A distributed control node enables monitoring of complex energy signatures for local loads. The control node can identify energy signatures unique to local loads. The energy signature includes a complex current vector for the load in operation identifying the primary current with a real power component and a reactive power component, and identifying one or more harmonics each with a real power component, a reactive power component, and an angular displacement relative to the primary current. Based on the energy signature, the control node can control a noise contribution of the load due to the harmonics as seen at a point of common coupling to reduce noise introduced onto the grid network from the load.

A distributed control node enables local control of reactive power. A consumer node generates local real power on a consumer side of a point of common coupling (PCC). The control node converts local real power into reactive power with a conversion device on the consumer side of the PCC. The control node can deliver the reactive power to the grid to provide VARs to the grid from locally generated real power.

A distributed control node enables local control of reactive power. A consumer node generates local real power on a consumer side of a point of common coupling (PCC). The control node converts local real power into reactive power with a conversion device on the consumer side of the PCC. The control node can deliver the reactive power to the grid to provide VARs to the grid from locally generated real power.

A method of controlling an electricity production station including at least one renewable energy source and an energy accumulation system, allowing an operator to commit, at an electrical distribution network manager, to a power profile P.sub.G that the station will be able to deliver over a forthcoming time period. The declared power profile must, furthermore, comply with constraints imposed by the manager of the electricity distribution network. Non-compliance with this commitment may be subject to penalties. It is then incumbent on the operator to best optimize the method of controlling the electricity production station so as to maximize the electrical power fed into the network, while complying, in so far as possible, over a certain tolerance range, with the power profile commitment P.sub.G.

A method of controlling an electricity production station including at least one renewable energy source and an energy accumulation system, allowing an operator to commit, at an electrical distribution network manager, to a power profile P.sub.G that the station will be able to deliver over a forthcoming time period. The declared power profile must, furthermore, comply with constraints imposed by the manager of the electricity distribution network. Non-compliance with this commitment may be subject to penalties. It is then incumbent on the operator to best optimize the method of controlling the electricity production station so as to maximize the electrical power fed into the network, while complying, in so far as possible, over a certain tolerance range, with the power profile commitment P.sub.G.

Apparatuses, method and systems featuring model predictive voltage and VAR controls with coordination with and optional optimization of autonomous reactive power control such as autonomous distributed energy resource and/or autonomous switched capacitor banks One embodiment includes an electronic control system structured to construct a linearized model of the power distribution system including a plurality of predetermined nodes, operate a model predictive controller to identify optimized control commands using an objective function defined over a plurality of future scenarios over a look ahead time horizon and a plurality of constraints, and transmit the identified control commands to control operation of at least the voltage regulators and the switched capacitor banks.

Distributed grid intelligence can enable a modular power grid. Multiple consumer nodes are coupled to a same point of common coupling (PCC). Local power sources are coupled to the PCC. None of the power sources has sufficient generation capacity alone to meet peak demand of the multiple consumer nodes of the grid segment. The grid segment includes multiple control nodes to control distribution of power from the power sources to the multiple consumer nodes based on power demand from the multiple consumer nodes and based on operation of the other power sources. Thus, consumer nodes can share power generated locally, but operate independently without the need for central management or a central power plant, and different independent segments can be coupled to each other to expand the grid network.

Distributed grid intelligence can enable a modular power grid. Multiple consumer nodes are coupled to a same point of common coupling (PCC). Local power sources are coupled to the PCC. None of the power sources has sufficient generation capacity alone to meet peak demand of the multiple consumer nodes of the grid segment. The grid segment includes multiple control nodes to control distribution of power from the power sources to the multiple consumer nodes based on power demand from the multiple consumer nodes and based on operation of the other power sources. Thus, consumer nodes can share power generated locally, but operate independently without the need for central management or a central power plant, and different independent segments can be coupled to each other to expand the grid network.