Wind-solar-wind power storage integrated coordinated control method, device and equipment and storage medium

Abstract

The application provides a wind-solar-thermal storage integrated coordinated control method and device, equipment and storage medium. The method comprises the following steps: obtaining a scheduling instruction; sending the scheduling instruction to an administrator terminal; receiving a running mode instruction sent by the administrator terminal; obtaining an optimization target and a constraint condition corresponding to a controlled power station group or a controlled power station according to the running mode instruction; updating a preset optimization model according to the optimization target and the constraint condition; obtaining real-time running data of the controlled power station group or the controlled power station; inputting the real-time running data and the corresponding target power into the updated optimization model to obtain a to-be-processed power instruction of each controlled power station; performing data preprocessing on the to-be-processed power instruction of each controlled power station to obtain an actual power instruction of each controlled power station; and sending the actual power instruction of each controlled power station to each controlled power station respectively. The regulation mode is more flexible, and the scheduling mode can be flexibly switched according to the scheduling mode of the power grid.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power multi-energy complementary coordinated operation, and in particular to a wind-solar-thermal-storage integrated coordinated control method, device, equipment and storage medium. BACKGROUND

[0002] The wind-solar-thermal-storage large base project is a large-scale and intensive construction project mainly including a wind farm, a photovoltaic power station, a thermal power plant and an energy storage power station. The wind-solar-thermal-storage large base project is a new thing, and there is no mature case in terms of regulation mode and system device.

[0003] At present, the most widely used new energy station control system adopts a dispatching mode in which a dispatching center of a power grid formulates a dispatching plan according to power prediction and clearing price information sent by each power station, and sends a dispatching instruction to each wind farm, photovoltaic power station and the like, and then a regulation system or device of each station controls the output of each generator unit, so that the output of a station grid connection point reaches a target value of the dispatching of the power grid.

[0004] However, because the specific dispatching mode after completion of the large base project cannot be determined at the initial stage of construction, the conventional station control system has the problem that the regulation mode is not flexible and cannot be flexibly switched according to the dispatching mode of the power grid. SUMMARY

[0005] The present application provides a wind-solar-thermal-storage integrated coordinated control method, device, equipment and storage medium to solve the technical problem that the regulation mode of the prior art is not flexible and cannot be flexibly switched according to the dispatching mode of the power grid.

[0006] In a first aspect, the present application provides a wind-solar-thermal-storage integrated coordinated control method, comprising:

[0007] obtaining a dispatching instruction;

[0008] sending the dispatching instruction to an administrator terminal, so that the administrator terminal generates a running mode instruction in response to an input operation of an administrator according to the dispatching instruction; wherein the running mode instruction includes a separate control instruction and a combined control instruction, wherein the separate control instruction includes a plurality of controlled power stations and a target power corresponding to each controlled power station, and the combined control instruction includes a controlled power station group and a target power corresponding to the controlled power station group;

[0009] receiving the running mode instruction sent by the administrator terminal;

[0010] parsing the running mode instruction to obtain a combined control instruction, and obtaining an optimization target and a constraint condition corresponding to the controlled power station group according to the combined control instruction;

[0011] updating a preset optimization model according to the optimization target and the constraint condition;

[0012] acquiring real-time operation data of each controlled power station in the controlled power station group;

[0013] inputting the real-time operation data and a target power corresponding to the controlled power station group into the updated optimization model to obtain a to-be-processed power instruction of each controlled power station in the controlled power station group;

[0014] performing data preprocessing on the to-be-processed power instruction of each controlled power station to obtain an actual power instruction of each controlled power station;

[0015] sending the actual power instruction of each controlled power station to each controlled power station in the controlled power station group;

[0016] analyzing the operation mode instruction to obtain the individual control instruction, and for each controlled power station in the individual control instruction, performing the following steps:

[0017] acquiring an optimization target and a constraint condition corresponding to the controlled power station;

[0018] updating a preset optimization model according to the optimization target and the constraint condition;

[0019] acquiring real-time operation data of the controlled power station;

[0020] inputting the real-time operation data of the controlled power station and a target power corresponding to the controlled power station into the updated optimization model to obtain a to-be-processed power instruction of the controlled power station;

[0021] performing data preprocessing on the to-be-processed power instruction of the controlled power station to obtain an actual power instruction of the controlled power station;

[0022] sending the actual power instruction to the controlled power station.

[0023] Optionally, the method described above, the sending the scheduling instruction to the administrator terminal comprises: performing approval verification on the scheduling instruction to generate a verification result; and if the verification result is a verification pass, sending the scheduling instruction to the administrator terminal.

[0024] Optionally, the method described above, the performing data preprocessing on the to-be-processed power instruction of each controlled power station to obtain an actual power instruction of each controlled power station comprises: performing data verification on the to-be-processed power instruction of each controlled power station to obtain a depolarization power instruction of each controlled power station; and performing amplitude limiting and speed limiting processing on the depolarization power instruction of each controlled power station to obtain an actual power instruction of each controlled power station.

[0025] Optionally, the method as described above, the dispatching instruction is a dispatching instruction for the integrated wind-solar-thermal-storage power plant.

[0026] Optionally, the method as described above, if the combined control instruction or the individual control instruction includes a thermal power plant, the constraint condition includes a thermal power plant output upper and lower limit constraint and a thermal power plant ramp rate constraint:

[0027] The formula of the thermal power plant output upper and lower limit constraint is:

[0028]

[0029] In the formula, Pg i,t represents the power generation power of the i-th thermal power plant at time t; represents the upper limit of the power generation power of the i-th thermal power plant at time t; represents the lower limit of the power generation power of the i-th thermal power plant at time t;

[0030] The formula of the thermal power plant ramp rate constraint is:

[0031] -P i down ≤Pg i,t -Pg i,t-1 ≤P i up

[0032] In the formula, P i down represents the maximum downhill rate of the i-th thermal power plant at adjacent two time points; P i up represents the maximum uphill rate of the i-th thermal power plant at adjacent two time points;

[0033] Correspondingly, the method as described above, the method further includes: acquiring the power generation power upper limit, the power generation power lower limit, the maximum downhill rate at adjacent two time points, and the maximum uphill rate at adjacent two time points of each thermal power plant.

[0034] Optionally, the method as described above, if the combined control instruction or the individual control instruction includes a wind farm, the constraint condition includes a wind power upper and lower limit constraint;

[0035] The formula of the wind power upper and lower limit constraint is:

[0036]

[0037] In the formula, Pwi,t Pi(t) is the power generated by the i th wind farm at time t; Pi(t) is the power generated by the i th wind farm at time t;

[0038] Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquiring the upper and lower limits of the wind power of each wind farm; and correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquiring the upper and lower limits of the wind power of each wind farm.

[0039] Optionally, in the method described above, if the photovoltaic power station is included in the combined control instruction or the individual control instruction, the constraint condition comprises a photovoltaic power upper and lower limit constraint;

[0040] The formula of the photovoltaic power upper and lower limit constraint is:

[0041]

[0042] In the formula, Ps i,t Pi(t) is the power generated by the i th photovoltaic power station at time t; Pi(t) is the power generated by the i th photovoltaic power station at time t;

[0043] Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquiring the upper and lower limits of the wind power of each wind farm; and correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquiring the upper and lower limits of the wind power of each wind farm.

[0044] Optionally, in the method described above, if the energy storage power station is included in the combined control instruction or the individual control instruction, the constraint condition comprises an energy storage power constraint and an energy storage battery health state constraint;

[0045] The formula of the energy storage power constraint is:

[0046]

[0047] In the formula, Pessc i,t Pi(t) is the power generated by the i th photovoltaic power station at time t; Pi(t) is the power generated by the i th photovoltaic power station at time t; Pi(t) is the power generated by the i th photovoltaic power station at time t; i,t Pi(t) is the power generated by the i th photovoltaic power station at time t; Pi(t) is the power generated by the i th photovoltaic power station at time t; Pi(t) is the power generated by the i th photovoltaic power station at time t;

[0048] The formula of the energy storage battery health state constraint is:

[0049]

[0050] SOCi(t) is the average battery state of charge of the i-th energy storage power station at time t; i,t SOCi(t) is the average battery state of charge of the i-th energy storage power station at time t; SOCi(t) is the average battery state of charge of the i-th energy storage power station at time t; SOCi(t) is the average battery state of charge of the i-th energy storage power station at time t;

[0051] Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquiring the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station; and correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquiring the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station.

[0052] Optionally, in the method described above, the optimization target corresponding to the combined control instruction is the minimum sum of the scheduling instruction tracking deviation and the cost of each controlled power station in the combined control instruction;

[0053] The formula of the optimization target is as follows:

[0054] minf c = E + θ g Cg + θ w Cw + θ s Cs + θ ess Cess

[0055] In the formula, θ g , θ w , θ s , θ ess is a binary variable, indicating whether the thermal power plant, the wind farm, the photovoltaic power station or the energy storage power station participates in the combined control, and when being 0, it indicates that the corresponding power station does not participate in the combined control, and when being 1, it indicates that the corresponding power station participates in the combined control; E is the scheduling instruction tracking deviation; Cg is the thermal power plant operation and machine starting cost; Cw is the wind power curtailment cost; Cs is the photovoltaic curtailment cost; and Cess is the energy storage operation cost.

[0056] The formula of the scheduling instruction tracking deviation is as follows:

[0057]

[0058] In the formula, n is the total number of the thermal power plant, the wind farm, the photovoltaic power station or the energy storage power station controlled individually; Pcmdi,t Pi,t represents the dispatch instruction value of the ith power station at time t; Pact i,t Pi,t represents the actual output of the ith power station at time t; Pact i,t Pi,t represents the line loss of the ith power station at time t; Pact

[0059] The formula of the thermal power plant operation and starting cost is:

[0060]

[0061] In the formula, Tg represents the operation duration of the thermal power plant; ng represents the total number of controlled thermal power plants; a i Pg i,t 2 +b i Pg i,t +c i represents the operation cost of the ith thermal power plant, a i , b i , c i are the operation cost function coefficients of the ith thermal power plant, Pg i,t is a decision variable, representing the output of the ith thermal power plant at time t; q i,t is a binary variable, representing the starting state of the ith unit at time t, and is 0 when the unit is stopped and is 1 when the unit is running; is the starting cost of the ith thermal power plant;

[0062] The formula of the wind power curtailment cost is:

[0063]

[0064] In the formula, Tw represents the operation duration of the wind farm; nw represents the total number of controlled wind farms; λw is the wind farm curtailment cost factor; Pw i,t is a decision variable, representing the power generation of the ith wind farm at time t;

[0065] The formula of the photovoltaic curtailment cost is:

[0066]

[0067] In the formula, Ts represents the operation duration of the photovoltaic power station; ns represents the total number of controlled photovoltaic power stations; λs is the photovoltaic power station curtailment cost factor; Ps i,t is a decision variable, representing the power generation of the ith photovoltaic power station at time t;

[0068] The formula of the energy storage operation cost is:

[0069]

[0070] In the formula, Te represents the operation duration of the energy storage power station; ne represents the total number of the controlled energy storage power stations; λe is the operation cost factor of the energy storage power station; SOC i,t is the average battery state of charge of the i th energy storage power station at time t; is the maximum average battery state of charge of the i th energy storage power station at time t; is the minimum average battery state of charge of the i th energy storage power station at time t; Pess i,t is a decision variable, representing the power of the i th energy storage power station at time t, and when it is positive, it represents power generation, at this time Pess i,t = Pessd i,t , and when it is negative, it represents charging, at this time Pess i,t = -Pessc i,t , Pessc i,t is the charging power of the i th energy storage power station at time t, and Pessd i,t is the discharging power of the i th energy storage power station at time t;

[0071] Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquiring the real-time line loss of each controlled power station in the controlled power station group; and if it is determined that the combined control instruction comprises an energy storage power station, acquiring the real-time average battery state of charge, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station in the controlled power station group.

[0072] Optionally, in the method described above, if the individual control instruction comprises a thermal power plant, the optimization target corresponding to the thermal power plant is the minimum sum of the dispatch instruction tracking deviation and the thermal power plant operation and start-stop cost;

[0073] The formula of the optimization target is:

[0074] minf g = E + Cg

[0075] In the formula, E is the dispatch instruction tracking deviation; and Cg is the thermal power plant operation and start cost.

[0076] Optionally, in the method described above, if the individual control instruction comprises a wind power plant, the optimization target corresponding to the wind power plant is the minimum sum of the dispatch instruction tracking deviation and the wind power plant abandoned power cost;

[0077] The formula of the optimization target is:

[0078] minf w=E+Cw

[0079] Wherein, E is the scheduling instruction tracking deviation; and Cw is the wind power curtailment cost.

[0080] Optionally, in the method described above, if the individual control instruction includes a photovoltaic power station, the optimization objective corresponding to the photovoltaic power station is the sum of the scheduling instruction tracking deviation and the photovoltaic curtailment cost being minimum.

[0081] Wherein, the formula of the optimization objective is:

[0082] minf s =E+Cs

[0083] Wherein, E is the scheduling instruction tracking deviation; and Cs is the photovoltaic curtailment cost.

[0084] Optionally, in the method described above, if the individual control instruction includes an energy storage power station, the optimization objective corresponding to the energy storage power station is the sum of the scheduling instruction tracking deviation and the energy storage operation cost being minimum.

[0085] Wherein, the formula of the optimization objective is:

[0086] minf e =E+Cess

[0087] Wherein, E is the scheduling instruction tracking deviation; and Cess is the energy storage operation cost.

[0088] Optionally, in the method described above, the scheduling instruction includes a power grid scheduling instruction and a manual scheduling instruction.

[0089] In a second aspect, the present application provides a wind-solar-thermal-storage integrated coordinated control device, comprising:

[0090] An acquisition module, configured to acquire a scheduling instruction;

[0091] A sending module, configured to send the scheduling instruction to an administrator terminal, so that the administrator terminal generates a running mode instruction in response to an input operation of an administrator according to the scheduling instruction; wherein the running mode instruction includes an individual control instruction and a combined control instruction, wherein the individual control instruction includes a plurality of controlled power stations and one target power corresponding to each controlled power station, and wherein the combined control instruction includes a controlled power station group and one target power corresponding to the controlled power station group;

[0092] A receiving module, configured to receive the running mode instruction sent by the administrator terminal;

[0093] An analysis module, configured to analyze the running mode instruction to obtain a combined control instruction, and acquire an optimization objective and a constraint condition corresponding to the controlled power station group according to the combined control instruction;

[0094] an updating module, configured to update a preset optimization model according to the optimization target and the constraint condition;

[0095] The acquisition module is further configured to acquire real-time operation data of each controlled power station in the controlled power station group.

[0096] The input module is configured to input the real-time operation data and the target power corresponding to the controlled power station group into the updated optimization model, to obtain a to-be-processed power instruction of each controlled power station in the controlled power station group.

[0097] The data processing module is configured to perform data preprocessing on the to-be-processed power instruction of each controlled power station, to obtain an actual power instruction of each controlled power station.

[0098] The sending module is further configured to send the actual power instruction of each controlled power station to each controlled power station in the controlled power station group.

[0099] The individual control module is configured to parse the operation mode instruction to obtain the individual control instruction, and for each controlled power station in the individual control instruction, perform the following steps: acquiring an optimization target and a constraint condition corresponding to the controlled power station; updating a preset optimization model according to the optimization target and the constraint condition; acquiring real-time operation data of the controlled power station; inputting the real-time operation data of the controlled power station and a target power corresponding to the controlled power station into the updated optimization model, to obtain a to-be-processed power instruction of the controlled power station; performing data preprocessing on the to-be-processed power instruction of the controlled power station, to obtain an actual power instruction of the controlled power station; and sending the actual power instruction to the controlled power station.

[0100] In a third aspect, a service device is provided, which includes a processor and a memory connected with the processor in communication;

[0101] The memory stores computer-executable instructions.

[0102] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the wind-solar-thermal storage integrated coordinated control method as described in the first aspect and various possible designs of the first aspect.

[0103] In a fourth aspect, a computer-readable storage medium is provided, which stores computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method as described in the first aspect and various possible designs of the first aspect.

[0104] In a fifth aspect, an embodiment of the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method in the first aspect and various possible designs of the first aspect.

[0105] The wind-solar-fire-storage integrated coordinated control method, device, equipment and storage medium provided by the present application receive the operation mode instruction sent by the administrator terminal, obtain the optimization target and constraint condition corresponding to the controlled power station or controlled power station group according to the operation mode instruction, update the preset optimization model according to the optimization target and constraint condition, input the real-time operation data and target power of the controlled power station or controlled power station group into the updated optimization model, obtain the actual power instruction of each controlled power station in the controlled power station or controlled power station group, and send the actual power instruction to each controlled power station of the controlled power station or controlled power station group. The method realizes the selection of appropriate optimization target and constraint condition combination to form multiple optimization models under different scenarios, and the regulation mode is more flexible, which can flexibly switch the dispatching mode according to the dispatching mode of the power grid. BRIEF DESCRIPTION OF DRAWINGS

[0106] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0107] Figure 1 The scene schematic diagram of the wind-solar-fire-storage integrated coordinated control method provided by the embodiment of the present application is shown in the following figure.

[0108] Figure 2 The flowchart of the wind-solar-fire-storage integrated coordinated control method provided by an embodiment of the present application is shown in the following figure.

[0109] Figure 3 The structure schematic diagram of the wind-solar-fire-storage integrated coordinated control device provided by the embodiment of the present application is shown in the following figure.

[0110] Figure 4 The hardware structure schematic diagram of the service equipment provided by the embodiment of the present application is shown in the following figure.

[0111] Through the above-mentioned drawings, the specific embodiments of the present application have been shown, and more detailed descriptions will be given in the following. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application by any means, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0112] The exemplary embodiments will be described in detail herein with reference to the attached drawings. The following description is only exemplary and is not intended to limit the scope, applicability or configuration of the application. Rather, the following description is intended to describe some of the exemplary embodiments consistent with the application. Alternative embodiments will become apparent to those skilled in the art to which the present application pertains. Furthermore, descriptions of well-known functions and constructions can be omitted for clarity and conciseness.

[0113] The technical solutions of the application and how the technical solutions solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of the application will be described below with reference to the drawings.

[0114] Figure 1 A scene diagram of the wind-solar-fire storage integrated coordination control method provided by an embodiment of the application is shown in FIG. 1. As shown in FIG. 1, the scene provided by the embodiment includes an administrator terminal 101 and a service device 102. Figure 1

[0115] The administrator terminal 101 can be a mobile phone or a computer.

[0116] The service device 102 can be a server. Alternatively, it can be a single server or a cluster composed of multiple servers.

[0117] Specifically, the service device 102 sends a scheduling instruction to the administrator terminal 101; the administrator terminal 101 generates a running mode instruction in response to the input operation of the administrator according to the scheduling instruction; the administrator terminal 101 sends the running mode instruction to the service device 102; and the service device 102 performs wind-solar-fire storage integrated coordination control according to the running mode instruction.

[0118] Figure 2 A flowchart of the wind-solar-fire storage integrated coordination control method provided by an embodiment of the application is shown in FIG. 2. The execution subject of the embodiment can be the service device 102 shown in FIG. 1, or other computer devices, which are not particularly limited herein. As shown in FIG. 2, the method comprises the following steps. Figure 1 Figure 2

[0119] S201: Obtain a scheduling instruction.

[0120] The scheduling instruction includes a power grid scheduling instruction and a manual scheduling instruction.

[0121] ​​​S202: send the scheduling instruction to the administrator terminal, so that the administrator terminal generates a running mode instruction in response to an input operation of the administrator according to the scheduling instruction; wherein the running mode instruction comprises a single control instruction and a combined control instruction, wherein the single control instruction comprises a plurality of controlled power stations and a target power corresponding to each controlled power station, and the combined control instruction comprises a controlled power station group and a target power corresponding to the controlled power station group.

[0122] Specifically, S202 specifically comprises S2021-S2022:

[0123] S2021: perform approval verification on the scheduling instruction to generate a verification result.

[0124] Specifically, the scheduling instructions of two consecutive preset periods are obtained, and the contents of the two scheduling instructions are verified for consistency.

[0125] S2022: if the verification result is a verification pass, send the scheduling instruction to the administrator terminal.

[0126] S203: receive the running mode instruction sent by the administrator terminal.

[0127] S204: parse the running mode instruction to obtain the combined control instruction, and obtain the optimization target and the constraint condition corresponding to the controlled power station group according to the combined control instruction.

[0128] Specifically, the running mode instruction is parsed to obtain the combined control instruction, and the combined control instruction is parsed to obtain the low-altitude power station group, and the optimization target and the constraint condition corresponding to the controlled power station group are obtained from a preset mapping table.

[0129] S205: update the preset optimization model according to the optimization target and the constraint condition.

[0130] S206: obtain real-time running data of each controlled power station in the controlled power station group.

[0131] The real-time running data of each controlled power station comprises one or more of the following: real-time output power and upper and lower limits of power generation power of each controlled power station, maximum climbing rate of the thermal power plant, real-time power and health status of the energy storage power station.

[0132] S207: input the real-time running data and the target power corresponding to the controlled power station group into the updated optimization model to obtain a to-be-processed power instruction of each controlled power station in the controlled power station group.

[0133] S208: data preprocessing is performed on the to-be-processed power instruction of each controlled power station to obtain an actual power instruction of each controlled power station.

[0134] Specifically, the to-be-processed power instruction of each controlled power station is preprocessed according to preset standard power data to obtain an actual power instruction of each controlled power station.

[0135] S209: respectively sending the actual power instructions of the controlled power stations to each controlled power station in the controlled power station group.

[0136] S210: parsing the operation mode instruction to obtain a separate control instruction, and for each controlled power station in the separate control instruction, performing the following steps S2101-S2106:

[0137] S2101: obtaining an optimization target and a constraint condition corresponding to the controlled power station.

[0138] S2102: updating a preset optimization model according to the optimization target and the constraint condition.

[0139] S2103: obtaining real-time operation data of the controlled power station.

[0140] The real-time operation data of the controlled power station includes one or more of the following: real-time output power and upper and lower limits of generated power, maximum climbing rate, real-time power, and health status of the controlled power station.

[0141] S2104: inputting the real-time operation data of the controlled power station and the target power corresponding to the controlled power station into the updated optimization model to obtain a to-be-processed power instruction of the controlled power station.

[0142] S2105: preprocessing the to-be-processed power instruction of the controlled power station to obtain an actual power instruction of the controlled power station.

[0143] Specifically, the to-be-processed power instruction of the controlled power station is preprocessed according to preset standard power data to obtain an actual power instruction of the controlled power station.

[0144] S2106: sending the actual power instruction to the controlled power station.

[0145] From the above description, it can be seen that the application receives an operation mode instruction sent by an administrator terminal, obtains an optimization target and a constraint condition corresponding to a controlled power station or a controlled power station group according to the operation mode instruction, updates a preset optimization model according to the optimization target and the constraint condition, inputs real-time operation data and a target power of the controlled power station or the controlled power station group into the updated optimization model to obtain actual power instructions of each controlled power station in the controlled power station or the controlled power station group, and sends the actual power instructions to each controlled power station in the controlled power station or the controlled power station group. This realizes selection of appropriate optimization target and constraint condition combinations to form multiple optimization models under different scenarios, and makes the regulation mode more flexible and capable of flexibly switching the regulation mode according to the dispatching mode of the power grid.

[0146] In an embodiment of the present application, the scheduling instruction is a scheduling instruction for the integrated wind-solar-thermal power plant, and accordingly, in step S204, the corresponding optimization target and constraint condition of the controlled power plant group are obtained according to the combined control instruction, and in step S2101, another implementation manner is further provided, which is described in detail as follows:

[0147] S204: parse the operation mode instruction to obtain the combined control instruction, and obtain the corresponding optimization target and constraint condition of the controlled power plant group according to the combined control instruction.

[0148] If the combined control instruction includes the thermal power plant, the constraint condition includes the upper and lower limits of the thermal power plant output and the climbing rate constraint of the thermal power plant.

[0149] The formula of the upper and lower limits of the thermal power plant output is:

[0150]

[0151] In the formula, Pg i,t represents the power generation of the i th thermal power plant at time t; represents the upper limit of the power generation of the i th thermal power plant at time t; represents the lower limit of the power generation of the i th thermal power plant at time t.

[0152] The formula of the climbing rate constraint of the thermal power plant is:

[0153] -P i down ≤ Pg i,t -Pg i,t-1 ≤ P i up

[0154] In the formula, P i down represents the maximum downhill rate of the i th thermal power plant at adjacent two time points; P i up represents the maximum uphill rate of the i th thermal power plant at adjacent two time points.

[0155] If the combined control instruction includes the wind power plant, the constraint condition includes the upper and lower limits of the wind power.

[0156] The formula of the upper and lower limits of the wind power is:

[0157]

[0158] In the formula, Pw i,t is the power generation of the i th wind power plant at time t; is the upper limit of the power generation of the i th wind power plant at time t.

[0159] If the combined control instruction includes a photovoltaic power station, the constraint includes photovoltaic power upper and lower limit constraints.

[0160] The formula of the photovoltaic power upper and lower limit constraint is:

[0161]

[0162] In the formula, Ps i,t is the power generation of the i th photovoltaic power station at time t; is the power generation upper limit of the i th photovoltaic power station at time t.

[0163] If the combined control instruction includes an energy storage power station, the constraint includes an energy storage power constraint and an energy storage battery health state constraint.

[0164] The formula of the energy storage power constraint is:

[0165]

[0166] In the formula, Pessc i,t is the charging power of the i th energy storage power station at time t; is the maximum charging power of the i th energy storage power station at time t; is the minimum charging power of the i th energy storage power station at time t; Pessd i,t is the discharging power of the i th energy storage power station at time t; is the maximum discharging power of the i th energy storage power station at time t; is the minimum discharging power of the i th energy storage power station at time t.

[0167] The formula of the energy storage battery health state constraint is:

[0168]

[0169] In the formula, SOC i,t is the average battery state of charge of the i th energy storage power station at time t; is the maximum average battery state of charge of the i th energy storage power station at time t; is the minimum average battery state of charge of the i th energy storage power station at time t.

[0170] The optimization objective corresponding to the combined control instruction is the minimum sum of the scheduling instruction tracking deviation and the cost of each controlled power station in the combined control instruction.

[0171] The formula of the optimization objective is:

[0172] minf c = E + θ g Cg + θ wCw+θ s Cs+θ ess Cess

[0173] wherein θ g , θ w , θ s , θ ess are binary variables, representing whether the thermal power plant, wind farm, photovoltaic power station, and energy storage power station participate in combined control, and when 0, it means that the corresponding power station does not participate in combined control, and when 1, it means that the corresponding power station participates in combined control; E is the scheduling instruction tracking deviation; Cg is the thermal power plant operation and unit startup cost; Cw is the wind power curtailment cost; Cs is the photovoltaic curtailment cost; and Cess is the energy storage operation cost.

[0174] wherein the formula of the scheduling instruction tracking deviation is:

[0175]

[0176] wherein n is the total number of the thermal power plant, wind farm, photovoltaic power station, or energy storage power station controlled individually; Pcmd i,t represents the scheduling instruction value of the i-th power station at time t controlled individually; Pact i,t is a decision variable, representing the actual output of the i-th power station at time t; Pl i,t represents the line loss of the i-th power station at time t.

[0177] wherein the formula of the thermal power plant operation and unit startup cost is:

[0178]

[0179] wherein Tg represents the operation time length of the thermal power plant; ng represents the total number of the controlled thermal power plants; a i Pg i,t 2 +b i Pg i,t +c i represents the operation cost of the i-th thermal power plant, a i , b i , c i are the operation cost function coefficients of the i-th thermal power plant, Pg i,t is a decision variable, representing the output of the i-th thermal power plant at time t; q i,t is a binary variable, representing the unit startup state of the i-th thermal power plant at time t, and when 0, it means that the unit is shutdown, and when 1, it means that the unit is running; is the unit startup cost of the i-th thermal power plant.

[0180] wherein the formula of the wind power curtailment cost is:

[0181]

[0182] wherein Tw represents the operating time length of the wind farm; nw represents the total number of the controlled wind farms; and λw is the abandoned power cost factor of the wind farm; is the maximum power generation of the i th wind farm at time t; and Pw i,t is the decision variable, representing the power generation of the i th wind farm at time t.

[0183] wherein the formula of the abandoned power cost of the photovoltaic power station is:

[0184]

[0185] wherein Ts represents the operating time length of the photovoltaic power station; ns represents the total number of the controlled photovoltaic power stations; and λs is the abandoned power cost factor of the photovoltaic power station; is the maximum power generation of the i th photovoltaic power station at time t; and Ps i,t is the decision variable, representing the power generation of the i th photovoltaic power station at time t.

[0186] wherein the formula of the operating cost of the energy storage is:

[0187]

[0188] wherein Te represents the operating time length of the energy storage; ne represents the total number of the controlled energy storages; and λe is the operating cost factor of the energy storage; SOC i,t is the average battery state of charge of the i th energy storage at time t; is the maximum value of the average battery state of charge of the i th energy storage at time t; is the minimum value of the average battery state of charge of the i th energy storage at time t; Pess i,t is the decision variable, representing the power of the i th energy storage at time t, and when it is positive, it represents power generation, at this time Pess i,t = Pessd i,t , and when it is negative, it represents charging, at this time Pess i,t = -Pessc i,t , Pessc i,t is the charging power of the i th energy storage at time t, Pessd i,t is the discharging power of the i th energy storage at time t.

[0189] S2101: Obtain the optimization target and constraint condition corresponding to the controlled power station.

[0190] wherein if the controlled power station is a thermal power plant, the constraint condition includes the upper and lower limit constraint of the thermal power plant output and the thermal power plant climbing rate constraint.

[0191] wherein the formula of the upper and lower limits of the thermal power plant output is:

[0192]

[0193] wherein Pg i,t represents the power generation of the i th thermal power plant at time t; represents the upper limit of the power generation of the i th thermal power plant at time t; represents the lower limit of the power generation of the i th thermal power plant at time t.

[0194] wherein the formula of the ramp rate constraint of the thermal power plant is:

[0195] -P i down ≤ Pg i,t -Pg i,t-1 ≤ P i up

[0196] wherein P i down represents the maximum downhill rate of the i th thermal power plant at adjacent two time points; P i up represents the maximum uphill rate of the i th thermal power plant at adjacent two time points.

[0197] wherein if the controlled power station is a wind power plant, the constraint condition includes a wind power upper and lower limit constraint.

[0198] wherein the formula of the wind power upper and lower limit constraint is:

[0199]

[0200] wherein Pw i,t is the power generation of the i th wind power plant at time t; is the upper limit of the power generation of the i th wind power plant at time t.

[0201] wherein if the controlled power station is a photovoltaic power station, the constraint condition includes a photovoltaic power upper and lower limit constraint.

[0202] wherein the formula of the photovoltaic power upper and lower limit constraint is:

[0203]

[0204] wherein Ps i,t is the power generation of the i th photovoltaic power station at time t; is the upper limit of the power generation of the i th photovoltaic power station at time t.

[0205] wherein if the controlled power station is an energy storage power station, the constraint condition includes an energy storage power constraint and an energy storage battery health state constraint.

[0206] wherein the formula of the energy storage power constraint is:

[0207]

[0208] wherein Pessc i,t is the charging power of the i-th energy storage power station at time t; is the maximum charging power of the i-th energy storage power station at time t; is the minimum charging power of the i-th energy storage power station at time t; Pessd i,t is the discharging power of the i-th energy storage power station at time t; is the maximum discharging power of the i-th energy storage power station at time t; is the minimum discharging power of the i-th energy storage power station at time t.

[0209] wherein the formula of the energy storage battery health state constraint is:

[0210]

[0211] wherein SOC i,t is the average battery state of charge of the i-th energy storage power station at time t; is the maximum average battery state of charge of the i-th energy storage power station at time t; is the minimum average battery state of charge of the i-th energy storage power station at time t.

[0212] wherein if the thermal power plant is included in the individual control instruction, the optimization target corresponding to the thermal power plant is the sum of the dispatch instruction tracking deviation and the thermal power plant operation and start-stop cost being minimum;

[0213] wherein the formula of the optimization target is:

[0214] minf g = E + Cg

[0215] wherein E is the dispatch instruction tracking deviation; and Cg is the thermal power plant operation and start cost.

[0216] wherein if the wind power plant is included in the individual control instruction, the optimization target corresponding to the wind power plant is the sum of the dispatch instruction tracking deviation and the wind power curtailment cost being minimum;

[0217] wherein the formula of the optimization target is:

[0218] minf w = E + Cw

[0219] wherein E is the dispatch instruction tracking deviation; and Cw is the wind power curtailment cost.

[0220] If the photovoltaic power station is included in the individual control instruction, the optimization target corresponding to the photovoltaic power station is the sum of the scheduling instruction tracking deviation and the photovoltaic curtailment cost being minimum.

[0221] The formula of the optimization target is:

[0222] minf s =E+Cs

[0223] In the formula, E is the scheduling instruction tracking deviation, and Cs is the photovoltaic curtailment cost.

[0224] If the energy storage power station is included in the individual control instruction, the optimization target corresponding to the energy storage power station is the sum of the scheduling instruction tracking deviation and the energy storage operation cost being minimum.

[0225] The formula of the optimization target is:

[0226] minf e =E+Cess

[0227] In the formula, E is the scheduling instruction tracking deviation, and Cess is the energy storage operation cost.

[0228] Correspondingly, the specific process of step S206 is described as follows:

[0229] S206: Real-time operation data of each controlled power station in the controlled power station group is acquired.

[0230] Specifically, if the thermal power plant is included in the combined control instruction, the power generation upper limit, the power generation lower limit, the maximum downhill rate of adjacent two time points and the maximum uphill rate of adjacent two time points of each thermal power plant are acquired.

[0231] Specifically, if the wind farm is included in the combined control instruction, the wind power upper and lower limits of each wind farm are acquired.

[0232] Specifically, if the photovoltaic power station is included in the combined control instruction, the photovoltaic power upper and lower limits of each photovoltaic power station are acquired.

[0233] Specifically, if the energy storage power station is included in the combined control instruction, the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the real-time average battery state of charge, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station are acquired.

[0234] Specifically, the real-time line loss of each controlled power station in the controlled power station group is acquired.

[0235] Correspondingly, the specific process of step S2103 is described as follows:

[0236] S2103: Real-time operation data of the controlled power station is acquired.

[0237] Specifically, if the thermal power plant is included in the individual control instruction, the upper limit of the power generation, the lower limit of the power generation, the maximum downhill rate of adjacent two time points and the maximum uphill rate of adjacent two time points of each thermal power plant are obtained.

[0238] Specifically, if the wind farm is included in the individual control instruction, the upper and lower limits of the wind power of each wind farm are obtained.

[0239] Specifically, if the photovoltaic power station is included in the individual control instruction, the upper and lower limits of the photovoltaic power of each photovoltaic power station are obtained.

[0240] Specifically, if the energy storage power station is included in the individual control instruction, the maximum value of the charging power, the minimum value of the charging power, the maximum value of the discharging power, the minimum value of the discharging power, the real-time average battery state of charge, the maximum value of the average battery state of charge and the minimum value of the average battery state of charge of each energy storage power station are obtained.

[0241] Specifically, the real-time line loss of each controlled power station is obtained.

[0242] As can be seen from the above description, in the present application, the different characteristics of thermal power, wind power, photovoltaic power generation and energy storage power station are comprehensively considered, different optimization objectives and constraint conditions are set, the appropriate optimization objective and constraint condition combination is selected under different scenarios to form multiple optimization models, and finally the coordinated control of wind, light, fire and storage is realized, so as to improve the economic benefit and control performance of the power station.

[0243] In an embodiment of the present application, steps S208 and S2105 also provide another implementation manner, which is described in detail as follows:

[0244] S208: data preprocessing is performed on the to-be-processed power instructions of each controlled power station to obtain the actual power instructions of each controlled power station.

[0245] Specifically, S208 specifically includes S2081-S2082:

[0246] S2081: data verification is performed on the to-be-processed power instructions of each controlled power station to generate the depolarization power instructions of each controlled power station.

[0247] Specifically, the to-be-processed power instructions of each controlled power station in adjacent preset periods are compared, and the maximum value is removed to obtain the depolarization power instructions of each controlled power station.

[0248] S2082: amplitude limiting and speed limiting processing are performed on the depolarization power instructions of each controlled power station to obtain the actual power instructions of each controlled power station.

[0249] Specifically, the maximum value, the minimum value and the upper limit of the change of the power value per minute or per second of the power generation of each power station are counted, the upper and lower limits of the power of each controlled power station in each period are limited according to the counting results, the depolarization power instruction of each controlled power station is limited in amplitude and speed according to the upper and lower limits of the power of each controlled power station, and the actual power instruction of each controlled power station is obtained.

[0250] S2105: data preprocessing is performed on the to-be-processed power instruction of the controlled power station to obtain the actual power instruction of the controlled power station.

[0251] Specifically, S2105 specifically includes Sa-Sb:

[0252] Sa: data verification is performed on the to-be-processed power instruction of the controlled power station to obtain the depolarization power instruction of the controlled power station.

[0253] Sb: the depolarization power instruction of the controlled power station is limited in amplitude and speed to obtain the actual power instruction of the controlled power station.

[0254] As can be seen from the above description, the application can avoid the adverse effects caused by assigning abnormal values as actual calculation results to the power station. The adverse effects caused by the inconsistency between the issued instruction and the actual operation of the power station are avoided.

[0255] Figure 3 The structure schematic diagram of the wind-solar-thermal-storage integrated coordinated control device provided by the embodiment of the application is shown in the figure. Figure 3 As shown in the figure, the wind-solar-thermal-storage integrated coordinated control device 30 includes an acquisition module 301, a sending module 302, a receiving module 303, an analysis module 304, an updating module 305, an input module 306, a data processing module 307 and a separate control module 308.

[0256] The acquisition module 301 is used to acquire a dispatching instruction.

[0257] The sending module 302 is used to send the dispatching instruction to an administrator terminal, so that the administrator terminal generates a running mode instruction in response to the input operation of the administrator according to the dispatching instruction; wherein the running mode instruction includes a separate control instruction and a combined control instruction, wherein the separate control instruction includes a plurality of controlled power stations and one target power corresponding to each controlled power station, and the combined control instruction includes a controlled power station group and one target power corresponding to the controlled power station group.

[0258] The receiving module 303 is used to receive the running mode instruction sent by the administrator terminal.

[0259] The parsing module 304 is configured to parse the operation mode instruction to obtain a combined control instruction, and obtain an optimization target and a constraint condition corresponding to the controlled power station group according to the combined control instruction.

[0260] The updating module 305 is configured to update a preset optimization model according to the optimization target and the constraint condition.

[0261] The obtaining module 301 is further configured to obtain real-time operation data of each controlled power station in the controlled power station group.

[0262] The input module 306 is configured to input the real-time operation data and a target power corresponding to the controlled power station group into the updated optimization model, to obtain a to-be-processed power instruction of each controlled power station in the controlled power station group.

[0263] The data processing module 307 is configured to perform data preprocessing on the to-be-processed power instruction of each controlled power station, to obtain an actual power instruction of each controlled power station.

[0264] The sending module 302 is further configured to send the actual power instruction of each controlled power station to each controlled power station in the controlled power station group.

[0265] The separate control module 308 is configured to parse the operation mode instruction to obtain the separate control instruction, and perform the following steps on each controlled power station in the separate control instruction: obtaining an optimization target and a constraint condition corresponding to the controlled power station; updating a preset optimization model according to the optimization target and the constraint condition; obtaining real-time operation data of the controlled power station; inputting the real-time operation data of the controlled power station and a target power corresponding to the controlled power station into the updated optimization model, to obtain a to-be-processed power instruction of the controlled power station; performing data preprocessing on the to-be-processed power of the controlled power station, to obtain an actual power instruction of the controlled power station; and sending the actual power instruction to the controlled power station.

[0266] In a possible design, the sending module 302 is specifically configured to perform approval verification on the scheduling instruction, to generate a verification result; and if the verification result is a verification pass, the scheduling instruction is sent to an administrator terminal.

[0267] In a possible design, the data processing module 307 is specifically configured to perform data verification on the to-be-processed power instruction of each controlled power station, to obtain a depolarization power instruction of each controlled power station; and perform amplitude limiting and speed limiting processing on the depolarization power instruction of each controlled power station, to obtain an actual power instruction of each controlled power station.

[0268] In a possible design, the scheduling instruction is a scheduling instruction for a wind-solar-thermal-storage integrated power plant.

[0269] In a possible design, if the thermal power plant is included in the combined control instruction or the individual control instruction, the constraint condition includes a thermal power plant output upper and lower limit constraint and a thermal power plant ramp rate constraint.

[0270] The formula of the thermal power plant output upper and lower limit constraint is as follows:

[0271]

[0272] In the formula, Pg i,t represents the power generation of the i th thermal power plant at time t; represents the upper limit of the power generation of the i th thermal power plant at time t; represents the lower limit of the power generation of the i th thermal power plant at time t;

[0273] The formula of the thermal power plant ramp rate constraint is as follows:

[0274] -P i down ≤ Pg i,t -Pg i,t-1 ≤ P i up

[0275] In the formula, P i down represents the maximum downward ramp rate of the i th thermal power plant between adjacent time points; P i up represents the maximum upward ramp rate of the i th thermal power plant between adjacent time points;

[0276] Correspondingly, the obtaining of the real-time operation data of each controlled power station in the controlled power station group includes: obtaining the power generation upper limit, the power generation lower limit, the maximum downward ramp rate between adjacent time points, and the maximum upward ramp rate between adjacent time points of each thermal power plant; and correspondingly, the obtaining of the real-time operation data of the controlled power station includes: obtaining the power generation upper limit, the power generation lower limit, the maximum downward ramp rate between adjacent time points, and the maximum upward ramp rate between adjacent time points of each thermal power plant.

[0277] In a possible design, if the wind farm is included in the combined control instruction or the individual control instruction, the constraint condition includes a wind power upper and lower limit constraint.

[0278] The formula of the wind power upper and lower limit constraint is as follows:

[0279]

[0280] In the formula, Pw i,t represents the power generation of the i th wind farm at time t; an upper limit of power generation of the i th wind farm at time t;

[0281] Correspondingly, the acquiring the real-time operation data of each controlled power station in the group of controlled power stations comprises: acquiring the upper and lower limits of wind power of each wind farm; and correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquiring the upper and lower limits of wind power of each wind farm.

[0282] In a possible design, if the photovoltaic power station is included in the combined control instruction or the individual control instruction, the constraint condition comprises a photovoltaic power upper and lower limit constraint;

[0283] The formula of the photovoltaic power upper and lower limit constraint is as follows:

[0284]

[0285] In the formula, Ps i,t is the power generation of the i th photovoltaic power station at time t; is an upper limit of power generation of the i th photovoltaic power station at time t;

[0286] Correspondingly, the acquiring the real-time operation data of each controlled power station in the group of controlled power stations comprises: acquiring the upper and lower limits of wind power of each wind farm; and correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquiring the upper and lower limits of wind power of each wind farm.

[0287] In a possible design, if the energy storage power station is included in the combined control instruction or the individual control instruction, the constraint condition comprises an energy storage power constraint and an energy storage battery health state constraint;

[0288] The formula of the energy storage power constraint is as follows:

[0289]

[0290] In the formula, Pessc i,t is the charging power of the i th energy storage power station at time t; is a maximum value of the charging power of the i th energy storage power station at time t; is a minimum value of the charging power of the i th energy storage power station at time t; Pessd i,t is the discharging power of the i th energy storage power station at time t; is a maximum value of the discharging power of the i th energy storage power station at time t; is a minimum value of the discharging power of the i th energy storage power station at time t;

[0291] The formula of the energy storage battery health state constraint is as follows:

[0292]

[0293] SOCi(t) is the average battery state of charge of the i th energy storage power station at time t i,t SOCi(t) is the average battery state of charge of the i th energy storage power station at time t SOCi(t) is the average battery state of charge of the i th energy storage power station at time t SOCi(t) is the average battery state of charge of the i th energy storage power station at time t

[0294] Correspondingly, the obtaining of the real-time operation data of each controlled power station in the controlled power station group comprises: obtaining the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station; correspondingly, the obtaining of the real-time operation data of the controlled power station comprises: obtaining the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station.

[0295] In a possible design, the optimization target corresponding to the combined control instruction is to minimize the sum of the scheduling instruction tracking deviation and the cost of each controlled power station in the combined control instruction;

[0296] The formula of the optimization target is as follows:

[0297] minf c = E + θ g Cg + θ w Cw + θ s Cs + θ ess Cess

[0298] In the formula, θ g , θ w , θ s , θ ess is a binary variable, indicating whether the thermal power plant, the wind farm, the photovoltaic power station or the energy storage power station participates in the combined control; when it is 0, it indicates that the corresponding power station does not participate in the combined control; when it is 1, it indicates that the corresponding power station participates in the combined control; E is the scheduling instruction tracking deviation; Cg is the thermal power plant operation and machine starting cost; Cw is the wind power curtailment cost; Cs is the photovoltaic curtailment cost; Cess is the energy storage operation cost;

[0299] The formula of the scheduling instruction tracking deviation is as follows:

[0300]

[0301] In the formula, n is the total number of the thermal power plant, the wind farm, the photovoltaic power station or the energy storage power station controlled individually; Pcmd i,t represents the scheduling instruction value of the i th power station controlled individually at time t; Pact i,tis the actual output of the i-th power plant at time t; P i,t is the line loss of the i-th power plant at time t;

[0302] wherein the formula of the thermal power plant operation and starting cost is:

[0303]

[0304] wherein Tg represents the operation duration of the thermal power plant; ng represents the total number of the controlled thermal power plants; a i Pg i,t 2 +b i Pg i,t +c i represents the operation cost of the i-th thermal power plant; a i , b i , c i are the operation cost function coefficients of the i-th thermal power plant; Pg i,t is the decision variable, representing the output of the i-th thermal power plant at time t; q i,t is a binary variable, representing the starting state of the i-th unit at time t, and is 0 when the unit is stopped and is 1 when the unit is running; is the starting cost of the i-th thermal power plant;

[0305] wherein the formula of the wind power curtailment cost is:

[0306]

[0307] wherein Tw represents the operation duration of the wind farm; nw represents the total number of the controlled wind farms; λw is the wind farm curtailment cost factor; is the maximum power generation of the i-th wind farm at time t; Pw i,t is the decision variable, representing the power generation of the i-th wind farm at time t;

[0308] wherein the formula of the photovoltaic curtailment cost is:

[0309]

[0310] wherein Ts represents the operation duration of the photovoltaic power station; ns represents the total number of the controlled photovoltaic power stations; λs is the photovoltaic power station curtailment cost factor; is the maximum power generation of the i-th photovoltaic power station at time t; Ps i,t is the decision variable, representing the power generation of the i-th photovoltaic power station at time t;

[0311] wherein the formula of the energy storage operation cost is:

[0312]

[0313] wherein, Te represents the operating time length of the energy storage power station; ne represents the total number of the controlled energy storage power stations; λe is the operating cost factor of the energy storage power station; SOC i,t is the average battery state of charge of the i th energy storage power station at time t; is the maximum average battery state of charge of the i th energy storage power station at time t; is the minimum average battery state of charge of the i th energy storage power station at time t; Pess i,t is a decision variable, representing the power of the i th energy storage power station at time t, when being positive, representing power generation, at this time Pess i,t = Pessd i,t , when being negative, representing charging, at this time Pess i,t = -Pessc i,t , Pessc i,t is the charging power of the i th energy storage power station at time t, Pessd i,t is the discharging power of the i th energy storage power station at time t;

[0314] Correspondingly, the acquiring the real-time operating data of each controlled power station in the controlled power station group comprises: acquiring the real-time line loss of each controlled power station in the controlled power station group; if it is determined that the combined control instruction comprises an energy storage power station, acquiring the real-time average battery state of charge, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station in the controlled power station group.

[0315] In a possible design, if the individual control instruction comprises a thermal power plant, the optimization target corresponding to the thermal power plant is the minimum sum of the dispatch instruction tracking deviation and the operating and start-stop cost of the thermal power plant;

[0316] The formula of the optimization target is as follows:

[0317] minf g = E + Cg

[0318] wherein, E is the dispatch instruction tracking deviation; and Cg is the operating and start-stop cost of the thermal power plant.

[0319] In a possible design, if the individual control instruction comprises a wind power plant, the optimization target corresponding to the wind power plant is the minimum sum of the dispatch instruction tracking deviation and the wind power curtailment cost;

[0320] The formula of the optimization target is as follows:

[0321] minf w = E + Cw

[0322] wherein, E is the dispatch instruction tracking deviation; and Cw is the wind power curtailment cost.

[0323] In a possible design, if the single control instruction includes a photovoltaic power station, an optimization target corresponding to the photovoltaic power station is a sum of scheduling instruction tracking deviation and photovoltaic curtailment cost being minimum.

[0324] The formula of the optimization target is as follows:

[0325] minf s =E+Cs

[0326] In the formula, E is the scheduling instruction tracking deviation, and Cs is the photovoltaic curtailment cost.

[0327] In a possible design, if the single control instruction includes an energy storage power station, an optimization target corresponding to the energy storage power station is a sum of scheduling instruction tracking deviation and energy storage operation cost being minimum.

[0328] The formula of the optimization target is as follows:

[0329] minf e =E+Cess

[0330] In the formula, E is the scheduling instruction tracking deviation, and Cess is the energy storage operation cost.

[0331] In a possible design, the scheduling instruction includes a grid scheduling instruction and an artificial scheduling instruction.

[0332] The apparatus provided in this embodiment can be used to execute the technical solutions of the method embodiments, and has similar implementation principles and technical effects, which will not be described here again in this embodiment.

[0333] Figure 4 A hardware structure diagram of a service device provided in this embodiment is shown in FIG. 1. As shown in FIG. 1, the service device in this embodiment includes at least one processor 401 and a memory 402. The memory stores computer execution instructions. The at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the wind-solar-fire-storage integrated coordinated control method as described above. Figure 4

[0334] Optionally, the memory 402 can be independent or integrated with the processor 401.

[0335] When the memory 402 is independently arranged, the service device further includes a bus 403 for connecting the memory 402 and the processor 401.

[0336] This embodiment of the present application further provides a computer readable storage medium, which stores computer execution instructions. When the processor executes the computer execution instructions, the wind-solar-fire-storage integrated coordinated control method as described above is implemented.​

[0337] The embodiment of the present application further provides a computer program product comprising a computer program, which, when executed by a processor, implements the wind-solar-fire storage integrated coordinated control method as described above.

[0338] It should be noted that, for the foregoing method embodiments, in order to simply describe, the foregoing method embodiments are all described as a combination of a series of actions, but those skilled in the art should know that the present application is not limited to the order of the actions described, because according to the present application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0339] It should be further noted that, although each step in the flowchart is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified in this document, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other order. Moreover, at least part of the steps in the flowchart can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with other steps or sub-steps or stages of other steps.

[0340] It should be understood that the above-mentioned device embodiments are only schematic, and the device of the present application can also be realized by other manners. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and another division manner can be used in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0341] In addition, each functional unit / module in each embodiment of the present application can be integrated in one unit / module, or each unit / module can exist physically, or two or more units / modules can be integrated together. The integrated unit / module can be realized in the form of hardware or in the form of software program module.

[0342] If the integrated units / modules are implemented in the form of hardware, the hardware can be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, an ASIC, etc. Unless otherwise specified, the storage unit can be any appropriate magnetic storage medium or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0343] If the integrated units / modules are implemented in the form of software program modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the essential part or all or part of the technical solutions that make contributions to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0344] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0345] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0346] It is to be understood that the application is not limited to the precise construction herein disclosed and shown in the drawings, and that various changes in shape, size and arrangements of parts can be made without departing from the scope of the application. The scope of the application is limited only by the claims that follow.

Claims

1. A wind-solar-fire integrated coordinated control method, characterized in that, The application is applied to a service device, comprising: obtaining a scheduling instruction; sending the scheduling instruction to an administrator terminal, so that the administrator terminal generates a running mode instruction in response to an input operation of the administrator according to the scheduling instruction; wherein the running mode instruction comprises a single control instruction and a combined control instruction, wherein the single control instruction comprises a plurality of controlled power stations and a target power corresponding to each controlled power station, and the combined control instruction comprises a controlled power station group and a target power corresponding to the controlled power station group; receiving the running mode instruction sent by the administrator terminal; parsing the running mode instruction to obtain the combined control instruction, and obtaining an optimization target and a constraint condition corresponding to the controlled power station group according to the combined control instruction; updating a preset optimization model according to the optimization target and the constraint condition; obtaining real-time running data of each controlled power station in the controlled power station group; inputting the real-time running data and the target power corresponding to the controlled power station group into the updated optimization model to obtain a to-be-processed power instruction of each controlled power station in the controlled power station group; performing data preprocessing on the to-be-processed power instruction of each controlled power station to obtain an actual power instruction of each controlled power station; sending the actual power instruction of each controlled power station to each controlled power station in the controlled power station group respectively; parsing the running mode instruction to obtain the single control instruction, and performing the following steps for each controlled power station in the single control instruction: obtaining an optimization target and a constraint condition corresponding to the controlled power station; updating a preset optimization model according to the optimization target and the constraint condition; obtaining real-time running data of the controlled power station; inputting the real-time running data of the controlled power station and the target power corresponding to the controlled power station into the updated optimization model to obtain a to-be-processed power instruction of the controlled power station; performing data preprocessing on the to-be-processed power instruction of the controlled power station to obtain an actual power instruction of the controlled power station; sending the actual power instruction to the controlled power station.

2. The method of claim 1, wherein, The sending of the scheduling instruction to the administrator terminal comprises: performing approval verification on the scheduling instruction to generate a verification result; if the verification result is a verification pass, sending the scheduling instruction to the administrator terminal.

3. The method of claim 1, wherein, The data preprocessing on the to-be-processed power instruction of each controlled power station to obtain the actual power instruction of each controlled power station comprises: performing data verification on the to-be-processed power instruction of each controlled power station to obtain a depolarization power instruction of each controlled power station; performing amplitude limiting and speed limiting processing on the depolarization power instruction of each controlled power station to obtain the actual power instruction of each controlled power station.

4. The method of claim 1, wherein, The scheduling instruction is a scheduling instruction for a wind-solar-thermal-storage integrated power plant.

5. The method of claim 4, wherein, If the combined control instruction or the single control instruction comprises a thermal power plant, the constraint condition comprises a thermal power plant output upper and lower limit constraint and a thermal power plant climbing rate constraint: wherein the formula of the thermal power plant output upper and lower limit constraint is: wherein Pg i,t represents the power generated by the i-th thermal power plant at time t; represents the upper limit of the power generated by the i-th thermal power plant at time t; represents the lower limit of the power generated by the i-th thermal power plant at time t; wherein the formula of the thermal power plant climbing rate constraint is: - P i down ≤ Pg i,t - Pg i,t-1 ≤ P i up In the formula, P i down P represents the maximum downhill rate of the i th thermal power plant at adjacent two time points; P i up P represents the maximum uphill rate of the i th thermal power plant at adjacent two time points; P Correspondingly, the obtaining of the real-time running data of each controlled power station in the controlled power station group comprises: acquire the upper limit of power generation, the lower limit of power generation, the maximum downhill rate of adjacent two time points and the maximum uphill rate of adjacent two time points of each thermal power plant; Correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquire the upper limit of power generation, the lower limit of power generation, the maximum downhill rate of adjacent two time points and the maximum uphill rate of adjacent two time points of each thermal power plant.

6. The method of claim 4, wherein, If the combined control instruction or the separate control instruction includes a wind power plant, the constraint condition comprises a wind power upper and lower limit constraint; The formula of the wind power upper and lower limit constraint is: In the formula, Pw i,t is the power generation of the i th wind farm at time t; is the upper limit of the power generation of the i th wind farm at time t; Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquire the wind power upper and lower limit of each wind power plant; Correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquire the wind power upper and lower limit of each wind power plant.

7. The method of claim 4, wherein, If the combined control instruction or the separate control instruction includes a photovoltaic power station, the constraint condition comprises a photovoltaic power upper and lower limit constraint; The formula of the photovoltaic power upper and lower limit constraint is: In the formula, Ps i,t is the power generation of the i th photovoltaic power station at time t; is the upper limit of the power generation of the i th photovoltaic power station at time t; Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquire the photovoltaic power upper and lower limit of each photovoltaic power station; Correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquire the photovoltaic power upper and lower limit of each photovoltaic power station.

8. The method of claim 4, wherein, If the combined control instruction or the separate control instruction includes an energy storage power station, the constraint condition comprises an energy storage power constraint and an energy storage battery health state constraint; The formula of the energy storage power constraint is: Pessc i,t is the charging power of the i-th energy storage power station at time t; is the maximum charging power of the i-th energy storage power station at time t; is the minimum charging power of the i-th energy storage power station at time t; i,t Pessd is the maximum discharging power of the i-th energy storage power station at time t; is the minimum discharging power of the i-th energy storage power station at time t; The formula of the energy storage battery health state constraint is: In the formula, SOC i,t is the average battery state of charge of the i-th energy storage power station at time t; is the maximum average battery state of charge of the i-th energy storage power station at time t; is the minimum average battery state of charge of the i-th energy storage power station at time t; Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquire the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station; Correspondingly, the acquiring the real-time operation data of the controlled power station comprises: acquire the maximum charging power, the minimum charging power, the maximum discharging power, the minimum discharging power, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station.

9. The method of claim 4, wherein, The optimization target corresponding to the combined control instruction is the minimum sum of the scheduling instruction tracking deviation and the cost of each controlled power station in the combined control instruction; The formula of the optimization target is: minf c = E + θ g Cg + θ w Cw + θ s Cs + θ ess Cess wherein θ g , θ w , θ s , θ ess are binary variables, representing whether the thermal power plant, the wind farm, the photovoltaic power station, and the energy storage power station participate in the combined control, and when 0, it means that the corresponding power station does not participate in the combined control, and when 1, it means that the corresponding power station participates in the combined control; E is the dispatch instruction tracking deviation; Cg is the thermal power plant operation and starting cost; Cw is the wind power curtailment cost; Cs is the photovoltaic curtailment cost; and Cess is the energy storage operation cost. The formula of the scheduling instruction tracking deviation is: In the formula, n is the total number of individually controlled thermal power plants, wind farms, photovoltaic power stations, or energy storage power stations; Pcmd i,t Pcmd represents the dispatch instruction value of the i th power station at time t; Pact i,t is a decision variable, representing the actual output of the i th power station at time t; Pl i,t represents the line loss of the i th power station at time t; The formula of the thermal power plant operation and starting cost is: wherein Tg represents the length of time when the thermal power plant is running; ng represents the total number of the thermal power plants to be controlled; a i Pg i,t 2 +b i Pg i,t +c i represents the running cost of the i-th thermal power plant, a i , b i , c i are the running cost function coefficients of the i-th thermal power plant, Pg i,t is a decision variable, representing the output of the i-th thermal power plant at time t; q i,t is a binary variable, representing the on-off state of the i-th unit at time t, and is 0 when the unit is off and is 1 when the unit is running; is the on-off cost of the i-th thermal power plant; The formula of the wind power curtailment cost is: In the formula, Tw represents the wind farm operation time length; nw represents the total number of the controlled wind farms; and λw is the wind farm curtailment cost factor; is the maximum power generation of the ith wind farm at time t; Pw i,t is the decision variable, representing the power generation of the ith wind farm at time t; The formula of the photovoltaic power curtailment cost is: In the formula, Ts represents the operation time length of the photovoltaic power station; ns represents the total number of the controlled photovoltaic power stations; λs is the abandoned electricity cost factor of the photovoltaic power station; is the maximum power generation of the i-th photovoltaic power station at t time; Ps i,t is the decision variable, representing the power generation of the i-th photovoltaic power station at t time. The formula of the energy storage operation cost is: where Te represents the operating time length of the energy storage power station; ne represents the total number of the controlled energy storage power stations; λe is the operating cost factor of the energy storage power station; SOC i,t is the average battery state of charge of the i-th energy storage power station at time t; is the maximum average battery state of charge of the i-th energy storage power station at time t; is the minimum average battery state of charge of the i-th energy storage power station at time t; Pess i,t is a decision variable, representing the power of the i-th energy storage power station at time t, and when it is positive, it represents power generation, at this time Pess i,t = Pessd i,t , and when it is negative, it represents charging, at this time Pess i,t = -Pessc i,t , Pessc i,t is the charging power of the i-th energy storage power station at time t, Pessd i,t is the discharging power of the i-th energy storage power station at time t; Correspondingly, the acquiring the real-time operation data of each controlled power station in the controlled power station group comprises: acquire the real-time line loss of each controlled power station in the controlled power station group; If it is determined that the combined control instruction includes an energy storage power station, acquire the real-time average battery state of charge, the maximum average battery state of charge and the minimum average battery state of charge of each energy storage power station in the controlled power station group.

10. The method of claim 4, wherein, If the individual control instruction includes a thermal power plant, the optimization objective corresponding to the thermal power plant is to minimize the sum of the dispatch instruction tracking deviation and the operation and start-stop cost of the thermal power plant; The formula of the optimization objective is: min f g = E + Cg In the formula, E is the dispatch instruction tracking deviation; and Cg is the operation and start-stop cost of the thermal power plant.

11. The method of claim 4, wherein, If the individual control instruction includes a wind power plant, the optimization objective corresponding to the wind power plant is to minimize the sum of the dispatch instruction tracking deviation and the wind power curtailment cost; The formula of the optimization objective is: min f w = E + Cw In the formula, E is the dispatch instruction tracking deviation; and Cw is the wind power curtailment cost.

12. The method of claim 4, wherein, If the individual control instruction includes a photovoltaic power station, the optimization objective corresponding to the photovoltaic power station is to minimize the sum of the dispatch instruction tracking deviation and the photovoltaic curtailment cost; The formula of the optimization objective is: min f s = E + Cs In the formula, E is the dispatch instruction tracking deviation; and Cs is the photovoltaic curtailment cost.

13. The method of claim 4, wherein, If the individual control instruction includes an energy storage power station, the optimization objective corresponding to the energy storage power station is to minimize the sum of the dispatch instruction tracking deviation and the energy storage operation cost; The formula of the optimization objective is: min f e = E + Cess In the formula, E is the dispatch instruction tracking deviation; and Cess is the energy storage operation cost.

14. The method according to any one of claims 1 to 13, characterized in that, The dispatch instruction includes a power grid dispatch instruction and a manual dispatch instruction.

15. A wind-solar-fire integrated coordinated control device, characterized in that, The application is applied to a service device, which comprises: an acquisition module configured to acquire a dispatch instruction; a sending module configured to send the dispatch instruction to an administrator terminal, so that the administrator terminal generates an operation mode instruction in response to an input operation of an administrator according to the dispatch instruction; wherein the operation mode instruction comprises an individual control instruction and a combined control instruction, wherein the individual control instruction comprises a plurality of controlled power stations and one target power corresponding to each controlled power station, and wherein the combined control instruction comprises a controlled power station group and one target power corresponding to the controlled power station group; a receiving module configured to receive the operation mode instruction sent by the administrator terminal; an analysis module configured to analyze the operation mode instruction to obtain the combined control instruction, and to acquire an optimization objective and a constraint condition corresponding to the controlled power station group according to the combined control instruction; an updating module configured to update a preset optimization model according to the optimization objective and the constraint condition; the acquisition module is further configured to acquire real-time operation data of each controlled power station in the controlled power station group; an input module configured to input the real-time operation data and the target power corresponding to the controlled power station group into the updated optimization model, so as to obtain a to-be-processed power instruction of each controlled power station in the controlled power station group; a data processing module configured to perform data preprocessing on the to-be-processed power instruction of each controlled power station, so as to obtain an actual power instruction of each controlled power station; the sending module is further configured to send the actual power instruction of each controlled power station to each controlled power station in the controlled power station group, respectively. A separate control module is configured to parse the operation mode instruction to obtain the separate control instruction, and for each controlled power station in the separate control instruction, the following steps are performed: obtaining an optimization target and a constraint condition corresponding to the controlled power station; updating a preset optimization model according to the optimization target and the constraint condition; obtaining real-time operation data of the controlled power station; inputting the real-time operation data of the controlled power station and a target power corresponding to the controlled power station into the updated optimization model to obtain a to-be-processed power instruction of the controlled power station; performing data preprocessing on the to-be-processed power instruction of the controlled power station to obtain an actual power instruction of the controlled power station; and sending the actual power instruction to the controlled power station.

16. A service device, characterized by Comprise: a processor, and a memory connected to the processor in communication; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the wind-solar-thermal storage integrated coordinated control method according to any one of claims 1 to 14.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by the processor to implement the wind-solar-thermal storage integrated coordinated control method according to any one of claims 1 to 14.

18. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the wind-solar-thermal storage integrated coordinated control method according to any one of claims 1 to 14.

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