS 205.000. The CPS in turn is equipped with a connection to 200.000 for data exchange. Furthermore, the QFC has a buffer on each of its edges 2.110 and 2.120 to compensate for small deviations or to implement quantisation. In one embodiment, in order to transmit an energy packet either via an edge connected to port a) or to port b), the physical power is set by the power controller 2.300 at the corresponding location of the edges, i.e. the connection point to the corresponding port. This is done by the corresponding control instance carrying out the corresponding setting by means of the actuator. In one embodiment, this is done by transmitting the real-time data packets assigned to the energy packet to be transmitted from the corresponding control instance 220.000 to 205.000 via the data connection from 205.000 to 200.000 for setting. There, the corresponding setting data for the setting device is then calculated and entered into a queue system. For the corresponding time cycles, the setting device 2.400 then takes these values from the queue and sets the power at the power controller 2.300 depending on the flow direction. The data determined by the sensors is transferred to 205.000 and, if necessary, already subjected to processing there, for example by forming moving average values in one embodiment. These values are then transmitted to 220.000 for further processing, e.g. for real-time predictions, but also for early fault detection. In another embodiment, the setting parameters for setting the physical power are already calculated by the corresponding control instance and transferred to 205.000 for setting.

[0383] In the following, we will explain the method according to the invention with the help of FIGS. 1 to 5 using a very simplified example. We assume that the sources 6.100 and 6.200 described in FIG. 1 and the load 7.100 are located in an area where, due to the seasonal period, an essentially constant production and consumption can be assumed for the transmission period T under consideration. The time series of the measured values acquired by the sensors of the perimeter network 210.000, which are assigned to the sources 6.100 and 6.200, are transmitted to the perimeter network 210.000, which, as FIG. 3 shows, is a part of the data and computer network 200.000. By means of Sensors in the analogue electrical part of the sources 6.100 and 6.1000 and the sensors of the supply QFC 2.800, as shown in FIG. 5, further measured values are transmitted to the data and computer network. Using the results of a general weather prediction and the various time series of the measured values, the supply predictions are produced for T by one or more prediction systems as part of one or more control instances 220.000, which are executed on 200.000. Similarly, by the prediction system responsible for the load, as part of the control instance time series responsible for the load, the power absorbed by the load 7.100 via the demand edge 5.920 is measured by the sensor of the demand QFC. Furthermore, time series on the power curves in the analogue electrical part assigned to the load are measured by sensors of the perimeter network 210.000 assigned to the load. Based on these time series and additional information influencing the future consumption, the prediction system assigned to the load as part of the corresponding control instance then creates the demand prediction for the load 7.100. In addition, time series on the time courses of the power from the relevant sensors in the ohm nodes, as shown in FIG. 5, and the QFCs are recorded and processed by the relevant control instances. In this example, we will describe an embodiment of the reservation and booking determination method described in claims 7 and 8, which we will refer to as the routing method. For a time period T lying in the future, the routing procedure determines the corresponding demand and supply data packets on the basis of the demand prediction for the load 7.100 and the supply predictions for the wind generator 6.100 and the solar generator 6.200. We assume that the supply data packets E.sub.Ein.sub.W for 6.100 and E.sub.Ein.sub.S for 6.200 determined by the routing procedure on the basis of the demand prediction for 7.100 and the supply predictions for 6.100 and 6.200 are composed as follows. There is a sub-packet E′B.sub.Ein.sub.W of the supply data packet E.sub.Ein.sub.W of the wind generator 6.100, so that E′B.sub.Ein.sub.W=E.sub.D⊕E.sub.V.sub.TP1. Wherein for the cover packet E.sub.D=E.sub.Bed, wherein E.sub.Bed is the demand data packet of load 7.100, and E.sub.V.sub.TP1 is the loss packet to compensate for the loss incurred when transmitting E.sub.D=E.sub.Bed via transport path TP1. For the supply packet E.sub.Ein.sub.S, there is a sub-packet E′.sub.Ein.sub.S, such that E′.sub.Ein.sub.S=E.sub.D⊕E.sub.V.sub.TP2. Here, E.sub.V.sub.TP2 is the loss packet that compensates for the loss in the transmission of E.sub.D=E.sub.Bed via TP2. As a metric for determining which of the two paths 101.000 and 102.000 is the optimal one, the incurred cost is taken. We assume that the price for power is the same for both sources and that the transmission costs only depend on the length of the transport paths and the power transmitted at the same time. Equally, however, the transport paths in question must have the corresponding transmission capacities. We assume that both 101.000 and the transport path 1002.000 have the corresponding capacities to transmit the corresponding energy packets. In the routing procedure, the possible transport paths connecting 6.100 with 7.100 and 6.200 with 7. 100 and comprising the transmission capacity to transmit the respective energy packets E.sub.1=E′.sub.Ein.sub.W=E.sub.D⊕E.sub.V.sub.TP1 and E.sub.2=E′.sub.Ein.sub.S=E.sub.D⊕E.sub.V.sub.TP2 are considered. These are the transport paths 101.000 and 102.000 of FIG. 1. For booking, the routing procedure determines which one of the two is the more optimal transport path. Since the prices for power for both sources are the same, the transport path with the smallest transmission costs, which are mainly determined by the transfer costs, is the optimal one. We assume that the two transport paths do not differ in terms of length and specific line resistance. Thus, the transmission loss depends on whether additional packets are transmitted simultaneously over one edge. Since both the wind generator 6.100 via transport path 101.000 and the solar generator 6.200 via transport path can transmit the energy packet E.sub.2 to cover the demand of load 7.100, the routing procedure for booking, we skip the reservation here, must select the most optimal of the two paths.

[0384] According to FIG. 1, the transmission of another energy packet from the SynBio generator 6.300 to a load 7.200 via a subgraph 102.000 is also booked for the period 7′. Thus, the loss packet E.sub.V.sub.TP2 for the transmission of the cover packet E.sub.D=E.sub.Bed to 7.100 via 102.000 is larger than the loss packet E.sub.V.sub.TP1 for the transmission of E.sub.D=E.sub.Bed via 101.000 and thus 101.000 is booked. In the following we consider the path that the booked energy packet E=E.sub.1=E′.sub.Ein.sub.W=E.sub.D⊕E.sub.V.sub.TP1 takes in the transmission from the wind generator 6.100, via the optimally determined transport path 101.000 to the load 7.100. We have again omitted the edge designations in FIG. 1 for the sake of clarity. These result automatically from the position of the edges in the figure. The transmission takes place from 6.100 via the supply edge 5.810, by means of which 6.100 is connected to the supply QFC 2.800. The supply QFC 2.800 then transmits the packet via edge 5.820 by means of which edge the QFC is connected to the supply node 1.800. Via an edge 5.000 connecting 1.800 to the following QFC 2.000, the packet is then transmitted via the ohm node 1.000 via an edge 5.000 and via another QFC 2.000, then via the following edge to the demand node 1.900. The demand QFC 2.900 then transmits the packet to the load 7.100 via the demand edge 5.910, which is connected to 1.900. All ohm and QFC nodes are connected to the data and computer network 200.000 via a data link, just like all sensors of the perimeter network 210.000, which are assigned to the source 6.100. The architecture, structure and components of 200.000 can be seen in FIG. 3 for the data and computer network and the associated description. This also applies to selected sensors in the analogue parts of 6.100 and 7.100 whose measured values are included in the various predictions. For example, the analogue network part has sensors for measuring the power consumed by the individual consumers of 7.100 and transmits these via the perimeter network 210.000 to the responsible control instance 220.000 which is executed on the data and computer network 200.000. The sensor 2.320, like the sensor 2.320 in the analogue part of 7.100, transmits the data via the perimeter network 210.000 to the responsible control instance 220.000. By means of the sensor 2.320, as shown in FIG. 5, the cumulative power consumed by 8.100 is measured on the edge 5.920 of the demand QFC 2.900 and is used as one of the input parameters for the various predictions. Through the routing procedure, the source 6.100, the transport path 101.000 with the energy packet E to be transmitted to cover the demand packet E.sub.Bed of the load 7.100 is determined so that E=E′.sub.Ein.sub.W=E.sub.D⊕E.sub.V.sub.TP1=E.sub.Bed. In the following, we will use our example to explain in more detail how the packets E.sub.Ein.sub.W and E.sub.Bed are determined. At a prediction time t.sup.0, the supply data packet for 6.1000 is determined by means of a supply prediction for the power that can be made available for transmission by the source in the transmission time period T. We assume that for the execution time t.sub.0=t.sup.0+24 h and the duration DT of T is one hour. Accordingly, the demand data packet of load 7.100 must be formed for time period T. The data and computer network 200.000 has a prediction system, as a subsystem of one or more coherently coupled control instances 220.000, which is executed on 200.000. As assumed, T is a typical annual consumption period, in which consumption period the power consumption of 7.100 is well reflected by the temporal trends in the comparison periods of the past.

[0385] For clarification, we simplify our example even further and assume that the measured values for these comparison periods satisfy a Gaussian distribution and have a constant expected value, mean value, over T of <p.sub.Bed(t)>:=<p.sub.Be>=100 kW, ∀t from T, with a constant standard deviation of σ=5%. Thus, in the past, about 99.7% of the values of the power consumption of load 7.100 were in the interval from

−3σ to +3σ and fluctuated within the limits of 85 kW to 115 kW. It is therefore obvious to take these data for the demand prediction of the corresponding transmission period for the same seasonal period. To simplify matters, we further assume in our example that the supply prediction for T, due to seasonally largely constant wind conditions, results in a mean value for the source of a predicted power <p.sub.Ein(t) >=110 kW, ∀t from T. For the standard deviation of the supply prediction, we assume that this is also σ=5%. Based on these predictions, the routing procedure now forms the demand, supply, coverage and loss data packet. The routing procedure checks whether E′.sub.Ein.sub.W=E.sub.D⊕E.sub.V.sub.TP1 can be formed. According to the demand prediction, it is obvious to determine the nominal power of the demand data packets p.sub.nomBed(t)=<p.sub.Bed(t)>=<p.sub.Bed>=100 kW.

[0386] Furthermore, it is obvious to determine the remainder R.sub.Bed(t) of the power class of the demand data packet to be R.sub.Bed(t)=ƒ.sub.Prognose.sub.Bed(σ)=3σ*<p.sub.Bed>=15 kW. Since the standard deviations of the demand prediction and the supply prediction are the same, the power class of the supply data packet can be determined from the supply prediction as {110 kW, 16.5 kW, T}. This then also determines the power class of the coverage packet E.sub.D, with E.sub.D=E.sub.D, to {100 kW, 15 kW, T}. If we now assume for the sake of simplicity that the loss in the transmission of the cover packet is 5%, then the power class of the loss packet E.sub.V.sub.TP1 is equal to (5 kW, 0.75 kW, T). Thus E′.sub.Ein.sub.W=E.sub.D⊕E.sub.V.sub.TP1 is a sub-packet of E.sub.Ein and the energy packet E to be transmitted to meet the demand of load 7.100 from source 6.100 via 101.000 to 7.100 is obtained by booking the data packet with power class {p.sub.nom.sub.E(t)=105 kW, R.sub.E(t)≡15.75 kW, T} of E′.sub.Ein.sub.W. As part of the routing procedure, a contract has been concluded between the source 6.100 and the load 7.100 so that the source will set a physical power at at least one location x.sub.p of the demand edge 5.920, which is an element of the power class of E. Similarly, the load undertakes to take in a power via demand edge 5.920 which is an element of this power class of E at x.sub.p. In our example, this means that the wind generator 6.100 is allowed to supply a physical power of p.sub.φ.sup.Ein(x.sub.p, t)=90 kW via 101.001 into the demand edge 5.920 according to the contract and at the same time the load 7.100 is allowed to take a power of e.sub.φ.sup.Bed(x.sub.p,t)=110 kW from there according to the contract. That is, within the limits set by the power class of the energy packet to be transmitted, there can be an allowable difference or a shortage or excess between the supplied physical power p.sub.φ.sup.Ein(x.sub.p,t) and the power demand p.sub.φ.sup.Bed(x.sub.p, t) at the connection point x.sub.p of the demand edge 5.920 to the demand QFC 2.900. The maximum allowable deviation is therefore

[00023]$\begin{array}{c}.Math.p_{\phi }^{\mathrm{Ein}}\left(x_p,t\right)-p_{\phi }^{\mathrm{Bed}}\left(x_p,t\right).Math.=\delta \left(t\right)\le 30\mathrm{kW}\\ =2.Math.R_{\mathrm{bed}}\\ =2.Math.\frac{R_{\mathrm{Bed}}}{R_E}.Math.R_E\\ =f_C\left(R\right)=C\left(t\right),\end{array}$

leading to ƒ.sub.C(R)≈1.9.Math.R.sub.E. One task of the demand prediction is to predict, in the case that the load has a storage in its analogue part, whether this storage has the potential to absorb or release a maximum power of C(t), ∀t, in order to be able to compensate for the difference δ(t). In the event that the load does not have this potential, the demand prediction is used to instruct the routing procedure to determine a transport graph extended by compensation. In case that the load 7.100 is equipped with a storage in its analogue electrical part that can deliver or receive C(t), the difference δ(t) is compensated by a suitable control, e.g. by the condition P.sub.Bedarf+p.sub.ein(t)+p.sub.Speicher(t)=0, ∀t from T. This is, according to claim 1, the simplest embodiment of the invention, so that by transferring the energy packet of 6.100 via 101.000, the demand of 7.100 is met.

[0387] At this point we would like to note that the improvement in prediction accuracy is immediately reflected in the required storage capacity. For example, if σ can be reduced from 5% to 2.5%. Then C=2R decreases from 30 kW to 15 kW and over the whole period T the maximum energy that must be able to be absorbed or delivered by the storage decreases from 30 kW T to 15 kW T. For this reason, between the reservation and the final booking, further predictions are carried out with ever decreasing intervals between the prediction and the execution time, so that the prediction uncertainty becomes smaller. Reserved but then no longer required capacities are then released again. The sequence of predictions after booking ends with the sequence of real-time predictions. Here, too, capacities that are no longer required are released immediately if they are no longer needed due to the more accurate prediction. If the storage does not have a suitable storage, then an optimally determined extended transport graph is determined by the routing procedure. In our example, FIG. 2 shows the transport graph thus extended by the compensation. This consists of the transport path 101.000 which connects the source 6.100 with the load 7.100 and the compensation node 4.400 which is connected to the demand node of the load 7.100 via the compensation path 106.000. The compensation node is the demand node of the load 7.100. The demand node of the load 7.100 is connected with the compensation node of the source 6.100. The compensation node is a storage device that can absorb a maximum power up to the maximum compensation power C(t) constantly equal to C(t)=30 kW or deliver a power C′(t)=C(t)+v(t) increased by the loss v(t) occurring during the transmission of C(t) for each point in time within the transmission period.

[0388] In case that the source feeds in the physical power p.sub.φ.sup.Ein(x.sub.p, t)=p.sub.φ.sup.Bed(x.sub.p, t)+δ(t), the QFC node 2.410, which is connected on one side to the demand node 1.900 and on the other side to the compensation path 106.000, sets the power δ(t) and the QFC 2.420, which is connected on one side to the compensation path 106.000 and on the other side to the storage as compensation node 4.400, sets the power supplied to 4.400 to {tilde over (δ)}(t)=δ(t)−δ.sub.ν(t). Here δ.sub.ν(t) is the loss that occurs during the transmission of δ(t) via 106,000. In a case wherein p.sub.φ.sup.Ein(x.sub.p, t)=p.sub.φ.sup.Bed(x.sub.p, t)−δ(t), the QFC 2.420 sets the power {tilde over (δ)}(t)=δ(t)+δ.sub.ν(t) in 106.000 and δ(t) is then supplied to demand node 1.900 via QFC 2.410. Since the demand node is an ohm node, taking into account the direction of flow, it follows that the physical power from the demand QFC at the location x.sub.p of the demand edge can be set exactly equal to the demand. To determine δ(t) and δ(t), p.sub.φ.sup.Ein(x.sub.p, t) and ρ.sub.φ.sup.Bed(x.sub.p, t) are determined by predictions, and real-time predictions, respectively. Thus, packets with the power class {p.sub.nom(t)=0, R(t)=C(t),T} are transmitted on the compensation path. By means of a conversion, this then corresponds to the fact that the physical power set for x.sub.p can be represented as the sum of the nominal power of the transmitted energy packet E and a compensation power δ′(t):

p.sub.φ(x.sub.p,t)=p.sub.nom(t)+δ′(t).

[0389] In our example, we had assumed, on the one hand, that both the supply and the demand prediction have the same percentage standard deviation of 5% and, on the other hand, that the function ƒ.sub.Prognose is the multiplication by the factor 3.

[0390] In the following consideration, we want to use the example to show that the function for determining the remainder takes place on a case-by-case basis. To explain this, we will now consider an example, wherein an analogue storage connected to load 7.100 cannot completely provide C(t)=2R.sub.Bed=30 kW. However, the demand prediction shows that the analogue storage can only take in or deliver 10 kW for each point in time of the transmission period. For simplicity, we neglect the losses. In this case, a demand data packet with a remainder R′.sub.Bed(t)=⅔R.sub.Ein(t)=10 kW can be formed based on the demand prediction. The nominal power remains constant and equal to 100 kW over T. Accordingly, the load then requests that the routing determines a transport graph 120.000 extended by compensation. The compensation node must then have a maximum compensation power of C(t)=2, R′.sub.Bed (t). By transmitting the thus modified energy packet E with power class {100 kW, 10 kW, T}, the physical power injected by the source varies in the interval from −2σ to +2α, whereby, on the other hand, the demand of the load varies in the range from −3σ to +3σ. This means that in about 95% of the cases, a possible difference between the physical power injected and the physical power required by the load 7.100 is compensated by the compensation node of 120.000. Thus, via the energy packet and the compensation packet of compensation node 4.400, a maximum physical power p.sub.φ(x.sub.p, t)=p.sub.nom(t)+R′.sub.Bed(t)=110 kW can be injected into the demand edge of load 7.100. In case the demand is e.g. in the interval between +2σ and +3σ, the missing difference is then compensated by the analogue storage. If, for example, the demand is 115 kW, the missing 5 kW in the analogue part is compensated via the control of the analogue storage. In this case, the choice of the new remainder for the demand data packet can simply be justified by the fact that the use of the analogue storage reduces the purchase price for the energy packet and for the compensation.

[0391] It is essential that the sources and loads have concluded a generally valid agreement for the transfer of energy packets. In our example, we assume that the source and the load have committed themselves according to this agreement that in 99.7% of the points in time of a transmission period both injected and absorbed physical power is an element of the agreed energy packet.

[0392] In our example, the source 6.100 can only supply a physical power that is an element of the power class (100 kW, 10 kW, T) of the modified energy packet in approx. 95% of the points in time. At the remaining times, the physical power of the source is in the |2σ| to β3σ| range and there is either a shortage ρ.sup.+, the power is less than 90 kW, e.g. it is 85 kW, or there is an excess ρ.sup.−, the power of 6.100 is greater than 110 kW, e.g. it is 125 kW. To compensate for this gap, the source needs an additional maximum compensating power ID(t)I of 5 kW. Since D(t)=ƒ.sub.D(R(t)) and R(t)=R′.sub.Bed(t) for the modified energy packet, the function ƒ.sub.D is determined as

[00024]$f_D=\left(1-\frac{R\left(t\right)}{R_{\mathrm{Ei��}\left(t\right)}}\right).$

R.sub.Ein(t). Within the framework of the supply prediction, in the case that the source has a connected analogue storage unit, it is also predicted which D(t) the connected analogue storage can absorb or deliver. If the supply prediction shows that 6.100 has such an analogue storage system that can absorb or deliver a physical power up to the maximum balancing power of D(t)=5 kW for each point in time within the transmission period, then the balancing is carried out by this storage system. This means that both a shortage ρ.sup.+(t) and an excess ρ.sup.−(t) are compensated by the storage unit by means of a corresponding control, analogous to compensation.

[0393] If a compensation via an analogue storage is only partially possible or not possible at all, the supply prediction requests an optimised transport graph from the routing procedure, as shown in FIG. 2. In FIG. 2, the balancing node 4.401 is connected to the supply node 1.800 of the source 6.100 via a balancing path 108.000. The routing procedure has determined 4.401 in such a way that this, for example, is a storage facility, can take in a maximum physical power up to the maximum balancing power D(t) or can deliver a physical power up to D′(t)=D(t)+ν.sub.108.00(D(t)). This D(t) is the remaining part that cannot be compensated by an analogue storage of the source 6.100.

[0394] Balancing packets with the power class {0, D(t), T} are then transmitted on the balancing path. At the transmission time, the modified energy packet is then transmitted via the transport path 101.000 and the physical power, corresponding to the flow direction at the two QFCs of the balancing path, is set so that it is either equal to ρ.sup.+(t) or ρ.sup.−(t)

[0395] At this point we want to note that both the supply and demand predictions and the derived formation of the supply, demand, coverage and loss data packets are part of the iterative routing procedure. In addition to the ratios of the expected values z of the demand and supply predictions to each other, the ratio of the variances or standard deviations of these predictions to each other also plays a decisive role in determining the power class of an energy packet to be transmitted using the compensation and balancing mechanism.

[0396] To show the variety of possibilities for determining the energy packet to be transferred, we now modify our example slightly. We assume that the transmission period falls in a period of very stable wind conditions, so that the standard deviation, in contrast to the one considered before, is only half, i.e. σ′=σ.sub.Ein=2.5% and thus R.sub.Ein=3.Math.σ′.Math.<p.sub.Ein(t)>=7.5 kW. If we again neglect the losses for the sake of simplicity, we could set the coverage packet E.sub.D and thus the energy packet E to be transmitted equal to the demand data packet E.sub.Bed with the power class (100 kW, 15 kW, T). We further assume that the load 7.100 has an analogue storage to compensate for the difference C(t)=2.Math.R.sub.Bed between the supplied and required power. Since the physical power supplied by source 6.100 is an element of E.sub.Bed due to the smaller variation by half, the source 6.100 can meet the demand of load 7.100 by transferring this energy pact E=E.sub.D=E.sub.Bed, according to the agreement. But the choice of this packet has the consequence that an unnecessarily large amount of transmission capacity, twice as much as necessary, must be reserved for the transmission of the energy packet. An alternative way to define an energy packet is to set the remainder R.sub.E of the energy packet equal to R.sub.Ein=7.5 kW. In this way, only the transmission capacity that is really needed must be reserved. However, in order to compensate a possible difference, C(t)=ƒ.sub.c(R.sub.Bed) must be set. Since R.sub.Bed can again be expressed as a function of R, in this case, ƒ.sub.c is also a function of R. Since we have assumed that the storage can compensate for this C(t), this energy packet together with 101.000 is determined as the optimal transport graph or transport path due to the transmission costs lowered by half. The example shows that a transport path TP(E, Q, S, T) always consists of a path P in the transmission network that connects the source Q with the load S and an energy packet E, defined by its power class {p.sub.nom(t), R(t),T}.

[0397] Finally, let us briefly look at the transmission of the energy packet and the assigned compensation and balancing packets. For this purpose, we assume that all quantities are “quantised”. For this we assume that the duration DT=100 dt and the duration of all real-time prediction periods is DT.sub.RT=dt. Thus T can be covered by the real-time prediction periods Th.sub.r with l=1 to 100 without intersections. The corresponding real-time predictions are carried out at the real-time prediction periods t.sub.l.sup.000. Here t.sub.l.sup.000 is chosen so that for the execution time t.sub.0=t.sub.1.sup.000+dt and for t.sub.l.sup.000=t.sub.1.sup.000+(l−1).Math.dt. According to the real-time predictions, the nominal powers of the corresponding real-time packets are then formed, so that for the nominal powers of the real-time energy packets are determined to p.sub.nomRT(x.sub.TP,t)=n.sub.ij.sup.TP.Math.dp, of the real-time compensation packets are determined to p.sub.nomRT(x.sub.TP, t)=n.sub.ir.sup.kP.Math.dp, and of the realtime compensation packets are determined to p.sub.nomRT.sup.Aus(x.sub.AP, t)=n.sub.is.sup.AP.Math.dp. Here n.sub.ij.sup.TP, n.sub.ir.sup.kP and n.sub.is.sup.AP are integers greater than or equal to zero, dp is the elementary power, the so-called “power quantum” and dt the “time quantum”. The index j designates the location x of the edge e.sub.j.sup.TP of the transport path TP 101.000. Correspondingly, the indices r and s are to be understood for the edges of the compensation path KP 106.000 and the compensation path AP 108.000. The index i denotes the “quantised” point in time associated with the point in time t with (i−1)≤t≤i.Math.dt.

[0398] In our example, according to the sequence of real-time predictions for the sequence of T.sub.RT.sup.l, the values n.sub.ij.sup.TP, n.sub.ir.sup.kP and n.sub.is.sup.AP are determined by the corresponding control instances 220.000 and transmitted via the corresponding data connections to the CPS 205.000 of the corresponding QFCs 2.000, as in FIG. 5. There, these are converted into the corresponding actuating parameters, e.g. pulse widths for the power actuator 2.300, and transmitted to the actuating device 2.300. The actuating device 2.300 then sets the power actuator 2.300 via the power actuator. This power actuator then sets the power via the power controller, e.g. a bidirectional step-up step-down controller, according to the flow direction at the corresponding connection point of the respective edge 2.110 or at the edge 2.120 of the corresponding QFC. Through this transmission of the corresponding real-time packets, the energy packet is then transmitted from the source to the load and the demand of the load is met according to the contract.

[0399] Finally, we would like to note that with the advances in quantum computing, at least one node of the data and computer network can be a quantum computer. Due to the superior computational power of the quantum computer and the advances in the models for accurate long-term weather prediction that can be run alongside the routing procedure on this quantum computer, a highly dynamic and accurate regenerative hybrid energy supply system can thus be implemented that is superior to today's solutions.

[0400] For purposes of the original disclosure, it is pointed out that all features as they become apparent to a person skilled in the art from the present description, the drawings and the claims, even if they have been specifically described only in connection with certain further features, can be combined both individually and in any combination with others of the features or groups of features disclosed herein, unless this has been expressly excluded or technical circumstances render such combinations impossible or pointless. A comprehensive, explicit presentation of all conceivable combinations of features is omitted here only for the sake of brevity and readability of the description.

[0401] While the invention has been illustrated and described in detail in the drawings and the foregoing description, this illustration and description is by way of example only and is not intended to limit the scope of protection as defined by the claims. The invention is not limited to the disclosed embodiments.

[0402] Variations of the disclosed embodiments will be obvious to those skilled in the art from the drawings, description and appended claims. In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “one” or “a” does not exclude a plurality. The mere fact that certain features are claimed in different claims does not exclude their combination. Reference signs in the claims are not intended to limit the scope of protection.

LIST OF REFERENCE SIGNS

[0403] 100.000 transmission network [0404] 200.000 data and computer network, called control network [0405] 210.000 perimeter sensor network [0406] 220.000 control instance [0407] 205.000 CPS computer node [0408] 110,000 transport graph without compensation and balancing [0409] 120.000 extended transport graph with compensation and balancing [0410] 101.000, 102.000 transport paths [0411] 106.000 compensation path [0412] 108.000 compensation paths [0413] 1.000 ohm node [0414] 1.300 ohm node sensors [0415] 1.800 supply nodes [0416] 1.900 demand nodes [0417] 2.000 QFC nodes [0418] 2.001 QFC [0419] 2.300 bidirectional power controller [0420] 2.110 inner edge with port a): connection point for flexibly connecting the power controller with an outer edge [0421] 2.120 inner edge with port b): connection point for flexible connection of the power controller to an outer edge [0422] 2.310 to 2.320 sensors for measuring the power on the inner edges [0423] 2.400 device for setting the direction of flow and the magnitude of the power on the bidirectional power controller [0424] 205.000 CPS computer [0425] 2.800 supply QFC of the supply edge 5.800 [0426] 2.900 demand edge OFC of demand edge 5.900 [0427] 4.400 compensation node [0428] 4.401 compensation node [0429] 5.000 edge [0430] 5.810 connection part of the supply edge from the source to the supply QFC [0431] 5.820 connection part of the supply edge from the supply QFC to the supply node [0432] 5.910 connection part of the demand edge from the demand QFC to the demand node [0433] 5.920 connection part of the demand edge from the demand QFC to the load [0434] 6.100 wind generators [0435] 6.200 solar generators [0436] 7.100 private household as load