Energy storage cluster operation regulation method and apparatus taking market clearing into consideration

Abstract

Disclosed in the present application are an energy storage cluster operation regulation method and apparatus taking market clearing into consideration. In the present application, power grid load data in the next cycle is predicted by means of historical power grid load data; operating parameters of a thermal power unit and operating parameters of an energy storage cluster are further acquired; in view of the operating parameters of the thermal power unit and the operating parameters of the energy storage cluster, a preset energy storage cluster operation regulation model is initialized, wherein the energy storage cluster operation regulation model is a double-layer optimization model, and is acquired by means of coupling an energy storage cluster utilization rate optimization model and a power market clearing model, an upper layer being the energy storage cluster utilization rate optimization model so as to improve the utilization rate of the energy storage cluster, and a lower layer being the power market clearing model for optimizing the distribution of electric energy and frequency modulation capacity of the thermal power unit and the energy storage cluster; and on the basis of a solving result of the energy storage cluster operation regulation model, the charging / discharging power and frequency modulation capacity of each energy storage power station within each time period are set. The present application specifies the application scenario of an energy storage cluster, and uniformly optimizes and regulates different energy storage power stations in the form of a cluster, thereby improving the utilization rate of the energy storage power stations.

Description

A method and device for operating and regulating an energy storage cluster considering market clearing TECHNICAL FIELD

[0001] The present application relates to the field of power grid energy storage planning, and in particular to a method and device for operating and regulating an energy storage cluster considering market clearing. BACKGROUND

[0002] With the continuous increase in installed capacity of new energy, the accommodation pressure of new energy increases, and energy storage is an important strategic support for promoting new energy accommodation, building a new power system, and planning and constructing a new energy system. In recent years, energy storage has developed rapidly. Currently, new energy storage projects mainly include independent energy storage and new energy storage, and the application mode of grid-side energy storage power stations is relatively single, and the market clearing factors are not considered comprehensively, resulting in a low average utilization rate index of grid-side energy storage power stations. The average utilization rate index refers to the ratio of the utilization hours of the energy storage power station during the statistical period to the designed charging and discharging hours during the statistical period, and the driving force for the active operation of the energy storage power station is not fully stimulated, which easily leads to waste of energy storage equipment resources. On the other hand, when different energy storage power stations participate in the electricity market as independent subjects, due to different investment costs of different energy storage power stations, their operation declaration strategies in the electricity market are different, and the differences in the declaration strategies between different energy storage power stations affect the calculation efficiency of the market clearing model.

[0003] Therefore, how to aggregate independently distributed energy storage resources in the form of an energy storage cluster for unified operation and regulation, considering market clearing factors, and more quickly and efficiently obtaining an energy storage cluster operation scheme with higher energy storage power station resource utilization is a technical problem to be solved at present. SUMMARY

[0004] The present application provides a method and device for operating and regulating an energy storage cluster considering market clearing, to solve the technical problem of low utilization rate of energy storage power stations, which leads to unreasonable utilization of energy storage resources.

[0005] To solve the above technical problems, in a first aspect, the present application provides a method for operating and regulating an energy storage cluster considering market clearing, comprising:

[0006] acquiring a thermal power unit operation parameter, an energy storage cluster operation parameter, and a power grid historical load data, respectively, and predicting power grid load data of a next complete operation period according to the power grid historical load data;

[0007] initialize a preset energy storage cluster operation regulation model according to the predicted power grid load data, the operation parameters of the thermal power generating units, and the operation parameters of the energy storage clusters; the energy storage cluster operation regulation model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model; the energy storage cluster utilization optimization model is obtained by optimizing the utilization of the energy storage clusters; and the power market clearing model is obtained by optimizing the distribution of the energy and frequency modulation capacity of the thermal power generating units and the energy storage clusters;

[0008] solving the energy storage cluster operation regulation model to obtain an optimal energy storage cluster operation scheme, and setting the charging and discharging power and the frequency modulation capacity of each energy storage power station in the energy storage cluster in each time period according to the optimal energy storage cluster operation scheme.

[0009] Compared with the prior art, the embodiments of the application have the following beneficial effects: when the energy storage cluster operation regulation model is constructed, the application scenarios of the energy storage clusters are determined, the utilization of each energy storage power station in the energy storage clusters and the distribution of the energy and frequency modulation capacity of the energy storage clusters and the thermal power generating units are fully considered, the utilization of each energy storage power station is improved while meeting the requirements of the power market clearing, different energy storage power stations are uniformly involved in the power market clearing in the form of energy storage clusters, the calculation complexity of the market clearing model is reduced, and the application-proposed energy storage cluster operation regulation method considering the market clearing can simulate the application scenarios of the independent energy storage power stations participating in the power market, can provide a reference for the operation scheme of the energy storage and the declaration strategy of participating in the power market, thereby improving the utilization of the independent energy storage power stations and the calculation efficiency of the market clearing, and making the finally obtained optimal energy storage cluster operation scheme more close to the actual operation environment.

[0010] In some embodiments of the first aspect of the application, the energy storage cluster operation regulation model is obtained by coupling the energy storage cluster utilization optimization model and the power market clearing model, and includes:

[0011] first-order partial derivatives of each decision variable of the Lagrangian function of the power market clearing model are obtained to obtain additional equality constraints;

[0012] the KKT condition is applied to the power market clearing model to obtain additional complementary constraints;

[0013] the energy storage cluster operation regulation model is obtained in combination with the energy storage cluster utilization optimization model and the additional equality constraints and the additional complementary constraints.

[0014] Compared with the prior art, the above-mentioned embodiment has the following beneficial effects: since the energy storage cluster utilization rate optimization model and the power market clearing model are nested optimization models, the optimal utilization rate energy storage cluster operation scheme solved by the energy storage cluster utilization rate optimization model is further substituted into the power market clearing model to obtain an optimal cost energy storage cluster operation scheme under the influence of the power market clearing, and then the optimal cost energy storage cluster operation scheme is substituted into the energy storage cluster utilization rate optimization model for repeated iteration and solving. It can be seen that in the above solving process, two models need to be calculated repeatedly, and the calculation efficiency is not high. The KKT condition is applied to the above double-layer model for further processing, the power market clearing model is converted into an additional constraint of the energy storage cluster utilization rate optimization model, the double-layer model is converted into a single-layer model for solving, and the solving efficiency is improved.

[0015] In some embodiments of the first aspect of the application, the energy storage cluster utilization rate optimization model is constructed by optimizing the energy storage cluster utilization rate and comprises:

[0016] a first optimization objective function is constructed by combining the charge and discharge power, frequency modulation capacity and power market clearing price of the energy storage cluster;

[0017] a first constraint is constructed by combining the energy storage cluster operation constraint and the energy storage cluster energy cost, frequency modulation capacity and frequency modulation mileage cost constraint;

[0018] The energy storage cluster utilization rate optimization model is obtained by combining the first optimization objective function and the first constraint.

[0019] In some embodiments of the first aspect of the application, the first optimization objective function is constructed by combining the charge and discharge power, frequency modulation capacity and power market clearing price of the energy storage cluster, and comprises:

[0020] The first optimization objective function is specifically:

[0021] wherein λ t , and are the energy market, frequency modulation capacity and frequency modulation mileage clearing prices of period t; and are the bid charge and discharge power of energy storage power station j in period t; is the bid frequency modulation capacity of energy storage power station j in period t; and es,j S is the frequency modulation mileage factor of energy storage power station j.

[0022] In some embodiments of the first aspect of the application, the first constraint is constructed by combining the energy storage cluster operation constraint and the energy storage cluster charge and discharge cost, frequency modulation capacity cost constraint, and comprises:

[0023] The energy storage cluster operation constraint, in particular:

[0024] The energy storage cluster electric energy cost, frequency modulation capacity and frequency modulation mileage cost constraint, in particular:

[0025] Wherein, and Respectively, the bid charging and discharging power of the energy storage power station j in the time period t; and Respectively, the maximum charging and discharging power of the energy storage power station j in the time period t; and Respectively, the bid frequency modulation capacity and frequency modulation mileage of the energy storage power station j; and Respectively, the maximum frequency modulation capacity and mileage of the energy storage power station j in the time period t; es,j The frequency modulation mileage factor of the energy storage power station j; E es,j,t The energy value of the energy storage power station j in the time period t; and Respectively, the charging and discharging efficiency of the energy storage power station j; and Respectively, the initial energy and final energy value of the energy storage power station j; and Respectively, the charging and discharging cost of the energy storage power station j in the time period t; and Respectively, the maximum charging and discharging cost of the energy storage power station j in the time period t; and Respectively, the frequency modulation capacity cost and frequency modulation mileage cost of the energy storage power station j in the time period t; and Respectively, the maximum frequency modulation capacity cost and frequency modulation mileage cost of the energy storage power station j in the time period t; The dual variable corresponding to the constraint condition.

[0026] Compared with the prior art, the energy storage cluster utilization optimization model provided by the above embodiment has the following beneficial effects: different energy storage power stations are unified to participate in power market settlement in the form of a cluster, which reduces the complexity of the market settlement model; in the process of constructing the model, the utilization rate of each energy storage power station in the energy storage cluster is accurately evaluated by considering the power market settlement price, combining the charging and discharging power of the energy storage cluster and the frequency modulation capacity, thereby improving the utilization rate of each energy storage power station.

[0027] In some embodiments of the first aspect of the application, the power market clearing model is constructed by optimizing the allocation of the electric energy and frequency modulation capacity of the thermal power units and the energy storage clusters, and comprises:

[0028] A second optimization objective function is constructed by combining the allocation of the electric energy and frequency modulation capacity of the thermal power units and the energy storage clusters;

[0029] A second constraint is constructed by combining the energy storage cluster operation constraint, the power grid operation balance constraint, the thermal power unit operation constraint, and the system frequency modulation demand constraint;

[0030] The power market clearing model is obtained by combining the second optimization objective function and the second constraint.

[0031] In some embodiments of the first aspect of the application, the second optimization objective function is constructed by combining the allocation of the electric energy and frequency modulation capacity of the thermal power units and the energy storage clusters, and comprises:

[0032] The second optimization objective function is specifically:

[0033] wherein price g,i,t is the generation cost of the thermal power unit i in the time period t; P g,i,t is the winning generation capacity of the thermal power unit i in the time period t; and are the charging and discharging costs of the energy storage power station j in the time period t, respectively; and are the winning charging and discharging powers of the energy storage power station j in the time period t, respectively; and are the frequency modulation capacity costs of the thermal power unit i and the energy storage power station j in the time period t, respectively; and are the frequency modulation mileage costs of the thermal power unit i and the energy storage power station j; S g,i and S es,j are the frequency modulation mileage factors of the thermal power unit i and the energy storage power station j, respectively; and are the winning frequency modulation capacities of the thermal power unit i and the energy storage power station j in the time period t, respectively.

[0034] In some embodiments of the first aspect of the application, the second constraint is constructed by combining the energy storage cluster operation constraint, the power grid operation balance constraint, the thermal power unit operation constraint, and the system frequency modulation demand constraint, and comprises:

[0035] The energy storage cluster operation constraint is specifically:

[0036] The power grid operation balance constraint is specifically:

[0037] The thermal power unit operation constraints, in particular:

[0038] The system frequency regulation demand constraints, in particular:

[0039] Wherein, and are the bid charging and discharging power of the energy storage power station j in period t; and are the maximum charging and discharging power of the energy storage power station j in period t; and are the bid frequency regulation capacity and mileage of the energy storage power station j in period t; and are the maximum frequency regulation capacity and mileage of the energy storage power station j in period t; es,j is the frequency regulation mileage factor of the energy storage power station j; E es,j,t is the energy value of the energy storage power station j in period t; and are the charging and discharging efficiencies of the energy storage power station j; and are the initial and final energy values of the energy storage power station j; ψ g (b), ψ es (b), ψ load (b) represent the set of thermal power units, energy storage power stations and loads located at node b, respectively; P g,i,t is the bid generation capacity of the thermal power unit i in period t; represents the set of branches connected to node b; P L,t is the power flowing into node b of line L at time t; P D,t is the power of load D; λ t , and are the clearing prices of the electricity market, frequency regulation capacity and frequency regulation mileage in period t, which are also the dual variables of the corresponding constraints; is the maximum power of line transmission; P Lij,t is the transmission power of line L ij at time t; θ i,t and θ j,t are the phase angles at both ends of line L ij in period t; x ij is the reactance of line L ij ; represents the set of branches connected to node i; and are respectively the minimum output and the maximum output of the thermal power generating unit i in the time period t; and are respectively the winning frequency modulation capacity and the winning frequency modulation mileage of the thermal power generating unit i in the time period t; and are respectively the maximum frequency modulation capacity and the maximum frequency modulation mileage of the thermal power generating unit i in the time period t; g,i is the frequency modulation mileage factor of the thermal power generating unit i; and are respectively the frequency modulation capacity demand and the frequency modulation mileage demand of the system in the time period t; is the dual variable corresponding to the constraint condition.

[0040] Compared with the prior art, the power market clearing model provided by the above embodiment has the following beneficial effects: the application constructs a power market clearing model by dynamically adjusting the power energy and frequency modulation capacity distribution of each energy storage power station in the energy storage cluster and the thermal power generating unit, realizes operation optimization of the thermal power generating unit and the energy storage cluster while obtaining the power market clearing price, thereby providing a reference for the operation strategy of the energy storage cluster and improving the utilization rate of the energy storage power station.

[0041] In a second aspect, the application also provides an energy storage cluster operation regulation and control device considering market clearing, comprising: a first data pre-acquisition module, a model initialization module and a scheme acquisition module;

[0042] The first data pre-acquisition module is configured to acquire the thermal power generating unit operation parameters, the energy storage cluster operation parameters and the power grid historical load data respectively, and predict the power grid load data of the next complete operation period according to the power grid historical load data.

[0043] The model initialization module is configured to initialize a preset energy storage cluster operation regulation and control model according to the predicted power grid load data, the thermal power generating unit operation parameters and the energy storage cluster operation parameters; the energy storage cluster operation regulation and control model is obtained by coupling an energy storage cluster utilization rate optimization model and a power market clearing model; the energy storage cluster utilization rate optimization model is obtained by optimizing the energy storage cluster utilization rate; and the power market clearing model is obtained by optimizing the power energy and frequency modulation capacity distribution of the thermal power generating unit and the energy storage cluster.

[0044] The scheme acquisition module is configured to solve the energy storage cluster operation regulation and control model, acquire an optimal energy storage cluster operation scheme, and set the charge-discharge power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each time period according to the optimal energy storage cluster operation scheme.

[0045] In some embodiments of the second aspect of the application, the energy storage cluster operation regulation model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model, and comprises:

[0046] a first-order partial derivative of each decision variable of the Lagrangian function of the power market clearing model is obtained to obtain additional equality constraints;

[0047] the KKT condition is applied to the power market clearing model to obtain additional complementary constraints;

[0048] the energy storage cluster operation regulation model is obtained in combination with the energy storage cluster utilization optimization model and the additional equality constraints and the additional complementary constraints. BRIEF DESCRIPTION OF DRAWINGS

[0049] FIG. 1 is a flowchart of a method for regulating operation of an energy storage cluster considering market clearing according to some embodiments of the application;

[0050] FIG. 2 is a flowchart of a method for transforming a double-layer model according to some embodiments of the application using the KKT condition;

[0051] FIG. 3 is a structural diagram of a device for regulating operation of an energy storage cluster considering market clearing according to some embodiments of the application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, but not all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the application.

[0053] Embodiment One

[0054] Referring to FIG. 1, a method for regulating operation of an energy storage cluster considering market clearing according to an embodiment of the application comprises S10 to S30, and specifically comprises:

[0055] S10: Obtain thermal power unit operation parameters, energy storage cluster operation parameters, and power grid historical load data, respectively, and predict power grid load data for a next complete operation period according to the power grid historical load data.

[0056] Preferably, in step S10, the prediction of power grid load data for a next complete operation period according to the power grid historical load data can be obtained by any machine learning algorithm, and the application does not limit the prediction method.

[0057] S20: initializing a preset energy storage cluster operation regulation model according to the predicted power grid load data, the thermal power unit operation parameters, and the energy storage cluster operation parameters; the energy storage cluster operation regulation model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model; the energy storage cluster utilization optimization model is obtained by optimizing energy storage cluster utilization; and the power market clearing model is obtained by optimizing allocation of energy and frequency modulation capacity of the thermal power unit and the energy storage cluster.

[0058] In some embodiments of the present application, the energy storage cluster utilization optimization model is obtained by optimizing energy storage cluster utilization, and includes:

[0059] a first optimization objective function is constructed by combining frequency modulation of the energy storage cluster and frequency modulation capacity cost of the energy storage cluster;

[0060] a first constraint is constructed by combining energy storage cluster operation constraints and energy storage cluster energy cost, frequency modulation capacity, and frequency modulation mileage cost constraints;

[0061] the energy storage cluster utilization optimization model is obtained by combining the first optimization objective function and the first constraint.

[0062] By participating in power market clearing in the form of a cluster, the complexity of the market clearing model is reduced, and the execution efficiency of the subsequent energy storage cluster operation scheme is improved. At the same time, when optimizing the utilization of the energy storage cluster, the utilization of the energy storage cluster is comprehensively evaluated by comprehensively considering the charging and discharging power, frequency modulation capacity, and power market clearing price of the energy storage cluster, so as to improve the utilization of each energy storage power station in the subsequent energy storage cluster operation scheme.

[0063] Preferably, in some embodiments of the present application, the above-mentioned energy storage cluster utilization optimization model can be obtained by the following preferred implementation:

[0064] S211: constructing an optimization objective function of the energy storage cluster utilization optimization model:

[0065] S212: constructing a constraint of the energy storage cluster utilization optimization model by combining energy storage cluster operation constraints and energy storage cluster energy cost, frequency modulation capacity, and frequency modulation mileage cost constraints:

[0066] The energy storage cluster operation constraints are specifically:

[0067] The energy storage cluster energy cost, frequency modulation capacity, and frequency modulation mileage cost constraints are specifically:

[0068] In the above S211-S212 formulas, λ t , and are the energy market, frequency modulation capacity and frequency modulation mileage clearing prices of period t, respectively; and are the bid charging and discharging powers of the energy storage power station j in period t, respectively; and are the bid frequency modulation capacity and frequency modulation mileage of the energy storage power station j in period t, respectively; es,j is the frequency modulation mileage factor of the energy storage power station j; and are the maximum charging and discharging powers of the energy storage power station j in period t, respectively; and are the maximum frequency modulation capacity and mileage of the energy storage power station j in period t, respectively; es,j,t is the energy value of the energy storage power station j in period t; and are the charging and discharging efficiencies of the energy storage power station j, respectively; and are the initial energy and final energy values of the energy storage power station j, respectively; and are the charging and discharging costs of the energy storage power station j in period t, respectively; and are the maximum charging and discharging costs of the energy storage power station j in period t, respectively; and are the frequency modulation capacity cost and frequency modulation mileage cost of the energy storage power station j in period t, respectively; and are the maximum frequency modulation capacity cost and frequency modulation mileage cost of the energy storage power station j in period t, respectively; are the dual variables corresponding to the constraint conditions.

[0069] In some embodiments of the present application, the power market clearing model is constructed by optimizing the energy and frequency modulation capacity allocation of the thermal power unit and the energy storage cluster, and comprises:

[0070] a second optimization objective function is constructed by combining the energy and frequency modulation capacity allocation of the thermal power unit and the energy storage cluster;

[0071] a second constraint is constructed by combining the grid operation balance constraint, the thermal power unit operation constraint and the system frequency modulation demand constraint;

[0072] the power market clearing model is obtained by combining the second optimization objective function and the second constraint.

[0073] Preferably, in some embodiments of this application, the above-mentioned electricity market clearing model can be constructed and obtained through the following preferred implementation methods:

[0074] S221: Constructing the optimization objective function for the electricity market clearing model:

[0075] S222: Combining the energy storage cluster operation constraints (i.e., the energy storage cluster operation constraints in S212), grid operation balance constraints, thermal power unit operation constraints, and system frequency regulation demand constraints, the constraints for constructing the electricity market clearing model are as follows:

[0076] The power grid operation balance constraints are as follows:

[0077] The operating constraints of thermal power units are as follows:

[0078] The system frequency regulation requirement constraints are as follows:

[0079] In the formulas S221 to S222 above, price g,i,t , These represent the generation cost, frequency regulation capacity cost, and frequency regulation mileage cost of thermal power unit i during time period t; P g,i,t S represents the power generation of thermal power unit i during time period t; g,i ψ is the frequency regulation mileage factor for thermal power unit i; g (b) ψ es (b) ψ load (b) represents the set of thermal power units, energy storage power stations, and loads located at node b; P g,i,t The winning bid for the power generation of thermal power unit i during time period t; P represents the set of branches connected to node b; L,t P is the power flowing into node b from line L at time t. D,t λ is the power of load D; t , and These are the electricity market, frequency regulation capacity, and frequency regulation mileage clearing price for time period t, respectively, and also the dual variables of the corresponding constraints. P represents the maximum power transmitted through the line. Lij,t For time t, line L ij The transmission power; θ i,t and θ j,t For time period t, line L ij Phase angle at both ends; x ij For line L ij The reactance; denotes the set of branches connected to node i; and denote the minimum and maximum output of thermal power unit i at time period t respectively; and denote the winning frequency modulation capacity and frequency modulation mileage of thermal power unit i at time period t respectively; and denote the maximum frequency modulation capacity and frequency modulation mileage of thermal power unit i at time period t respectively; and denote the frequency modulation capacity demand and frequency modulation mileage demand of the system at time period t respectively; denote the dual variables corresponding to the constraints.

[0080] When the energy storage cluster utilization optimization model and the power market clearing model are obtained through the above preferred embodiments, the energy storage cluster utilization optimization model and the power market clearing model can be iteratively solved through the following preferred embodiments to obtain an optimized energy storage cluster operation scheme:

[0081] S231: initialize the energy storage cluster utilization optimization model through a preset power market clearing price, and solve the energy storage cluster utilization optimization model to obtain an energy storage cluster operation scheme under the current iteration;

[0082] S232: obtain a preset thermal power unit declaration strategy and the energy storage cluster operation scheme obtained in S231, initialize the power market clearing model, and solve the power market clearing model to obtain a power market clearing price, and evaluate the utilization rate of the current energy storage cluster operation scheme according to the optimization objective function of the energy storage cluster utilization optimization model;

[0083] S233: when the utilization rate calculated in S232 is greater than the utilization rate calculated in the last iteration, stop the iteration, otherwise, according to the power market clearing price solved in S232, re-execute S231.

[0084] In some embodiments of the present application, the energy storage cluster operation regulation model is obtained by coupling the energy storage cluster utilization optimization model and the power market clearing model, and includes:

[0085] first-order partial derivatives of each decision variable of the Lagrangian function of the power market clearing model are taken to obtain additional equality constraints;

[0086] the KKT condition is applied to the power market clearing model to obtain additional complementary constraints;

[0087] the energy storage cluster operation regulation model is obtained in combination with the energy storage cluster utilization optimization model and the additional equality constraints and the additional complementary constraints.

[0088] As can be seen from S231 to S233, since the energy storage cluster utilization rate optimization model and the power market clearing model are nested optimization models, the optimal utilization rate of the energy storage cluster operation scheme solved by the energy storage cluster utilization rate optimization model is further substituted into the power market clearing model to obtain the optimal cost of the energy storage cluster operation scheme under the influence of the power market clearing, and then the optimal cost of the energy storage cluster operation scheme is substituted into the energy storage cluster utilization rate optimization model for repeated iteration and solving. As can be seen, in the above solving process, the two models need to be calculated repeatedly, and the calculation efficiency is not high. Therefore, the KKT condition is applied to further process the above double-layer model, the power market clearing model can be converted into an additional constraint of the energy storage cluster utilization rate optimization model, so as to convert the double-layer model into a single-layer model for solving, and the solving efficiency is improved.

[0089] Preferably, with reference to FIG. 2, in some embodiments of the present application, the specific steps of coupling the energy storage cluster utilization rate optimization model and the power market clearing model through the KKT condition can be performed by the following preferred implementation (wherein the upper model in FIG. 2 refers to the energy storage cluster utilization rate optimization model described in the embodiments of the present application; the lower clearing model or the lower model refers to the power market clearing model described in the embodiments of the present application):

[0090] S241: first-order partial derivatives of the decision variables in the Lagrange function of the power market clearing model are calculated to obtain the following additional equality constraints:

[0091] S242: the KKT condition is applied to the power market clearing model to obtain the following additional complementary constraints:

[0092] S243: the optimization objective function in S211 is taken as the optimization objective function of the energy storage cluster operation regulation model, and combined with the constraints in S241 to S242, the constraints in S212, and the power grid operation balance constraints and system frequency regulation demand constraints in S222, to construct the energy storage cluster operation regulation model.

[0093] In the above formulas of S241 to S242, ψ line (i) represents a set of nodes connected to node i; represents a set of all branches with node i as the first end node; represents a set of all branches with node i as the last end node; x ij and x ji are the reactances of lines L ij and L ji , respectively.

[0094] Further, the above complementary constraint condition is converted into a linear constraint by a large M constraint method, and a specific example is shown in the constraint condition of FIG. 2 After being processed by the large M method, the constraint condition is specifically as follows:

[0095] wherein M is a very large number; and v is a 0-1 variable.

[0096] S30: solving the energy storage cluster operation regulation model to obtain an optimal energy storage cluster operation scheme, and setting the charging and discharging power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each time period according to the optimal energy storage cluster operation scheme.

[0097] Preferably, in some embodiments of the present application, the optimal energy storage cluster operation scheme can also be used to provide a reference for the declaration of the charging and discharging power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each time period.

[0098] Preferably, in some embodiments of the present application, the energy storage cluster operation regulation model can be solved by a commercial solver.

[0099] In summary, it can be seen that the energy storage cluster operation regulation method considering market clearing provided by the embodiments of the present application has the following beneficial effects:

[0100] In constructing the energy storage cluster operation regulation model, the application scenario of the large-scale energy storage cluster is clarified, the utilization rate of each energy storage power station in the energy storage cluster and the allocation of the energy storage cluster and the thermal power unit energy and frequency modulation capacity are fully considered, the utilization rate of each energy storage power station is improved while meeting the requirements of power market clearing. At the same time, different energy storage power stations are unified in the form of energy storage clusters to participate in power market clearing, which reduces the calculation complexity of the market clearing model. In addition, by combining the historical load data, the thermal power unit operation parameters and the energy storage cluster operation parameters, and through the energy storage cluster operation regulation method considering market clearing provided by the present application, the application scenario of the independent energy storage power station participating in the power market can be simulated and operated, which can provide a reference for the operation scheme of the energy storage and the declaration strategy of participating in the power market, thereby improving the utilization rate of the independent energy storage power station and the calculation efficiency of the market clearing, and making the optimal energy storage cluster operation scheme obtained more close to the actual operation environment.

[0101] Embodiment Two

[0102] Referring to FIG. 3, the energy storage cluster operation regulation device provided by the embodiments of the present application includes a first data pre-acquisition module 11, a model initialization module 12 and a scheme acquisition module 13.

[0103] In some embodiments of the present application, the first data pre-acquisition module 11 is configured to acquire power plant operation parameters, energy storage cluster operation parameters and power grid historical load data respectively, and predict power grid load data of a next complete operation period according to the power grid historical load data; the model initialization module 12 is configured to initialize a preset energy storage cluster operation control model according to the predicted power grid load data, the power plant operation parameters and the energy storage cluster operation parameters; the energy storage cluster operation control model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model; the energy storage cluster utilization optimization model is obtained by optimizing energy storage cluster utilization; and the power market clearing model is obtained by optimizing allocation of energy capacity and frequency modulation capacity of the power plant and the energy storage cluster; and the scheme acquisition module 13 is configured to solve the energy storage cluster operation control model, acquire an optimal energy storage cluster operation scheme, and set charge-discharge power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each period according to the optimal energy storage cluster operation scheme.

[0104] Preferably, in some embodiments of the present application, the optimal energy storage cluster operation scheme can also be used to provide a reference for declaration of charge-discharge power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each period.

[0105] In some embodiments of the present application, the energy storage cluster operation control model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model, including: first-order partial derivatives of each decision variable of a Lagrange function of the power market clearing model are calculated to obtain additional equality constraints; the KKT condition is applied to the power market clearing model to obtain additional complementary constraints; and the energy storage cluster operation control model is obtained in combination with the energy storage cluster utilization optimization model and the additional equality constraints and the additional complementary constraints.

[0106] In some embodiments of the present application, the energy storage cluster utilization optimization model is obtained by optimizing energy storage cluster utilization, including: a first optimization objective function is constructed by combining frequency modulation amount of the energy storage cluster and frequency modulation capacity cost of the energy storage cluster; a first constraint is constructed by combining energy storage cluster operation constraints and energy capacity cost, frequency modulation capacity and frequency modulation mileage cost constraints of the energy storage cluster; and the energy storage cluster utilization optimization model is obtained in combination with the first optimization objective function and the first constraint.

[0107] In some embodiments of the present application, the first optimization objective function is constructed by combining frequency modulation amount of the energy storage cluster and frequency modulation capacity cost of the energy storage cluster, including:

[0108] The first optimization objective function is specifically:

[0109] wherein λ t , and are the energy market, frequency regulation capacity and frequency regulation mileage clearing price of period t, respectively; and are the bid charging and discharging power of energy storage power station j in period t, respectively; is the bid frequency regulation capacity of energy storage power station j in period t;S es,j is the frequency regulation mileage factor of energy storage power station j.

[0110] In some embodiments of the present application, the first constraint is constructed by combining the energy storage cluster operation constraint and the energy storage cluster energy cost, frequency regulation capacity and frequency regulation mileage cost constraint, comprising:

[0111] The energy storage cluster operation constraint is specifically:

[0112] The energy storage cluster energy cost, frequency regulation capacity and frequency regulation mileage cost constraint is specifically:

[0113] wherein and are the bid charging and discharging power of energy storage power station j in period t, respectively; and are the maximum charging and discharging power of energy storage power station j in period t, respectively; and are the bid frequency regulation capacity and frequency regulation mileage of energy storage power station j in period t, respectively; and are the maximum frequency regulation capacity and mileage of energy storage power station j in period t, respectively;S es,j is the frequency regulation mileage factor of energy storage power station j;E es,j,t is the energy value of energy storage power station j in period t; and are the charging and discharging efficiency of energy storage power station j, respectively; and are the initial energy and final energy value of energy storage power station j, respectively; and are the charging and discharging cost of energy storage power station j in period t, respectively; and are the maximum charging and discharging cost of energy storage power station j in period t, respectively; and are the frequency regulation capacity cost and frequency regulation mileage cost of energy storage power station j in period t, respectively; and are the maximum frequency regulation capacity cost and frequency regulation mileage cost of energy storage power station j in period t, respectively. a dual variable corresponding to the constraint.

[0114] In some embodiments of the application, the power market clearing model is obtained by optimizing the allocation of the electric energy and frequency modulation capacity of the thermal power unit and the energy storage cluster, comprising: constructing a second optimization objective function by combining the allocation of the electric energy and frequency modulation capacity of the thermal power unit and the energy storage cluster; constructing a second constraint by combining the energy storage cluster operation constraint, the power grid operation balance constraint, the thermal power unit operation constraint and the system frequency modulation demand constraint; and obtaining the power market clearing model by combining the second optimization objective function and the second constraint.

[0115] In some embodiments of the application, the second optimization objective function is constructed by combining the allocation of the electric energy and frequency modulation capacity of the thermal power unit and the energy storage cluster, comprising:

[0116] The second optimization objective function is specifically:

[0117] Wherein, price g,i,t is the generation cost of the thermal power unit i in the time period t; P g,i,t is the winning generation capacity of the thermal power unit i in the time period t; and are the charging and discharging costs of the energy storage power station j in the time period t, respectively; and are the winning charging and discharging power of the energy storage power station j in the time period t, respectively; and are the frequency modulation capacity costs of the thermal power unit i and the energy storage power station j in the time period t, respectively; and are the frequency modulation mileage costs of the thermal power unit i and the energy storage power station j, respectively; S g,i and S es,j are the frequency modulation mileage factors of the thermal power unit i and the energy storage power station j, respectively; and are the winning frequency modulation capacities of the thermal power unit i and the energy storage power station j in the time period t, respectively.

[0118] In some embodiments of the application, the second constraint is constructed by combining the energy storage cluster operation constraint, the power grid operation balance constraint, the thermal power unit operation constraint and the system frequency modulation demand constraint, comprising:

[0119] The energy storage cluster operation constraint is specifically the energy storage cluster utilization optimization model in the above-mentioned embodiments;

[0120] The power grid operation balance constraint is specifically:

[0121] The thermal power unit operation constraints, specifically:

[0122] The system frequency regulation demand constraints, specifically:

[0123] Wherein ψ g (b), ψ es (b), ψ load (b) respectively represent the set of thermal power units, energy storage power stations and loads located at node b; P g,i,t is the winning generation capacity of thermal power unit i in time period t; and are respectively the winning charge-discharge power of energy storage power station j in time period t; represents the set of branches connected to node b; P L,t is the power flowing into node b of line L at time t; P D,t is the power of load D; λ t , and are respectively the clearing price of electricity market, frequency regulation capacity and frequency regulation mileage in time period t, which are also the dual variables corresponding to the constraint conditions; is the maximum power of line transmission; P Lij,t is the transmission power of line L ij at time t; θ i,t and θ j,t are the phase angles at both ends of line L ij in time period t; x ij is the reactance of line L ij ; represents the set of branches connected to node i; and are respectively the minimum output and maximum output of thermal power unit i in time period t; and are respectively the winning frequency regulation capacity and frequency regulation mileage of thermal power unit i in time period t; and are respectively the maximum frequency regulation capacity and maximum frequency regulation mileage of thermal power unit i in time period t; S g,i is the frequency regulation mileage factor of thermal power unit i; and are respectively the frequency regulation capacity demand and frequency regulation mileage demand of the system in time period t; is the dual variable corresponding to the constraint condition.

[0124] In summary, it can be seen that the energy storage cluster operation regulation device considering market clearing provided by the embodiment has the following beneficial effects: when the energy storage cluster operation regulation model is constructed, the application scenarios of the large-scale energy storage cluster are determined, the utilization rates of the energy storage power stations in the energy storage cluster and the allocation of the electric energy and frequency modulation capacity of the energy storage cluster and the thermal power unit are fully considered, the utilization rates of the energy storage power stations are improved while meeting the requirements of the power market clearing, different energy storage power stations are unified in the form of the energy storage cluster to participate in the power market clearing, the calculation complexity of the market clearing model is reduced, in addition, the energy storage cluster operation regulation method considering market clearing is combined with the historical load data, the thermal power unit operation parameters and the energy storage cluster operation parameters, the application scenarios containing the independent energy storage power station participating in the power market can be simulated and operated, the operation scheme of the energy storage and the declaration strategy of participating in the power market can be provided as a reference, thereby the utilization rate of the independent energy storage power station and the calculation efficiency of the market clearing are improved, and the optimal energy storage cluster operation scheme obtained finally is closer to the actual operation environment.

[0125] Embodiment three

[0126] On the basis of the above-mentioned embodiment of the energy storage cluster operation regulation method considering market clearing, another embodiment of the present application provides an energy storage cluster operation regulation terminal device considering market clearing. The energy storage cluster operation regulation terminal device considering market clearing comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor. When the computer program is executed by the processor, the energy storage cluster operation regulation method considering market clearing of any embodiment of the present application is realized.

[0127] For example, in this embodiment, the computer program can be divided into one or more modules stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the energy storage cluster operation regulation device considering market clearing.

[0128] The energy storage cluster operation regulation device considering market clearing can be a desktop computer, a notebook computer, a palm computer and a cloud server, etc. The energy storage cluster operation regulation terminal device considering market clearing can include, but is not limited to, a processor and a memory.

[0129] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The processor is a control center of the energy storage cluster operation regulation device considering market clearing, and connects various parts of the energy storage cluster operation regulation device considering market clearing through various interfaces and lines. The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the energy storage cluster operation regulation device considering market clearing by running or executing the computer program and / or modules stored in the memory, and calling 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 by a function, etc.; and the data storage area can store data created according to use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0130] Embodiment Four

[0131] On the basis of the above-mentioned embodiments of the energy storage cluster operation regulation method considering market clearing, another embodiment of the present application provides a storage medium including a stored computer program, wherein when the computer program runs, the device where the storage medium is located executes the energy storage cluster operation regulation method considering market clearing of any one of the embodiments of the present application.

[0132] In this embodiment, the storage medium described above is a computer readable storage medium, the computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0133] The specific embodiments described above further illustrate the purposes, technical solutions and beneficial effects of the present application. It should be understood that the above description is only for specific embodiments of the present application and is not intended to limit the protection scope of the present application. It is particularly pointed out that any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for operating and regulating an energy storage cluster considering market clearing, characterized in that, The method comprises the following steps: obtaining the operation parameters of the thermal power unit, the operation parameters of the energy storage cluster and the historical load data of the power grid, and predicting the load data of the power grid in the next complete operation period according to the historical load data of the power grid; initializing a preset energy storage cluster operation control model according to the predicted load data of the power grid, the operation parameters of the thermal power unit and the operation parameters of the energy storage cluster; the energy storage cluster operation control model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model; the energy storage cluster utilization optimization model is obtained by optimizing the utilization of the energy storage cluster; and the power market clearing model is obtained by optimizing the distribution of the energy and frequency modulation capacity of the thermal power unit and the energy storage cluster; solving the energy storage cluster operation control model to obtain an optimal energy storage cluster operation scheme, and setting the charging and discharging power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each time period according to the optimal energy storage cluster operation scheme. 2.The method of claim 1, wherein, The energy storage cluster operation control model is obtained by coupling an energy storage cluster utilization optimization model and a power market clearing model, comprising: taking the first-order partial derivative of each decision variable of the Lagrange function of the power market clearing model to obtain additional equality constraints; applying the KKT condition to the power market clearing model to obtain additional complementary constraints; combining the energy storage cluster utilization optimization model and the additional equality constraints and the additional complementary constraints to obtain the energy storage cluster operation control model. 3.The method of claim 1, wherein, The energy storage cluster utilization optimization model is obtained by optimizing the utilization of the energy storage cluster, comprising: constructing a first optimization objective function by combining the charging and discharging power, frequency modulation capacity and power market clearing price of the energy storage cluster; constructing a first constraint by combining the energy storage cluster operation constraint and the energy storage cluster energy cost, frequency modulation capacity and frequency modulation mileage cost; combining the first optimization objective function and the first constraint to obtain the energy storage cluster utilization optimization model. 4.The method of claim 3, wherein, Constructing a first optimization objective function by combining the charging and discharging power, frequency modulation capacity and power market clearing price of the energy storage cluster, comprising: The first optimization objective function, in particular: wherein λ t 、 and respectively, are the spot market price, the frequency regulation capacity and the frequency regulation mileage clearing price at time period t; and Pj(t) is the target charging / discharging power of the energy storage power station j in the time period t; and S is the frequency regulation capacity of the energy storage plant j for the time period t; S es,j S is the frequency regulation mileage factor of the energy storage plant j.

5. The method of claim 3, wherein the market clearing is considered. constructing a first constraint by combining the energy storage cluster operation constraint and the energy storage cluster energy cost, frequency modulation capacity and frequency modulation mileage cost, comprising: The energy storage cluster operation constraint is specifically: The energy storage cluster electric energy cost, frequency modulation capacity and frequency modulation mileage cost constraints, in particular, are: wherein, and Pj(t) is the target charging / discharging power of the energy storage power station j in the time period t; and and Pmaxj(t) is the maximum charge-discharge power of the energy storage power station j at time period t, respectively; and respectively, are the target frequency modulation capacity and frequency modulation mileage in the energy storage power station j at time period t; and respectively the maximum frequency regulation capacity and the mileage of the energy storage power plant j at time period t; S es,j is the frequency regulation mileage factor of the energy storage power plant j; E es,j,t is the energy value of the energy storage power plant j at time period t; and charging and discharging efficiency of the energy storage power station j, respectively; and respectively the initial and final energy values of the energy storage plant j; and respectively the charging and discharging cost of the energy storage power plant j at time period t; and respectively the maximum charging and discharging cost of the energy storage power plant j at time period t; and respectively the frequency regulation capacity cost and the frequency regulation mileage cost of the energy storage power station j at time period t; and respectively the maximum frequency regulation capacity cost and the frequency regulation mileage cost of the energy storage power station j at time period t; a dual variable corresponding to the constraint condition.

6. The method of claim 1, wherein, The power market clearing model is obtained by optimizing the distribution of the energy and frequency modulation capacity of the thermal power unit and the energy storage cluster, comprising: constructing a second optimization objective function by combining the energy and frequency modulation capacity distribution of the thermal power unit and the energy storage cluster; constructing a second constraint by combining the energy storage cluster operation constraint, the power grid operation balance constraint, the thermal power unit operation constraint and the system frequency modulation demand constraint; combining the second optimization objective function and the second constraint to obtain the power market clearing model.

7. The method of claim 6, wherein the market clearing is considered. Constructing a second optimization objective function by combining the energy and frequency modulation capacity distribution of the thermal power unit and the energy storage cluster, comprising: The second optimization objective function, in particular: wherein price g,i,t is the generation cost of the thermal power unit i in the time period t; P g,i,t is the winning generation of the thermal power unit i in the time period t; and respectively the charging and discharging cost of the energy storage power plant j at time period t; and Pj(t) is the target charging / discharging power of the energy storage power station j in the time period t; and and respectively the frequency modulation capacity cost of the thermal power unit i and the energy storage power station j at time period t; and The frequency modulation mileage cost of the thermal power unit i and the energy storage power station j; S g,i and S es,j The frequency modulation mileage factor of the thermal power unit i and the energy storage power station j, respectively; and the winning frequency modulation capacity of the thermal power unit i and the energy storage power station j in time period t, respectively. 8.The method of claim 6, wherein, The second constraint is constructed by combining the energy storage cluster operation constraint, the power grid operation balance constraint, the thermal power unit operation constraint, and the system frequency modulation demand constraint, and comprises: The energy storage cluster operation constraint is specifically: The power grid operation balance constraint, in particular, is: The thermal power generating unit operation constraint, in particular is: The system adjusts the frequency demand constraint, specifically: wherein and These represent the charging and discharging power of the energy storage power station j, which is awarded in time period t. and Pmaxj(t) is the maximum charge-discharge power of the energy storage power station j at time period t, respectively; and respectively, are the target frequency modulation capacity and frequency modulation mileage in the energy storage power station j at time period t; and respectively the maximum frequency regulation capacity and the mileage of the energy storage power plant j at time period t; S es,j is the frequency regulation mileage factor of the energy storage power plant j; E es,j,t is the energy value of the energy storage power plant j at time period t; and charging and discharging efficiency of the energy storage power station j, respectively; and respectively the initial and final energy values of the energy storage power station j; ψ g (b), ψ es (b), ψ load (b) respectively represent the set of thermal power units, energy storage power stations and loads located at node b; P g,i,t is the winning generation of thermal power unit i in time period t; denotes the set of branches connected to node b; P L,t is the power flowing into node b at time t; P D,t is the power of load D; λ t 、 and are the clearing prices of the period t electricity energy market, the frequency regulation capacity and the frequency regulation mileage, respectively, and are the dual variables corresponding to the constraints; P represents the maximum power transmitted through the line. Lij,t For time t, line L ij The transmission power; θ i,t and θ j,t For time period t, line L ij Phase angle at both ends; x ij For line L ij The reactance; denotes the set of branches connected to node i; and respectively the minimum and maximum output of the thermal power unit i at time period t; and the bid frequency modulation capacity and frequency modulation mileage of the thermal power generating unit i for the time period t; and respectively the maximum frequency modulation capacity and the maximum frequency modulation mileage of the thermal power unit i; S g,i frequency modulation mileage factor of the thermal power unit i; and respectively the frequency modulation capacity requirement and the frequency modulation mileage requirement of the time period t system; A dual variable corresponding to the constraint condition.

9. A device for regulating operation of an energy storage cluster taking into account market clearing, characterized in that, Comprise: A first data pre-acquisition module, a model initialization module, and a scheme acquisition module; The first data pre-acquisition module is configured to acquire thermal power unit operation parameters, energy storage cluster operation parameters, and power grid historical load data respectively, and predict power grid load data of a next complete operation period according to the power grid historical load data; The model initialization module is configured to initialize a preset energy storage cluster operation regulation and control model according to the predicted power grid load data, the thermal power unit operation parameters, and the energy storage cluster operation parameters; the energy storage cluster operation regulation and control model is obtained by coupling an energy storage cluster utilization rate optimization model and a power market clearing model; the energy storage cluster utilization rate optimization model is obtained by optimizing energy storage cluster utilization rate; and the power market clearing model is obtained by optimizing allocation of energy and frequency modulation capacity of the thermal power unit and the energy storage cluster; The scheme acquisition module is configured to solve the energy storage cluster operation regulation and control model, acquire an optimal energy storage cluster operation scheme, and set charge and discharge power and frequency modulation capacity of each energy storage power station in the energy storage cluster in each time period according to the optimal energy storage cluster operation scheme. 10.The device of claim 9, wherein, The energy storage cluster operation regulation and control model is obtained by coupling an energy storage cluster utilization rate optimization model and a power market clearing model, and comprises: First-order partial derivatives of each decision variable of a Lagrange function of the power market clearing model are calculated to obtain additional equality constraints; The KKT condition is applied to the power market clearing model to obtain additional complementary constraints; The energy storage cluster operation regulation and control model is obtained by combining the energy storage cluster utilization rate optimization model and the additional equality constraints and the additional complementary constraints.

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