METHOD OF CONTROLLING THE RENEWABLE ENERGY USE IN AN LNG TRAIN

Abstract

A method of controlling the renewable energy absorbed by a hybrid power train for driving a load, and in particular compressors for a liquefied natural gas (LNG) plant is disclosed. The method comprises an analysis of the health status of part and of the whole hybrid power plant that drive the load. A power plant is also disclosed, operated by the controlling method.

Claims

1. A method of controlling the renewable energy absorbed by a hybrid power train for driving a load, wherein the hybrid power train comprises one or more equipment, comprising a gas turbine and an electric motor/generator, wherein the electric motor/generator and is connected to a power generation plant (PG) and to a renewable energy source (PV), wherein the method comprises the steps of: detecting the one or more input parameters (P.sub.ij) of each equipment to determine the initial condition of at least one of the equipment; applying a first conditional statement, wherein the first conditional statement determines a combined membership function (M.sub.em+vfd), of at least one or more equipment, having two or more qualification states as output, so that if the combined membership functions (M.sub.em+vfd) of the equipment has qualification state such that the checked equipment operate correctly, then the step of applying a second conditional statement is carried out to the renewable energy source (PV), so as to determine the membership functions (M.sub.pv) of the renewable energy source (PV) having two or more qualification states as output, so that if the membership functions (M.sub.pv) of the renewable energy source (PV) has a qualification state such that the renewable energy source (PV) does not operate correctly, then the step of applying a third conditional statement to the power generation plant (PG) is carried out, so as to determine the membership functions (M.sub.pg) of the power generation plant (PG) having in two or more qualification states as output, so that if the membership functions (M.sub.pg) of the power generation plant (PG) has a qualification state such that power generation plant (PG) does not operate correctly, then change of load split between the gas turbine and the electric motor/generator; if the membership functions (M.sub.pv) of the renewable energy source (PV) has a qualification state such that the renewable energy source (PV) operates in a correct way, then the power generated by the gas turbine and the energy absorbed by the renewable energy source (PV) is determined according to an objective function; else, if the combined membership functions (M.sub.em+vfd) has qualification state such that the equipment checked does not operate correctly, then carrying out the load split between the gas turbine and the electric motor/generator.

2. The method according to claim 1, wherein the equipment comprise a variable detection device connected to electric motor/generator, and to a power generation plant (PG) and to a renewable energy source (PV), wherein in the detecting step the initial condition detected are those of the electric motor/generator and the variable detection device, and wherein the first conditional statement comprises the sub-steps of: associating a parametric membership function (M.sub.em,j) to each input parameter (P.sub.em,j) of the electric motor/generator; combining the parametric membership functions (M.sub.em,j) of the electric motor/generator through a true table (T.sub.em) to obtain health indexes (HI.sub.em,j) and then an equipment membership function (M.sub.em); associating a parametric membership function (M.sub.vfd,j) to each input parameter (P.sub.vfd,j) of the variable frequency device; combining the parametric membership functions (M.sub.vfd,j) of the variable frequency device through a true table (T.sub.vfd) to obtain health in-dexes (HI.sup.vfd,j) and then an equipment membership function (M.sub.vfd); and combining the membership function of each equipment (M.sub.em, M.sub.vfd) for obtaining a combined membership function (M.sub.em+vfd) having two or more qualification states as output.

3. The method according to claim 2, wherein the combined membership function (M.sub.em+vfd) can assume a first qualification state (Bad), a second qualification state (Medium), and a third qualification state (Good), wherein if the combined membership function (M.sub.em+vfd) assumes the first qualification state (Bad), then the step of increasing the gas turbine load and shedding the electric motor/generator is carried out; the second qualification state (Medium), then the step of changing the load split between the gas turbine and the electric motor/generator is carried out; the third qualification state (Good), then applying the second con-ditional statement to the renewable energy source (PV).

4. The method according to claim 1, wherein the second conditional statement comprises the sub-steps of: associating a parametric membership function (M.sub.pv,j) to each input parameter (P.sub.em,j) of the renewable energy source (PV); combining the parametric membership functions (M.sub.pv,j) of the of the renewable energy source (PV) through a true table (T.sub.ev) to obtain health indexes (HI.sub.ev,j) and then to obtain membership function (M.sub.ev) of the of the renewable energy source (PV); wherein the membership function (M.sub.pv) of the renewable energy source (PV) can assume a first qualification state (Bad), a second qualification state (Medium), and a third qualification state (Good), wherein if the membership function (M.sub.pv) of the renewable energy source (PV) assumes the first qualification state (Bad), then applying third conditional statement to the power generation plant (PG); the second qualification state (Medium), the step of changing the load split between the gas turbine and the electric motor/generator is carried out; the third qualification state (Good), then the power generated by the gas turbine and the energy absorbed by the renewable energy source (PV) is determined according to an objective function.

5. The method (5) according to claim 1, wherein the third conditional statement comprises the sub-steps of: associating a parametric membership function (M.sub.pg,j) to each input parameter (P.sub.pg,j) of the power generation plant (PG); combining the parametric membership functions (M.sub.pg,j) of the power generation plant (PG) through a true table (T.sub.pg) to obtain health indexes (HI.sub.pg,j) and then to obtain membership function (M.sub.pg) of the of the power generation plant (PG); wherein the membership function (M.sub.pg) of the power generation plant (PG) can assume a first qualification state (Bad), a second qualification state (Medium), and a third qualification state (Good), wherein if the membership function (M.sub.pv) of the renewable energy source (PV) assumes the first qualification state (Bad), then the step of increasing the gas turbine (21) load and shedding the electric motor/generator is carried out; the second qualification state (Medium), the step of changing (54) the load split between the gas turbine and the electric motor/generator is carried out; the third qualification state (Good), then maintaining the load split.

6. The method according to claim 1, wherein the objective function is that of minimizing the use of the gas turbine, such that the gas turbine load remains above the combustor transfer threshold Pmx.sub.Load, plus a load margin .sub.Load, to handle potential load transients.

7. The method according to claim 1, wherein the step of determining the power generated by the gas turbine and the energy absorbed by the renewable energy source (PV) according to an objective function, comprises the sub-steps of operating to maximize the electric motor/generator operation as helper, and decreasing the gas turbine load down to the value of the transfer threshold Pmx.sub.Load.

8. The method according to claim 1, wherein the input parameters (P.sub.ij) are analog or digital electrical signals.

9. A power plant comprising: a hybrid power train having: a through a shaft, a gas turbine, mechanically connected to the shaft; an electric motor/generator, mechanically connected to the shaft; a variable frequency device, connected to an electric motor/generator, and a power generation plant (PG) and to a renewable energy source (PV), wherein the variable frequency device is operable to allow the electric motor/generator transforming the energy from the power gen-eration plant (PG) and the renewable energy source (PV) to drive the load or to help the operation of the gas turbine; and a plant control unit operably connected to the gas turbine, the electric motor/generator, and the variable frequency device, wherein the plant control unit is configured to control the hybrid power train to maximize the energy used coming from the renewable energy source (PV) by maximizing the driving load of the electric motor/generator, and wherein the load of the gas turbine is kept above the combustor premix transfer threshold (Pmx.sub.Load); and a load mechanically connected to the shaft.

10. The power plant claim 9, wherein the load of the gas turbine is kept above the combustor premix transfer threshold (Pmx.sub.Load) plus a certain load margin (.sub.Load).

11. The power plant according to claim 9, wherein the plant control unit comprises: a processor; a bus, to which the processor is connected to; a database, connected to the bus, so as to be accessed and controlled by the processor; a computer-readable memory, connected to the bus, so as to be accessed and controlled by the processor, a receiving-transmitting module, connected to the bus, for receiving and transmitting data and signals from/to the hybrid power train.

12. The power plant according to claim 9, wherein the renewable energy source is a photovoltaic plant (PV) and/or a wind plant and/or concentrated solar power systems.

13. The power plant according to claim 9, wherein the load comprises one or more centrifugal compressors for refrigerating the natural gas.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0025] A more complete appreciation of the disclosed embodiments of the invention and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:

[0026] FIG. 1 illustrates a control system of a hybrid power train for controlling a load to maximize the use of renewable energy sources;

[0027] FIG. 2 illustrates a schematic of a plant hybrid power train connected to energy sources and to loads to be driven;

[0028] FIG. 3 illustrates a schematic diagram of the plant control unit;

[0029] FIG. 4 illustrates a flowchart of the method of controlling the renewable energies use, according to a first embodiment;

[0030] FIG. 5 illustrates a flow chart of a first conditional statement of the method of controlling the renewable energies use, according to the first embodiment;

[0031] FIG. 6 illustrates a set of signals of the parameters processed by the method of controlling the renewable energies use, according to a first embodiment;

[0032] FIG. 7 illustrates a set of true tables implemented in the method of controlling the renewable energies use, according to a first embodiment;

[0033] FIG. 8 illustrates a flow chart of a second conditional statement of the method of controlling the renewable energies use, according to the first embodiment;

[0034] FIG. 9 illustrates a flow chart of a third conditional statement of the method of controlling the renewable energies use, according to the first embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

[0035] Liquid natural gas is an important source of energy. it is necessary to liquefy the extracted gas. To this end, several compressors are used. To drive the compressors hybrid power trains are used. A hybrid power train comprises a gas turbine and an electric motor/generator. The electric motor/generator is a machine that can be connected, among the other things, to renewable energy plants, to transform the energy produced by such plants and use the same to drive compressors, minimizing, up to an appropriate level, the use of a gas turbine, so as to reduce the pollutants emitted in the ambient.

[0036] According to one aspect, the present subject matter is directed to a method to control the renewable energy use in an LNG train, capable of guaranteeing LNG

[0037] Plant/train reliable operations and avoiding negative impact on train availability when a renewable source is used to supply partially or completely the required power.

[0038] LNG production, being an energy-intensive process, can be seen as storage of renewables or a sink where every Watt produced, regardless of the moment (day, night, winter, or summer) and the quantity it is produced, can be used for the production with no need of physical storage or by minimizing it, and thus very high RTE.

[0039] Referring to FIG. 1 an embodiment of an LNG refrigeration plant is illustrated, and it is indicated with reference number 1. The LNG refrigeration plant 1 comprises a hybrid power train 2, a load 3, connected to, and driven by the hybrid power train 2. A power generation plant PG, which can even be the mains or any usual power generation facility, and renewable energy sources in general, indicated with the reference PV, are both connected to the hybrid power train 2, as better specified below.

[0040] With renewable energy sources PV is intended for any energy plant or system capable of producing energy from renewable sources, like a photovoltaic plant, wind energy plant, a concentrated solar power system, ocean or sea waves energy plant, etc., In the following, without limiting the scope of protection of the solution described, as renewable energy sources PV will be intended a photovoltaic plant. In any case, other renewable energy production plants or a combination thereof can be considered.

[0041] The hybrid power train 2 comprises a gas turbine 21, an electric motor/generator 22, a variable frequency device (VFD) 23, connected to the electric motor/generator 22, and to the power generation plant PG and to the photovoltaic plant PV. The hybrid power train 2 also comprises a shaft 24. The gas turbine 21 and the electric motor/generator 22 are connected to the same shaft 24.

[0042] The power to the load 3 can be derived from the gas turbine 21, the power generation plant PG and/or the photovoltaic plant PV.

[0043] The load 3 shown in FIG. 1 comprises two compressors 31 and 32, for compressing in the embodiment considered the liquefied natural gas. The compressors 31 and 32 are mechanically connected to the shaft 24. However, in other embodiments, different loads can be driven by the hybrid power train 2, such as pumps and the like, without departing from the scope of protection of the solution disclosed.

[0044] In addition, in other embodiments, the compressors are at least one or more than two, depending on the requirements of the plant.

[0045] The gas turbine 21 can be of different kinds, such as, for instance, a double-shaft gas turbine or a single shaft gas turbine. In other embodiments, other types of gas turbines can be installed.

[0046] The electric motor/generator 22 is adapted to operate as a motor, thus transforming electrical energy deriving from the power generation plant PG or from the photovoltaic plant PV in mechanical energy to drive the load 3, or to operate the as a helper, for supplying additional energy to that supplied by the gas turbine 21 required by the load 3, or as a starter, for activating the gas turbine 21. The electric motor/generator 22 can also operate as a generator, injecting any surplus energy generated by the gas turbine 21 into the power generation plant PG or the mains, for instance.

[0047] The variable frequency device 23 is the motor driving device. It is usually used in electro-mechanical drive systems to control AC motor speed and torque by varying motor input frequency and voltage. In general, the VFDs are used to improve performance through advances in semiconductor switching devices, drive topologies, simulation and control techniques, and control hardware and software.

[0048] It is seen that the lecturing motor/generator 22 and the variable frequency device 23 are the devices that manage the combination of energy to supply the load 3.

[0049] As better specified below, each component of the hybrid power train 2 is characterized by a proper health index HI. In particular, the gas turbine 21 is characterized by the health index HI.sub.gt, the electric motor/generator 22 is characterized by the health index HI.sub.em, the variable frequency device 23 is characterized by the health index HI.sub.vfa, as well as the lines of the photovoltaic plant PV and the power generation plant PG can be characterized by relevant health indexes, respectively HI.sub.pv and HI.sub.pg. Through the health index HI.sub.i of each piece of equipment i it is possible to associate a status to each equipment and subsystems and/or combination of equipment and subsystems to determine the status of the same in a synthetical manner and determine the most appropriate energy split to be produced.

[0050] Also, since the meaning of the above-mentioned health indexes HI will be better explained below, they allow checking the operating status of the hybrid power train 2 as a function of the single equipment and as a plant or fleet of plants. In other words, through the health indexes HI it is possible to keep track of the current operation of the equipment of the hybrid power train 2 as well as of the hybrid power train 2 as a whole. Synthetically, the health index of the train is a function of the health indexes of the equipment, and it can be mathematically expressed as

[00001]$\begin{array}{cc}{\mathrm{HI}}_{\mathrm{train}}=f\left(H_i\right).& \left(\mathrm{F1}\right)\end{array}$

[0051] In the following additional details will be given as to how the health indexes of the equipment will be calculated and evaluated as well as the calculation of the health indexes of the hybrid power train 2 as a whole.

[0052] In the following with equipment is indented any part of the hybrid power train 2, namely the gas turbine 21, the electric motor/generator 22, or the variable frequency device 23, as well as parts thereof.

[0053] Referring now to FIG. 2, it is shown how the hybrid power train 2 is controlled to maximize the use of the renewable energy coming from the renewable energy source(s), namely, in the embodiment that is described, the photovoltaic plant PV. In particular, the health indexes H.sub.j of each j-th equipment are determined and introduced into a health index system to be processed in order to achieve the objective function of minimizing the use of the gas turbine 21. Such objective function can be expressed by the following formula

[00002]$\begin{array}{cc}{\mathrm{Objective}}_{\mathrm{function}}=\min .Math.{\mathrm{GT}}_{\mathrm{Load}}-\left({\mathrm{Pmx}}_{\mathrm{Load}}+{}_{\mathrm{Load}}\right).Math.& \left(\mathrm{F2}\right)\end{array}$

where the objective function Objective.sub.function has the scope of driving the gas turbine 21, and the electric motor/generator 22 has the scope of maximizing the renewable energy and the maximum allowable power in the electric motor/generator 22. Also, if all the condition on the heath indexes HI are satisfied, the maximization of the photovoltaic plant PV need to target the gas turbine 21 load, such that the gas turbine load remains above the combustor Premix transfer threshold Pmx.sub.Load, plus a certain load margin .sub.Load, to handle any potential load transient. When the gas turbine 21 load achieves the target load, the objective function Objective.sub.function achieves the minimum of the function. Also. The gas turbine 21 premix transfer threshold Pmx.sub.Load could be calculated by the gas turbine 21 digital interface 211, which is connected to the plant control unit 4. The digital interface 211 is a model (digital twin model) of the hybrid power train 2 and the ambient the latter operates, capable of representing the performance of the combined system. The digital interface 211 model can be based on artificial intelligence, machine learning, physics-based or a combination of them.

[0054] The gas turbine combustion system needs to operate in a defined operating envelope to allow premixed combustion mode. In a premixed combustion mode, the fuel and the air are perfectly mixed and the resulting is a wide region of premixed flame with reduced diffusion flame. This allows a significant reduction of pollutant formation such as NO.sub.x and CO. Premix operating envelope is limited to medium-high GT load, therefore a precise threshold below which the premix mode is not possible is calculated by the engine model to provide information to control the minimum load at which the turbine can maintain premix operation mode.

[0055] Also the load margin .sub.Load is kept above the premix transfer threshold to ensure to do not cross the threshold and enter in diffusion flame operation mode which produces high pollutant content.

[0056] In some embodiments, the health index processing could be done remotely or in local (Edge) or a combination of the two.

[0057] In general, the plant control unit 4 (which can be or can be part of a local controller of a subsystem) is programmed or configured to obtain the objective function on the basis of some constraints based on the performance of the plant to be controlled, namely, in the present embodiment, the hybrid power train 2. In the embodiment illustrated in FIG. 2, the constraints are connected to the maximum energy that an electric motor/generator 22 can generate, and the power range the gas turbine 21 can work, namely

[00003]$\begin{array}{cc}\{\begin{array}{c}{\mathrm{EM}}_{\max \mathrm{Power}}=f\left(x_i.Math.\right)\mathrm{Const}\\ {\mathrm{GT}}_{\mathrm{Max}\mathrm{Power}}=\mathrm{Output}\\ {\mathrm{GT}}_{\mathrm{Min}\mathrm{Power}}=\mathrm{Output}\end{array}& \left(\mathrm{F3}\right)\end{array}$

[0058] In particular, EM.sub.maxPower is the electric motor/generator 22 maximum power function in a health status. It is noted that some upset conditions might require a reduction in motor loading; GT.sub.MaxPower is the maximum power of the function of ambient temperature, engine degradation, inlet and exhaust losses, etc., The plant control unit 4 calculates the remaining load capability for the engine to be communicated to process control system; and GT.sub.MinPower is the gas turbine 21 minimum power, which is function of ambient temperature, engine degradation, inlet and exhaust losses, flame temperature, etc. In this case, the plant control unit 4 calculates the remaining margin to minimum load to maintain combustion mode in premix and minimize NO.sub.x emission.

[0059] As mentioned above, plant control unit 4 of the hybrid power train 2 is programmed to control the operation of the hybrid power train 2 on the basis of a specific computer program, as better detailed below. The control unit 4 is also operatively connected to the gas turbine 21, and any part or equipment thereof. In a similar manner, the plant control unit 4 is operatively connected to the electric motor/generator 22, as well as to the variable frequency device 23. Also in this case, the plant control unit 4 is programmed to control and to check parts of the electric motor/generator 22 and of the variable frequency device 23.

[0060] As mentioned above, the plant control unit 4 is programmed to run a computer program to manage a fluctuating external source (namely the renewable energy sources, like the photovoltaic plant PV), for optimizing the energy production of the gas turbine 21 and other equipment availability and reliability. Also, since the LNG refrigeration plant 1 is typically energy-intensive, the program reduces the need of storage since power is constantly needed (increased Photo Voltaic Storage Efficiency, etc.). The plant control unit 4 can be remotely connected or wire-connected to the hybrid power trains 2 of the LNG refrigeration plant 1.

[0061] The plant control unit 4 can be connected to one or more hybrid power trains 2, namely to a fleet of hybrid power trains 2. In this connection, the control unit 4 can optimize the operation of the entire fleet.

[0062] In some embodiments, and particularly referring to FIG. 3, the plant control unit 4 may include: a processor 41, a bus 42, to which the processor 41 is connected to, a database 43, connected to the bus 42, so as to be accessed and controlled by the processor 41, a computer-readable memory 44, also connected to the bus 42, so as to be accessed and controlled by the processor 41, a receiving-transmitting module 45, connected to the bus 42, for receiving and transmitting data and signals from/to the hybrid power train 2.

[0063] As mentioned above, the power control unit 4 runs a program for controlling the hybrid power train 2, in order to optimize the energy production, the energy absorbed from the renewable resources, namely, in the embodiment that is described, the photovoltaic plant PV, and therefore for reducing the emission of NO.sub.x and CO.sub.2.

[0064] Referring to FIG. 4, the general method upon which the program is based for controlling the LNG plant 1 run by the plant control unit 4 is schematically illustrated.

[0065] Specifically, FIG. 4 illustrates a flowchart. The method 5 comprises (see FIGS. 4 and 5) a detecting step 51, where the real-time conditions of the hybrid power train 2 are checked. In particular, in this preliminary step, the gas turbine 21 load and the electric motor/generator 22 partial load is determined.

[0066] Specifically, the plant control unit 4, as mentioned above, is connected to the gas turbine 21, the electric motor/generator 22, and the variable frequency device 23. From each of this equipment the plant control unit 4 receives one or more input parameters P.sub.ij, where the index i labels one or more equipment of the hybrid power train 2, while the index j labels the parameters. Each piece of equipment might be checked through different parameters. In the embodiment that is described the equipment checked are the electric motor/generator 22 and the variable frequency device 23.

[0067] However, additional or different equipment can be considered for this initial checking step.

[0068] The parameters P.sub.ij are signals representing the equipment performance. There will be a total number of ji parameters, namely j signals times i equipment. The parameters signals allow determining the degree of operating capability of equipment. Also, their value, shape, or spectrum is/are influenced by the need for maintenance of any specific equipment.

[0069] For each parameter signal P.sub.ij a parametric membership function M.sub.ij is assigned (step 5211, referring to the electric motor/generator 22), which represents the j membership function of the equipment i. Each membership function M.sub.ij can have different forms or shapes, as can be also appreciated in greater detail in FIG. 6. The parametric membership function M.sub.ij is a logic state function, which can assume in the present embodiment, three possible values or qualification states, as a function of the value of each parameter P.sub.ij signal, namely Low (equipment under analysis not operating in a proper condition), medium (equipment under analysis still operating, although not in optimal conditions), and high (equipment correctly operating). In other embodiments the membership functions M.sub.ij can assume a different number of qualification states.

[0070] Continuing referring to FIG. 5, and considering also FIG. 7, once a parametric membership function M.sub.ij is associated with the parameters P.sub.ij signals received, for each piece of equipment i, the outcomes of the parametric membership functions M.sub.ij are combined (5221) through true tables Ti to obtain a set of equipment health index HI.sub.ij for each i-th equipment, from which an equipment membership function M.sub.em (see step 5231).

[0071] Therefore, referring to the electric motor/generator 21, from the parameters P.sub.em,j, membership functions M.sub.em,j are obtained, the true table T.sub.em applies combination rules to the membership functions M.sub.em, j, to calculate the electric motor/generator 21 health indexes HI.sub.em,j to obtain the membership function M.sub.em of the electric-motor generator 22 of the hybrid power train 2.

[0072] Likewise, referring to the electric motor/generator 22, from the parameters P.sub.vfd,j, membership functions M.sub.vfd,j are obtained, the true table T.sub.vfd applies combination rules to determine the health indexes HI.sub.vfd,j and the relevant membership functions M.sub.vfd,j, so as to calculate the membership function M.sub.vfd of the variable frequency drive 23 of the hybrid power train 2. FIG. 7 illustrates an example of line of code whereby the stages of some equipment are properly combined (see steps 5212, 5222, 5223).

[0073] The conditional statement subprocess 52, namely the membership function of each equipment, namely M.sub.em and M.sub.vfd can assume three different outputs, namely three different qualifications fuzzy states, here referred to as indicated as Bad, Medium or Good. More specifically, the first conditional step 52 comprises a combination sub-step 524 for obtaining a combined membership function M.sub.em+vfd, which can still assume the three different outputs or qualification fuzzy states, here still referred to as Bad, Medium or Good.

[0074] In case of the combined membership function M.sub.em+vfd assumes the value Bad, then the electric motor/generator 22 and/or the variable frequency device 23 are not working in good technical conditions. A first set of operating actions are carried out (step 53) by the plant control unit 4. In particular, the gas turbine 21 load is increased, the electric motor/generator is shed and the entire process load is reduced.

[0075] In case of the membership function M.sub.em+vfd assumes the value Medium, then, although the electric motor/generator 22 and the variable frequency device 23 can still operate without affecting excessively the pollution or in any case not to compromise the operation of the hybrid power train 2, (step 54) the load split between the gas turbine 21 and the electric motor/generator 22 is changed. In some circumstances, the process load can be also reduced. In this case, it is also communicated by the plant control unit 4 the status process to regulate the overall train load based on gas turbine 21electric motor/generator 22 load capability.

[0076] Finally, in case of the membership function M.sub.em+vfd assumes the value Good, the electric motor/generator 22 and the variable frequency device 23 are working in optimal or proper conditions.

[0077] In this case, a second conditional statement is carried out (step 55), to determine the photovoltaic source PV health indexes HI.sub.pv,j, or in general the health index of any renewable energy sources. Specifically, referring to FIG. 8, the sub-steps of the conditional statement subprocess 55 are shown. There can be more than one parameter P.sub.pv,j (see sub-step 551), that are counted by the index j. Each parameter P.sub.pv,j has a specific signal and a true table T.sub.pv, referred to the equipment at issue, namely the photovoltaic source PV. The true table T.sub.pv allow the application of proper combination rules among the parameter signals P.sub.pv,j of the photovoltaic plant PV, so as to calculate the health index HI.sub.pv of the same and determine the membership function M.sub.pv of the photovoltaic source PV, which can assume three qualification states, Bad, Medium, or Good.

[0078] In case of the membership function M.sub.pv of the photovoltaic source PV assumes the value Bad, the photovoltaic source PV does not work in a proper way, then the power generation unit PG is checked by carrying out a third conditional statement subprocess 56, which is also shown in FIG. 9. The operating check of the power generation unit PG is carried out, from a procedural standpoint, analogous to that of the photovoltaic plant 55.

[0079] FIG. 9 shows the sub-steps of the third conditional statement 56. Also, in this case, there can be more than one parameter P.sub.pg,j (see sub-step 561), likewise, the photovoltaic plant PV, that is counted by the index j. Each parameter P.sub.pg,j is associated to a parametric membership function M.sub.pg,j (step 562) has a specific signal and a true table T.sub.pg (step 563), referred to the equipment at issue, namely the power generation plant PG. The true table T.sub.pg allow the application of proper combination rules among the parameter signals P.sub.pg,j of the power generation plant PG, to calculate the health index HI.sub.pg,j for each parameter signals P.sub.pg,j, and then membership function M.sub.pg of the power generation plant PG, which can assume three qualification states, Bad, Medium, or Good.

[0080] If the qualification state of the membership function M.sub.pg is Bad, then the load 3 split is changed (go to step 53), thus the gas turbine 21 load is increased, the electric motor/generator is shed and the entire process load is reduced.

[0081] If the value of the membership function M.sub.pg is Medium, then the step 54 is carried out by the plant control unit 4, namely, the load split between the gas turbine 21 and the electric motor/generator 22 is changed. In some circumstances, the processing load can be also reduced. In this case, it is also communicated by the plant control unit 4 the status process to regulate the overall train load based on gas turbine 21electric motor/generator 22 load capability.

[0082] Finally, if the value of the membership function M.sub.pg is Good, then the load split is maintained as per initial conditions (step 57).

[0083] Coming back to step 55, namely the second conditional statement 5, if the membership function M.sub.pv of the photovoltaic plant PV assumes the value Medium, then the load of the electric motor/generator 22 is increased to operate as helper, up to an allowable presettable threshold (step 58).

[0084] Finally, if the membership function M.sub.pv of the photovoltaic plant PV assumes the value Good, then a rearrangement or different split (step 59) of the power generated by the electric motor/generator 22 and the gas turbine 21 is achieved. Specifically, the electric motor/generator 22 is operated to maximize the load as helper (step 591), namely the operation of the electric motor/generator 22 and the gas turbine 21 load is decreased (step 592) down to the value of the Premix transfer threshold Pmx.sub.Load. Also, it is achieved the objective function of minimizing the use of the gas turbine 21. Such objective function can be expressed by the formula (F2) mentioned above.

[0085] An advantage of the solution disclosed is that of optimizing the efficiency of the train when typical intermittency and cyclicity of renewable energy is taken in consideration

[0086] An additional advantage of the solution disclosed is that of ensuring that availability of the LNG trains is optimized, analyzing healthiness of the electric motor/generator, the viable frequency device and of the gas turbine, and acting on power balance to reduce risks of loss of production.

[0087] In addition, through the solution disclosed it's possible to optimize the emission of pollutants, ensuring CO.sub.2 (produced at system level plus Fuel) and NO.sub.x and CO (produced at combustion level) production are minimized. This is also achieved by blending between renewable sources and conventional.

[0088] In addition, the solution disclosed allows optimizing the overall cost of liquefied natural gas production, taking in consideration the cost of fuel and the cost of renewable energy. This is also achieved by recognizing equipment health status and aging for maintenance scheduling and plant availability optimization. Equipment under analysis are generator, motors, variable frequency devices (i.e., partial discharge, dedicated instrumentation installed). In particular, equipment data monitoring and analysis (real-time or postprocessing) allow recognizing and optimizing operative conditions that may affect production.

[0089] Recognize VFD's and motor's health statuses for maintenance scheduling and optimize the plant availability.

[0090] Gas turbine operating profile optimization to minimize pollutants in general, not limited to CO.sub.2 but considering also NO.sub.x.

[0091] An additional advantage of the present disclosure is that of reducing the carbon intensity of an LNG plant from 10% to 15% with no impact on production, availability, and reliability, only by optimization of the trains' operation, and increasing flexibility in hot gas parts' management.

[0092] Another advantage of the method disclosed in that it makes renewable power storage optional (LNG process consumes energy produced), maximizing renewable RTE, through advanced control of the LNG train, combined with the architecture of the train itself, so as to substantially optimize RTE of the renewable utilization and CAPEX of the renewable source.

[0093] While aspects of the invention have been described in terms of various specific embodiments, it will be apparent to those of ordinary skill in the art that many modifications, changes, and omissions are possible without departing from the spirit and scope of the claims. In addition, unless specified otherwise herein, the order or sequence of any process or method steps may be varied or re-sequenced according to alternative embodiments.

[0094] Reference has been made in detail to embodiments of the disclosure, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation of the disclosure, not limitation of the disclosure. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present disclosure without departing from the scope or spirit of the disclosure. Reference throughout the specification to one embodiment or an embodiment or some embodiments means that the particular feature, structure or characteristic described in connection with an embodiment is included in at least one embodiment of the subject matter disclosed. Thus, the appearance of the phrase in one embodiment or in an embodiment or in some embodiments in various places throughout the specification is not necessarily referring to the same embodiment(s). Further, the particular features, structures or characteristics may be combined in any suitable manner in one or more embodiments.

[0095] When elements of various embodiments are introduced, the articles a, an, the, and said are intended to mean that there are one or more of the elements. The terms comprising, including, and having are intended to be inclusive and mean that there may be additional elements other than the listed elements.

[0096] Barzan & Zanardo Roma S. p. A.