Wind, light and fire storage system regulation and control method and device, terminal equipment and storage medium

Abstract

The invention discloses a wind, light and fire storage system regulation and control method and device, terminal equipment and a storage medium. The method comprises the steps of obtaining basic data of a wind, light and fire storage system; according to the basic data, by taking the minimum comprehensive cost as a target, constructing a target function of a wind-solar-thermal storage system regulation and control model, and a power flow constraint, a standby constraint, a secondary frequency modulation constraint, a thermal power operation constraint, an energy storage operation constraint, a wind power operation constraint and a photovoltaic operation constraint of the target function; and under each constraint, carrying out iterative solution on the target function, generating a regulation and control strategy of the wind, light and fire storage system when the comprehensive cost is minimum, and carrying out regulation and control on the wind, light and fire storage system according to the regulation and control strategy. Wherein before the objective function is iteratively solved, the objective function is decomposed into a spatial dimension problem and a time dimension problem according to each constraint; and during iterative solution, carrying out parallel solution on the spatial dimension problem and the time dimension problem, and generating the regulation and control strategy when a preset convergence condition is met.

Description

Technical Field

[0001] The present invention relates to the field of power system control technology, and in particular to a wind, solar, thermal and energy storage system control method, device, terminal equipment and storage medium. Background Art

[0002] As the global climate warms, the energy crisis becomes increasingly prominent. It has become a global consensus to vigorously promote the development of renewable energy such as wind power and photovoltaics. Under the background of today's energy transformation, wind, solar, thermal and storage systems, as a form of power system that can comprehensively utilize multiple energy forms, have become an important means to improve energy efficiency and are of great significance to the sustainable development of power systems. The existing technology mainly constructs the objective function and the constraints corresponding to the objective function for peak and frequency regulation of wind, solar, thermal and storage systems, and then solves the objective function under the constraints. From a mathematical point of view, the problem of solving the objective function is essentially a mixed integer nonlinear programming problem. The existing technology mainly uses classical mathematical optimization methods and heuristic algorithms, such as genetic algorithms, particle swarm algorithms and other heuristic algorithms, to iteratively seek the optimal solution by simulating certain natural or human social behaviors. This single iterative solution method has low computational efficiency, which leads to the problem of untimely regulation when regulating the wind, solar, thermal and storage systems. Summary of the invention

[0003] The embodiments of the present invention provide a wind, solar, thermal and storage system control method, device, terminal equipment and storage medium, which can timely control the wind, solar, thermal and storage system and improve the real-time performance of the control.

[0004] An embodiment of the present invention provides a method for controlling a wind-solar-thermal-storage system, comprising:

[0005] Obtaining basic data of the wind, solar, thermal and energy storage system; wherein the basic data includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data;

[0006] According to the basic data, the objective function of the wind-solar-thermal-storage system control model is constructed with the goal of minimizing the comprehensive cost of operation cost, frequency regulation reserve cost and secondary frequency regulation response cost; and based on the basic data, the power flow constraint, reserve constraint, secondary frequency regulation constraint, thermal power operation constraint, energy storage operation constraint, wind power operation constraint and photovoltaic operation constraint of the objective function are constructed; among which, the power flow constraint, reserve constraint, secondary frequency regulation constraint, wind power operation constraint and photovoltaic operation constraint belong to the spatial dimension, and the thermal power operation constraint and energy storage operation constraint belong to the temporal dimension;

[0007] Under various constraints, the objective function is iteratively solved to generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and the wind, solar, thermal and storage system is controlled according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit;

[0008] Before iteratively solving the objective function, the objective function is decomposed into a spatial dimension problem and a temporal dimension problem according to various constraints; during the iterative solution, the spatial dimension problem and the temporal dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are iteratively solved, and several temporal dimension sub-problems in the temporal dimension problem are iteratively solved, and when the preset convergence conditions are met, the control strategy is generated.

[0009] Furthermore, before decomposing the objective function into a spatial dimension problem and a temporal dimension problem according to each constraint, it also includes:

[0010] Determine the first coupling variable in the time dimension according to the thermal power operation constraint; wherein the first coupling variable includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the secondary frequency regulation of the thermal power unit, and the secondary frequency regulation power of the thermal power unit;

[0011] Determine a second coupling variable in the time dimension according to the energy storage operation constraint; wherein the second coupling variable includes: charging power of the energy storage device, discharging power of the energy storage device, spare capacity of the energy storage device, and secondary frequency modulation power of the energy storage device;

[0012] Generate a first replica variable corresponding to the space dimension according to the first coupling variable, generate a second replica variable corresponding to the space dimension according to the second coupling variable, and construct a variable consistency constraint according to the first coupling variable, the second coupling variable, the first replica variable, and the second replica variable;

[0013] Obtaining a first Lagrange multiplier of a first coupling variable, a second Lagrange multiplier of a second coupling variable, and a penalty coefficient;

[0014] An augmented Lagrangian function of the objective function is constructed according to the variable consistency constraint, the first Lagrangian multiplier, the second Lagrangian multiplier, the penalty coefficient and the objective function.

[0015] Furthermore, decomposing the objective function into a spatial dimension problem and a temporal dimension problem according to each constraint includes:

[0016] Determine the spatial dimension problem according to the augmented Lagrangian function of the objective function, power flow constraints, wind power operation constraints, photovoltaic operation constraints, reserve capacity constraints and secondary frequency regulation constraints;

[0017] The time dimension problem is determined according to the augmented Lagrangian function of the objective function, thermal power operation constraints, energy storage operation constraints, reserve capacity constraints and secondary frequency regulation constraints.

[0018] Furthermore, during the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are solved iteratively, and several time dimension sub-problems in the time dimension problem are solved iteratively, including:

[0019] For each iterative solution process, the spatial dimension problem at the current iteration moment and the time dimension problem at the current iteration moment are solved in parallel;

[0020] Among them, for several spatial dimension sub-problems in the spatial dimension problem, iterative solutions are performed under the constraints of power flow constraints, wind power operation constraints, photovoltaic operation constraints, reserve capacity constraints and secondary frequency regulation constraints to obtain the active output of the photovoltaic unit at the current iteration moment, the active output of the wind turbine unit at the current iteration moment, the first replicated variable at the current iteration moment and the second replicated variable at the current iteration moment;

[0021] For several time dimension sub-problems in the time dimension problem, they are solved under the constraints of thermal power operation constraints, energy storage operation constraints, reserve capacity constraints and secondary frequency regulation constraints to obtain the first coupling variable at the current iteration moment and the second coupling variable at the current iteration moment.

[0022] Furthermore, the preset convergence condition is specifically:

[0023] The dual variable residual at the current iteration moment is not greater than the preset convergence accuracy; wherein, the dual variable residual at the current iteration moment is determined according to the first coupling variable at the current iteration moment, the second coupling variable at the current iteration moment, the first copy variable at the current iteration moment, and the second copy variable at the current iteration moment.

[0024] Furthermore, after solving the spatial dimension problem at the current iteration time and the time dimension problem at the current iteration time in parallel, it also includes:

[0025] Generate a first Lagrange multiplier at the next iteration time according to the first Lagrange multiplier at the current iteration time, the penalty coefficient, the first coupling variable at the next iteration time, and the first replica variable at the next iteration time;

[0026] The second Lagrange multiplier at the next iteration time is generated according to the second Lagrange multiplier at the current iteration time, the penalty coefficient, the second coupling variable at the next iteration time, and the second replica variable at the next iteration time.

[0027] Furthermore, the objective function of the wind-solar-thermal-storage system control model is specifically:

[0028]

[0029]

[0030] Among them, C represents the objective function; G is the thermal power set; W is the wind power set; P is the photovoltaic set; B is the energy storage set; M is the frequency regulation scenario set; is the operating cost of thermal power unit i in period t; is the active power output of thermal power unit i in period t; is the on / off status of thermal power unit i in period t; is the operating cost of energy storage device i in period t; is the charging power of energy storage device i in period t; is the discharge power of energy storage device i in period t; is the operating cost of wind turbine i in period t; is the active power output of wind turbine i in period t; is the operating cost of PV unit i in period t; is the active power output of photovoltaic unit i in period t; is the frequency regulation reserve capacity cost coefficient of thermal power unit i; is the upper reserve capacity of thermal power unit i for secondary frequency regulation during period t; is the lower reserve capacity of thermal power unit i for secondary frequency regulation during period t; is the frequency regulation reserve capacity cost coefficient of energy storage device i; is the upper reserve capacity of energy storage device i for secondary frequency regulation in period t; is the lower reserve capacity of energy storage device i for secondary frequency regulation in period t; is the frequency response cost coefficient of thermal power unit i; is the secondary frequency modulation power of thermal power unit i in time period τ in scenario m; is the frequency response cost coefficient of energy storage device i; is the secondary frequency modulation power of energy storage device i in time period τ in scenario m; a i , b i and c i is the operating cost coefficient of thermal power unit i; is the startup cost of thermal power unit i; is the shutdown cost of thermal power unit i; is the charging cost coefficient of energy storage device i; is the discharge cost coefficient of energy storage device i; is the operating cost coefficient of wind turbine i; is the penalty coefficient of wind power abandonment of wind turbine i; is the predicted output value of wind turbine i in time period t; is the operating cost coefficient of the photovoltaic unit; is the penalty coefficient for abandoned photovoltaic power of PV unit i; is the predicted output value of PV unit i in time period t.

[0031] Based on the above method embodiment, the present invention provides a corresponding device embodiment;

[0032] An embodiment of the present invention provides a wind-solar-thermal-storage system control device, including: a data acquisition module, a model building module and a model solving and control module;

[0033] The data acquisition module is used to acquire basic data of the wind, solar, thermal and energy storage system; wherein the basic data includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data;

[0034] The model building module is used to construct the objective function of the wind-solar-thermal-storage system control model based on the basic data, with the goal of minimizing the comprehensive cost of operation cost, frequency regulation standby cost and secondary frequency regulation response cost; and construct the power flow constraint, standby constraint, secondary frequency regulation constraint, thermal power operation constraint, energy storage operation constraint, wind power operation constraint and photovoltaic operation constraint of the objective function based on the basic data; wherein the power flow constraint, standby constraint, secondary frequency regulation constraint, wind power operation constraint and photovoltaic operation constraint belong to the space dimension, and the thermal power operation constraint and energy storage operation constraint belong to the time dimension;

[0035] The model solving and control module is used to iteratively solve the objective function under various constraints, generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and control the wind, solar, thermal and storage system according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit; wherein, before iteratively solving the objective function, the objective function is decomposed into a spatial dimension problem and a time dimension problem according to various constraints; during the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are iteratively solved, and several time dimension sub-problems in the time dimension problem are iteratively solved, and when the preset convergence conditions are met, the control strategy is generated.

[0036] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, a wind, solar, thermal and energy storage system control method described in the above-mentioned embodiment of the invention is implemented.

[0037] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a wind-solar-thermal-storage system control method described in the above-mentioned embodiment of the invention.

[0038] The following beneficial effects are achieved by implementing the present invention:

[0039] The present invention provides a wind-solar-thermal-storage system control method, device, terminal equipment and storage medium. The method obtains basic data of the wind-solar-thermal-storage system, and based on the basic data obtained, takes the comprehensive cost minimization of operation cost, frequency regulation standby cost and secondary frequency regulation response cost as the goal, constructs the objective function of the wind-solar-thermal-storage system control model and the flow constraints, standby constraints, secondary frequency regulation constraints, thermal power operation constraints, energy storage operation constraints, wind power operation constraints and photovoltaic operation constraints of the objective function; solves the objective function under the constraints of the above constraints, and decomposes the objective function solution problem into spatial dimensions according to the above constraints before solving. degree problem and time dimension problem; for several spatial dimension sub-problems in the spatial dimension problem and several time dimension sub-problems in the time dimension problem, iterative solution is still adopted. When the preset convergence condition is reached, that is, when the comprehensive cost is minimized, a control strategy including the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind turbine unit is generated, and then the wind-solar-thermal-storage system is regulated by the control strategy.

[0040] By converting the problem of solving the objective function into the solution of the spatial dimension problem and the solution of the time dimension problem, since the spatial dimension and the time dimension do not affect each other, the spatial dimension problem and the time dimension problem can be solved in parallel. By decomposing the problem of solving the objective function into the parallel solution of the spatial dimension problem and the time dimension problem, compared with the single iterative solution method adopted in the existing technology, it has higher efficiency in calculation, can improve the efficiency of solving the objective function, and then can obtain the control strategy in time, and control the wind, solar, thermal and storage systems in time, thereby improving the real-time performance of the control. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of a wind-solar-thermal-storage system control method provided by one embodiment of the present invention.

[0042] Figure 2 It is a structural schematic diagram of a wind-solar-thermal-storage system control device provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] like Figure 1As shown, a method for controlling a wind-solar-thermal-storage system provided by an embodiment of the present invention includes:

[0045] Step S1: Obtain basic data of the wind, solar, thermal and energy storage system; wherein the basic data includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data;

[0046] Step S2: Based on the basic data, with the goal of minimizing the comprehensive cost of operation cost, frequency regulation standby cost and secondary frequency regulation response cost, construct an objective function of the wind-solar-thermal-storage system control model; and based on the basic data, construct the power flow constraint, standby constraint, secondary frequency regulation constraint, thermal power operation constraint, energy storage operation constraint, wind power operation constraint and photovoltaic operation constraint of the objective function; wherein, the power flow constraint, standby constraint, secondary frequency regulation constraint, wind power operation constraint and photovoltaic operation constraint belong to the space dimension, and the thermal power operation constraint and energy storage operation constraint belong to the time dimension;

[0047] Step S3: Under various constraints, the objective function is iteratively solved to generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and the wind, solar, thermal and storage system is controlled according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit; wherein, before iteratively solving the objective function, the objective function is decomposed into a spatial dimension problem and a time dimension problem according to various constraints; during the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are iteratively solved, and several time dimension sub-problems in the time dimension problem are iteratively solved, and when the preset convergence conditions are met, the control strategy is generated.

[0048] For step S1, basic data of the wind, solar, thermal and energy storage system is obtained, which includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data; preferably, the power data and topology data of the system need to be obtained. Among them, the thermal power unit operation data includes: thermal power set G, frequency regulation reserve capacity cost coefficient of thermal power unit i Frequency response cost coefficient of thermal power unit i The operating cost coefficient of thermal power units and the startup cost of thermal power unit i The shutdown cost of thermal power unit i The lower limit of active output of thermal power unit i Active output upper limit of thermal power unit i Maximum ramp rate of thermal power unit i Maximum landslide rate of thermal power unit i Minimum downtime of thermal power unit i in period t and the minimum startup time of thermal power unit i in period t Wind turbine operation data include: wind power set W, operation cost coefficient of wind turbine i Wind power abandonment penalty coefficient of wind turbine i and the predicted output value of wind turbine i in period t PV unit operation data includes: PV set P, PV unit operation cost coefficient Wind power abandonment penalty coefficient of PV unit i and the predicted output value of PV unit i in period t Energy storage equipment operation data includes: energy storage set B, frequency response cost coefficient of energy storage equipment i Charging cost coefficient of energy storage device i Discharge cost coefficient of energy storage device i The charge state of energy storage device i in time period t Discharge state quantity of energy storage device i in time period t The upper limit of charging power of energy storage device i in time period t The upper limit of the discharge power of energy storage device i in time period t The lower limit of the charge of energy storage device i and the upper limit of the charge of energy storage device i The power data includes: the voltage phase angle lower limit θ of node i i,min and the voltage phase angle upper limit θ at node i i,max ; Topological data includes: wind, solar, thermal and storage system node set and wind, solar, thermal and storage system branch set.

[0049] For step S2, based on the basic data obtained above, the objective function of the wind-solar-thermal-storage system control model is constructed with the goal of minimizing the comprehensive cost of operating cost, frequency regulation standby cost and secondary frequency regulation response cost. Among them, the operating cost includes: the operating cost of thermal power units, the operating cost of wind power units, the operating cost of photovoltaic units and the operating cost of energy storage equipment; the frequency regulation standby cost includes: the thermal power frequency regulation standby cost and the energy storage frequency regulation standby cost; the secondary frequency regulation response cost includes: the thermal power participation in the secondary frequency regulation response cost and the energy storage participation in the secondary frequency regulation response cost.

[0050] In a preferred embodiment, the objective function of the wind-solar-thermal-storage system control model is specifically:

[0051]

[0052] Among them, C represents the objective function; G is the thermal power set; W is the wind power set; P is the photovoltaic set; B is the energy storage set; M is the frequency regulation scenario set; is the operating cost of thermal power unit i in period t; is the active power output of thermal power unit i in period t; is the on / off status of thermal power unit i in period t; is the operating cost of energy storage device i in period t; is the charging power of energy storage device i in period t; is the discharge power of energy storage device i in period t; is the operating cost of wind turbine i in period t; is the active power output of wind turbine i in period t; is the operating cost of PV unit i in period t; is the active power output of photovoltaic unit i in period t; is the frequency regulation reserve capacity cost coefficient of thermal power unit i; is the upper reserve capacity of thermal power unit i for secondary frequency regulation during period t; is the lower reserve capacity of thermal power unit i for secondary frequency regulation during period t; is the frequency regulation reserve capacity cost coefficient of energy storage device i; is the upper reserve capacity of energy storage device i for secondary frequency regulation in period t; is the lower reserve capacity of energy storage device i for secondary frequency regulation in period t; is the frequency response cost coefficient of thermal power unit i; is the secondary frequency modulation power of thermal power unit i in time period τ in scenario m; is the frequency response cost coefficient of energy storage device i; is the secondary frequency modulation power of energy storage device i in time period τ in scenario m; a i 、b i and c i is the operating cost coefficient of thermal power unit i; is the startup cost of thermal power unit i; is the shutdown cost of thermal power unit i; is the charging cost coefficient of energy storage device i; is the discharge cost coefficient of energy storage device i; is the operating cost coefficient of wind turbine i; is the penalty coefficient of wind power abandonment of wind turbine i; is the predicted output value of wind turbine i in time period t; is the operating cost coefficient of the photovoltaic unit; is the penalty coefficient for abandoned photovoltaic power of PV unit i; is the predicted output value of PV unit i in time period t.

[0053] When regulating the wind, solar, thermal and storage systems, the actual physical limitations of each unit, system power balance, system backup requirements and secondary frequency regulation requirements are taken into consideration, and the flow constraints, backup constraints, secondary frequency regulation constraints, thermal power operation constraints, energy storage operation constraints, wind power operation constraints and photovoltaic operation constraints of the objective function are constructed based on the above basic data.

[0054] Power flow constraints include:

[0055]

[0056] Among them, I is the set of wind, solar, thermal and storage system nodes; L is the set of wind, solar, thermal and storage system branches; is the active load of node i in period t; P ij,t is the active power of the branch between node i and node j in time period t; θ i,t is the voltage phase angle of node i in period t; X ij is the branch reactance between node i and node j; P ij,max is the upper limit of the active power transmitted by the branch between node i and node j; θ i,min is the lower limit of the voltage phase angle at node i; θ i,max is the upper limit of the voltage phase angle at node i.

[0057] Thermal power operation constraints include:

[0058]

[0059] in, is the lower limit of active output of thermal power unit i; is the upper limit of active output of thermal power unit i; is the maximum ramp rate of thermal power unit i; is the maximum landslide rate of thermal power unit i; is the startup time of thermal power unit i in time period t; is the downtime of thermal power unit i in period t; is the minimum downtime of thermal power unit i in period t; is the minimum startup time of thermal power unit i in time period t.

[0060] Wind power operation constraints are:

[0061]

[0062] The photovoltaic operation constraints are:

[0063]

[0064] Energy storage operation constraints and reserve constraints include:

[0065]

[0066] in, is the state of charge of energy storage device i in time period t; is the discharge state quantity of energy storage device i in time period t; is the upper limit of charging power of energy storage device i in time period t; is the upper limit of the discharge power of energy storage device i in time period t; is the charge state of energy storage device i in time period t; is the active power output of energy storage device i; is the charging efficiency of energy storage device i; is the discharge efficiency of energy storage device i; is the lower limit of the charge of energy storage device i; is the upper limit of the charge of energy storage device i.

[0067] Secondary frequency modulation constraints include:

[0068]

[0069] in, is the frequency regulation reserve demand of the system in period t; is the frequency regulation reserve demand of the system in period t; and They are respectively the load, wind power and photovoltaic power fluctuations of the system in period τ in scenario m.

[0070] For step S3, under the above constraints, the objective function is iteratively solved to generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and the wind, solar, thermal and storage system is regulated according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit.

[0071] In a preferred embodiment, before decomposing the objective function into a spatial dimension problem and a time dimension problem according to each constraint, it also includes: determining a first coupling variable in the time dimension according to the thermal power operation constraint; wherein the first coupling variable includes: the active output of the thermal power unit, the on / off state of the thermal power unit, the spare capacity of the secondary frequency regulation of the thermal power unit, and the secondary frequency regulation power of the thermal power unit; determining a second coupling variable in the time dimension according to the energy storage operation constraint; wherein the second coupling variable includes: the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, and the secondary frequency regulation power of the energy storage device; generating a first replica variable corresponding to the spatial dimension according to the first coupling variable, generating a second replica variable corresponding to the spatial dimension according to the second coupling variable, and constructing a variable consistency constraint according to the first coupling variable, the second coupling variable, the first replica variable, and the second replica variable; obtaining a first Lagrangian multiplier of the first coupling variable, a second Lagrangian multiplier of the second coupling variable, and a penalty coefficient; constructing an augmented Lagrangian function of the objective function according to the variable consistency constraint, the first Lagrangian multiplier, the second Lagrangian multiplier, the penalty coefficient, and the objective function.

[0072] Specifically, in the process of regulating the wind, solar, thermal and energy storage system, due to a series of constraints in the time dimension and the space dimension, a complex time-space coupling relationship is formed in the constructed wind, solar, thermal and energy storage system regulation model and its objective function. In the spatial dimension, it includes flow constraints, standby constraints, secondary frequency regulation constraints, wind power operation constraints and photovoltaic operation constraints, among which there is no coupling relationship between wind power operation constraints and photovoltaic operation constraints; in the time dimension, it includes thermal power operation constraints and energy storage operation constraints. In order to speed up the solution without losing accuracy, the present invention decomposes the problem of solving the objective function under the constraints of the objective function into a spatial dimension problem containing several spatial dimension sub-problems and a time dimension problem containing several time dimension sub-problems by adding coupling variables and corresponding replication variables. The basis for dividing the spatial dimension problem and the time dimension problem is mainly divided according to the dimensions described in the constraint conditions.

[0073] Determine the first coupling variable in the time dimension according to the thermal power operation constraints As shown below:

[0074]

[0075] Determine the second coupling variable in the time dimension according to the energy storage operation constraints

[0076]

[0077] Generate the first replication variable corresponding to the space dimension according to the first coupling variable Generate the corresponding second replication variable in the spatial dimension according to the second coupling variable And the first coupling variable, the second coupling variable, the first copy variable and the second copy variable satisfy the variable consistency constraint shown in the following formula.

[0078]

[0079] Since the ADMM algorithm (alternating direction method of multipliers) has good convergence, the ADMM algorithm is used to obtain the first coupling variable before solving the time dimension problem and the space dimension problem in parallel. The first Lagrange multiplier of Second coupling variable The second Lagrange multiplier and penalty coefficient ρ, the first Lagrange multiplier Second Lagrange multiplier The variable consistency constraint formula (34) is relaxed to the objective function with the penalty coefficient ρ, and the augmented Lagrangian function L of the objective function is obtained. ρ As shown below:

[0080]

[0081] In a preferred embodiment, the objective function is decomposed into a spatial dimension problem and a temporal dimension problem according to the constraints, including: determining the spatial dimension problem according to the augmented Lagrangian function, power flow constraints, wind power operation constraints, photovoltaic operation constraints, reserve capacity constraints and secondary frequency regulation constraints of the objective function; determining the temporal dimension problem according to the augmented Lagrangian function, thermal power operation constraints, energy storage operation constraints, reserve capacity constraints and secondary frequency regulation constraints of the objective function.

[0082] In a preferred embodiment, during the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are solved iteratively, and several time dimension sub-problems in the time dimension problem are solved iteratively, including: for each iterative solution process, the spatial dimension problem at the current iteration moment and the time dimension problem at the current iteration moment are solved in parallel; wherein, for several spatial dimension sub-problems in the spatial dimension problem, iterative solutions are performed under the constraints of power flow constraints, wind power operation constraints, photovoltaic operation constraints, spare capacity constraints and secondary frequency regulation constraints to obtain the active output of the photovoltaic unit at the current iteration moment, the active output of the wind turbine unit at the current iteration moment, the first replicated variable at the current iteration moment and the second replicated variable at the current iteration moment; for several time dimension sub-problems in the time dimension problem, solutions are performed under the constraints of thermal power operation constraints, energy storage operation constraints, spare capacity constraints and secondary frequency regulation constraints to obtain the first coupling variable at the current iteration moment and the second coupling variable at the current iteration moment.

[0083] Specifically, based on power flow constraints, wind power operation constraints, photovoltaic operation constraints, reserve capacity constraints and secondary frequency regulation constraints, L ρ Decompose it into a series of spatial dimension sub-problems. Based on the thermal power operation constraints, energy storage operation constraints, reserve capacity constraints and secondary frequency regulation constraints, L ρ Decompose into a series of time dimension sub-problems.

[0084] The spatial dimension subproblem (t∈T) is a nonlinear programming model as follows:

[0085]

[0086] Among them, st represents constraint.

[0087] The time dimension sub-problem includes the thermal power operation sub-problem and the energy storage operation sub-problem, which is a mixed integer nonlinear programming model, as shown below:

[0088] Thermal power operation subproblem (i∈G):

[0089]

[0090] Energy storage operation subproblem (i∈B):

[0091]

[0092] According to the above decomposition results, formula (36) shows that the series of spatial dimension sub-problems after decomposition are independent in the time dimension. Similarly, formulas (37) and (38) show that the series of time dimension sub-problems after decomposition are independent in the spatial dimension. Therefore, in each iteration, the spatial dimension problem and the time dimension problem can be solved in parallel, and several spatial dimension sub-problems in the spatial dimension problem can be solved iteratively, and several time dimension sub-problems in the time dimension can be solved iteratively, thereby improving the solution efficiency.

[0093] In a preferred embodiment, after solving the spatial dimension problem at the current iteration time and the temporal dimension problem at the current iteration time in parallel, it also includes: generating the first Lagrangian multiplier at the next iteration time according to the first Lagrangian multiplier at the current iteration time, the penalty coefficient, the first coupling variable at the next iteration time, and the first replica variable at the next iteration time; generating the second Lagrangian multiplier at the next iteration time according to the second Lagrangian multiplier at the current iteration time, the penalty coefficient, the second coupling variable at the next iteration time, and the second replica variable at the next iteration time.

[0094] Specifically, in the iterative mechanism of the ADMM algorithm, at the end of the kth alternating iteration process, the Lagrange multiplier needs to be updated to adjust the optimization target of the k+1th iteration. The corresponding first Lagrange multiplier and second Lagrange multiplier are updated in the k+1th iteration as shown in the following formula:

[0095]

[0096] In a preferred embodiment, the preset convergence condition is specifically: the dual variable residual at the current iteration moment is not greater than the preset convergence accuracy; wherein the dual variable residual at the current iteration moment is determined based on the first coupling variable at the current iteration moment, the second coupling variable at the current iteration moment, the first copy variable at the current iteration moment, and the second copy variable at the current iteration moment.

[0097] Specifically, after each iteration is completed, the dual variable residual at the current iteration time needs to be determined according to the first coupling variable at the current iteration time, the second coupling variable at the current iteration time, the first copy variable at the current iteration time, and the second copy variable at the current iteration time. The corresponding calculation formula is as follows:

[0098]

[0099] Among them, ||||2 is the binary norm; ε is the dual variable residual at the kth iteration; ε0 is the preset convergence accuracy; is the first coupling variable at the kth iteration; is the second coupling variable at the kth iteration; is the first replicated variable in the kth iteration; is the second replicate variable at the kth iteration.

[0100] During any iteration, when the calculated dual variable residual reaches the preset convergence accuracy, the ADMM algorithm is considered to have reached the convergence condition. and This is the optimal solution, that is, the control strategy of the wind, solar, thermal and storage system when the comprehensive cost is minimized.

[0101] Exemplarily, after the decomposition of the time dimension problem and the space dimension problem is completed, the iterative calculation process based on the ADMM algorithm is as follows:

[0102] Step S101: Initialization and ε0, initializing iteration index k = 1;

[0103] Step S201: Solve the spatial dimension sub-problems in parallel, that is, solve formula (36) to obtain and

[0104] Step S301: Solve the time dimension sub-problem in parallel, that is, solve formulas (37) and (38) to obtain Z G,k and Z B,k ;

[0105] Step S401: Update according to formula (39) and

[0106] Step S501: Calculate ε according to formula (40);

[0107] Step S601: If ε≤ε0, stop the iteration and output the optimal control strategy; if ε>ε0, k=k+1, and re-execute steps S201 to S601.

[0108] Based on the above method embodiment, the present invention provides a corresponding device embodiment.

[0109] like Figure 2 As shown, an embodiment of the present invention provides a wind-solar-thermal-storage system control device, including: a data acquisition module, a model building module and a model solving and control module;

[0110] The data acquisition module is used to acquire basic data of the wind, solar, thermal and energy storage system; wherein the basic data includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data;

[0111] The model building module is used to construct the objective function of the wind-solar-thermal-storage system control model based on the basic data, with the goal of minimizing the comprehensive cost of operation cost, frequency regulation standby cost and secondary frequency regulation response cost; and construct the power flow constraint, standby constraint, secondary frequency regulation constraint, thermal power operation constraint, energy storage operation constraint, wind power operation constraint and photovoltaic operation constraint of the objective function based on the basic data; wherein the power flow constraint, standby constraint, secondary frequency regulation constraint, wind power operation constraint and photovoltaic operation constraint belong to the space dimension, and the thermal power operation constraint and energy storage operation constraint belong to the time dimension;

[0112] The model solving and control module is used to iteratively solve the objective function under various constraints, generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and control the wind, solar, thermal and storage system according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit; wherein, before iteratively solving the objective function, the objective function is decomposed into a spatial dimension problem and a time dimension problem according to various constraints; during the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are iteratively solved, and several time dimension sub-problems in the time dimension problem are iteratively solved, and when the preset convergence conditions are met, the control strategy is generated.

[0113] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0114] Those skilled in the art can clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0115] Based on the above method item embodiments, the present invention provides corresponding terminal device item embodiments.

[0116] An embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, a wind, solar, thermal and energy storage system control method as described in any one of the present invention is implemented.

[0117] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0118] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0119] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0120] Based on the above method item embodiments, the present invention provides a corresponding storage medium item embodiment.

[0121] An embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a wind, solar, thermal and energy storage system control method as described in any one of the present inventions.

[0122] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.

[0123] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for controlling a wind-solar-thermal-storage system, characterized in that: include: Obtaining basic data of the wind, solar, thermal and energy storage system; wherein the basic data includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data; According to the basic data, the objective function of the wind-solar-thermal-storage system control model is constructed with the goal of minimizing the comprehensive cost of operation cost, frequency regulation reserve cost and secondary frequency regulation response cost; and based on the basic data, the power flow constraint, reserve constraint, secondary frequency regulation constraint, thermal power operation constraint, energy storage operation constraint, wind power operation constraint and photovoltaic operation constraint of the objective function are constructed; among which, the power flow constraint, reserve constraint, secondary frequency regulation constraint, wind power operation constraint and photovoltaic operation constraint belong to the spatial dimension, and the thermal power operation constraint and energy storage operation constraint belong to the temporal dimension; Under various constraints, the objective function is iteratively solved to generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and the wind, solar, thermal and storage system is controlled according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit; Before iteratively solving the objective function, the objective function is decomposed into a spatial dimension problem and a temporal dimension problem according to various constraints; during the iterative solution, the spatial dimension problem and the temporal dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are iteratively solved, and several temporal dimension sub-problems in the temporal dimension problem are iteratively solved, and when the preset convergence conditions are met, the control strategy is generated.

2. A method for controlling a wind-solar-thermal-storage system according to claim 1, characterized in that: Before decomposing the objective function into spatial dimension problems and time dimension problems according to various constraints, it also includes: Determine the first coupling variable in the time dimension according to the thermal power operation constraint; wherein the first coupling variable includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the secondary frequency regulation of the thermal power unit, and the secondary frequency regulation power of the thermal power unit; Determine a second coupling variable in the time dimension according to the energy storage operation constraint; wherein the second coupling variable includes: charging power of the energy storage device, discharging power of the energy storage device, spare capacity of the energy storage device, and secondary frequency modulation power of the energy storage device; Generate a first replica variable corresponding to the space dimension according to the first coupling variable, generate a second replica variable corresponding to the space dimension according to the second coupling variable, and construct a variable consistency constraint according to the first coupling variable, the second coupling variable, the first replica variable, and the second replica variable; Obtaining a first Lagrange multiplier of a first coupling variable, a second Lagrange multiplier of a second coupling variable, and a penalty coefficient; An augmented Lagrangian function of the objective function is constructed according to the variable consistency constraint, the first Lagrangian multiplier, the second Lagrangian multiplier, the penalty coefficient and the objective function.

3. A method for controlling a wind-solar-thermal-storage system according to claim 2, characterized in that: Decomposing the objective function into a spatial dimension problem and a temporal dimension problem according to the constraints includes: Determine the spatial dimension problem according to the augmented Lagrangian function of the objective function, power flow constraints, wind power operation constraints, photovoltaic operation constraints, reserve capacity constraints and secondary frequency regulation constraints; The time dimension problem is determined according to the augmented Lagrangian function of the objective function, thermal power operation constraints, energy storage operation constraints, reserve capacity constraints and secondary frequency regulation constraints.

4. A method for controlling a wind-solar-thermal-storage system according to claim 3, characterized in that: During the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are solved iteratively, and several time dimension sub-problems in the time dimension problem are solved iteratively, including: For each iterative solution process, the spatial dimension problem at the current iteration moment and the time dimension problem at the current iteration moment are solved in parallel; Among them, for several spatial dimension sub-problems in the spatial dimension problem, iterative solutions are performed under the constraints of power flow constraints, wind power operation constraints, photovoltaic operation constraints, reserve capacity constraints and secondary frequency regulation constraints to obtain the active output of the photovoltaic unit at the current iteration moment, the active output of the wind turbine unit at the current iteration moment, the first replicated variable at the current iteration moment and the second replicated variable at the current iteration moment; For several time dimension sub-problems in the time dimension problem, they are solved under the constraints of thermal power operation constraints, energy storage operation constraints, reserve capacity constraints and secondary frequency regulation constraints to obtain the first coupling variable at the current iteration moment and the second coupling variable at the current iteration moment.

5. A method for controlling a wind-solar-thermal-storage system according to claim 4, characterized in that: The preset convergence condition is specifically: The dual variable residual at the current iteration moment is not greater than the preset convergence accuracy; wherein, the dual variable residual at the current iteration moment is determined according to the first coupling variable at the current iteration moment, the second coupling variable at the current iteration moment, the first copy variable at the current iteration moment, and the second copy variable at the current iteration moment.

6. A method for controlling a wind-solar-thermal-storage system according to claim 4, characterized in that: After solving the spatial dimension problem at the current iteration time and the time dimension problem at the current iteration time in parallel, it also includes: Generate a first Lagrange multiplier at the next iteration time according to the first Lagrange multiplier at the current iteration time, the penalty coefficient, the first coupling variable at the next iteration time, and the first replica variable at the next iteration time; The second Lagrange multiplier at the next iteration time is generated according to the second Lagrange multiplier at the current iteration time, the penalty coefficient, the second coupling variable at the next iteration time, and the second replica variable at the next iteration time.

7. A method for controlling a wind-solar-thermal-storage system according to claim 1, characterized in that: The objective function of the wind-solar-thermal-storage system control model is specifically: Among them, C represents the objective function; G is the thermal power set; W is the wind power set; P is the photovoltaic set; B is the energy storage set; M is the frequency regulation scenario set; is the operating cost of thermal power unit i in period t; is the active power output of thermal power unit i in period t; is the on / off status of thermal power unit i in period t; is the operating cost of energy storage device i in period t; is the charging power of energy storage device i in period t; is the discharge power of energy storage device i in period t; is the operating cost of wind turbine i in period t; is the active power output of wind turbine i in period t; is the operating cost of PV unit i in period t; is the active power output of photovoltaic unit i in period t; is the frequency regulation reserve capacity cost coefficient of thermal power unit i; is the upper reserve capacity of thermal power unit i for secondary frequency regulation during period t; is the lower reserve capacity of thermal power unit i for secondary frequency regulation during period t; is the frequency regulation reserve capacity cost coefficient of energy storage device i; is the upper reserve capacity of energy storage device i for secondary frequency regulation in period t; is the lower reserve capacity of energy storage device i for secondary frequency regulation in period t; is the frequency response cost coefficient of thermal power unit i; is the secondary frequency modulation power of thermal power unit i in time period τ in scenario m; is the frequency response cost coefficient of energy storage device i; is the secondary frequency modulation power of energy storage device i in time period τ in scenario m; a i 、b i and c i is the operating cost coefficient of thermal power unit i; is the startup cost of thermal power unit i; is the shutdown cost of thermal power unit i; is the charging cost coefficient of energy storage device i; is the discharge cost coefficient of energy storage device i; is the operating cost coefficient of wind turbine i; is the penalty coefficient of wind power abandonment of wind turbine i; is the predicted output value of wind turbine i in time period t; is the operating cost coefficient of the photovoltaic unit; is the penalty coefficient for abandoned photovoltaic power of PV unit i; is the predicted output value of PV unit i in time period t.

8. A wind-solar-thermal-storage system control device, characterized in that: include: Data acquisition module, model building module and model solving and regulation module; The data acquisition module is used to acquire basic data of the wind, solar, thermal and energy storage system; wherein the basic data includes: thermal power unit operation data, wind power unit operation data, photovoltaic unit operation data and energy storage device operation data; The model building module is used to construct the objective function of the wind-solar-thermal-storage system control model based on the basic data, with the goal of minimizing the comprehensive cost of operation cost, frequency regulation standby cost and secondary frequency regulation response cost; and construct the power flow constraint, standby constraint, secondary frequency regulation constraint, thermal power operation constraint, energy storage operation constraint, wind power operation constraint and photovoltaic operation constraint of the objective function based on the basic data; wherein the power flow constraint, standby constraint, secondary frequency regulation constraint, wind power operation constraint and photovoltaic operation constraint belong to the space dimension, and the thermal power operation constraint and energy storage operation constraint belong to the time dimension; The model solving and control module is used to iteratively solve the objective function under various constraints, generate a control strategy for the wind, solar, thermal and storage system when the comprehensive cost is minimized, and control the wind, solar, thermal and storage system according to the control strategy; the control strategy includes: the active output of the thermal power unit, the on / off status of the thermal power unit, the spare capacity of the thermal power unit, the secondary frequency modulation power of the thermal power unit, the charging power of the energy storage device, the discharging power of the energy storage device, the spare capacity of the energy storage device, the secondary frequency modulation power of the energy storage device, the active output of the photovoltaic unit and the active output of the wind power unit; wherein, before iteratively solving the objective function, the objective function is decomposed into a spatial dimension problem and a time dimension problem according to various constraints; during the iterative solution, the spatial dimension problem and the time dimension problem are solved in parallel, several spatial dimension sub-problems in the spatial dimension problem are iteratively solved, and several time dimension sub-problems in the time dimension problem are iteratively solved, and when the preset convergence conditions are met, the control strategy is generated.

9. A terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a wind, solar, thermal and energy storage system control method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a wind-solar-thermal-storage system control method as described in any one of claims 1 to 7.

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