Energy storage capacity adequacy evaluation method, device, equipment and medium

Abstract

The invention provides an energy storage capacity adequacy assessment method, device, equipment and medium, and the method comprises the steps: constructing the capacity adequacy indexes of a high-proportion new energy power system, including a supply risk index, an economic benefit index and a flexible adjustment capability index, and calculating the energy storage capacity adequacy of the high-proportion new energy power system according to the capacity adequacy indexes; establishing an energy storage capacity adequacy value evaluation model by taking the minimum operation cost of the power system as an objective function; the energy storage investment and construction amount in the system is increased stage by stage, the marginal benefit and saturation effect of the energy storage capacity adequacy value of the system are considered, and the energy storage capacity adequacy value evaluation model is solved by taking the power abandoning constraint, the load loss constraint, the energy storage constraint, the thermal power generating unit constraint and the system operation constraint as constraint conditions, so that a configuration optimization result is obtained. According to the invention, marginal benefits and saturation benefits presented by adequacy values along with the change of the energy storage resource capacity are researched, so that the optimized layout of the energy storage resources is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid planning, and in particular to a method, device, equipment and medium for evaluating the adequacy of energy storage capacity. Background Art

[0002] In order to achieve optimal planning and reasonable allocation of energy storage resources, it is necessary to reasonably evaluate the capacity adequacy and value of energy storage. The existing energy storage adequacy evaluation methods can be roughly divided into three categories: direct method, indirect method and analytical evaluation method.

[0003] The direct evaluation method directly evaluates the application value of energy storage based on the proposed evaluation indicators. For example, based on the SMART principle of management, a comprehensive evaluation indicator system is proposed, including low-carbon indicators, safety and ample indicators, etc., and the applicability of the proposed indicators is verified by using the hierarchical analysis method with the central China region as the evaluation object. This type of method is essentially a sampling of capacity, and the capacity sampling method is relatively simple. It is usually a simple change in the energy storage capacity of a single node or a simple change in the charging and discharging time and other parameters of a fixed energy storage capacity. The research results have limited reference value for actual projects.

[0004] The indirect evaluation method is to indirectly consider the application value of energy storage when conducting research on energy storage capacity optimization and configuration. For example, when studying the two-layer optimization configuration method for the site selection and capacity of independent energy storage, the energy storage value under the planning result is indirectly evaluated through energy storage income, system power abandonment, etc. However, the indirect evaluation does not intuitively provide an evaluation indicator for the application value of energy storage. The result is the optimal energy storage capacity planning scheme, so it can only evaluate the application value of energy storage under this capacity scheme. The research results are difficult to migrate to other capacity configuration schemes and it is difficult to conduct a comparative analysis of the benefits of multiple capacity configuration schemes.

[0005] In addition, only a few existing technologies have proposed analytical evaluation methods. This method uses mathematical principles to make a relatively intuitive quantitative evaluation of the adequacy value of energy storage. For example, a method for evaluating the value of energy storage capacity based on parameter planning theory is proposed. Different energy storage configurations are divided into key areas to obtain linear expressions of the target application value in different key areas. Another example is that considering the uncertainty in a high-proportion new energy system, starting from the probability distribution, a system flexibility margin probability model is established to intuitively show the probability of insufficient flexibility in the system's upward / downward adjustment after the optimized configuration. The evaluation method based on parameter planning is a further study of the indirect evaluation method, and the analytical results of the application value with the power capacity (P) and energy capacity (E) of energy storage investment and construction as parameters are obtained. However, it is limited to connecting energy storage at a certain point. Multi-point access will greatly increase the complexity of the solution, making it difficult to obtain a reference conclusion; the evaluation method based on probability distribution combines the advantages of direct evaluation and brief evaluation, but the accuracy is overly dependent on the probability distribution function of flexibility supply and demand.

[0006] In view of this, there is an urgent need to provide an energy storage capacity adequacy assessment method that combines the advantages of the above three methods and can solve the corresponding problems. Summary of the invention

[0007] In order to overcome the problems existing in the related art, the present disclosure provides a method, device, equipment and medium for evaluating the adequacy of energy storage capacity to solve the technical problems in the related art.

[0008] One or more embodiments of this specification provide a method for evaluating energy storage capacity adequacy, including the following steps:

[0009] Construct capacity adequacy indicators for high-proportion new energy power systems, including supply risk indicators, economic benefit indicators and flexible adjustment capacity indicators; among them, the supply risk indicator is the expected loss value when the loss value caused by power shortage under the preset confidence exceeds the acceptable threshold when the system is operating at a specific energy storage investment; the economic benefit indicator is the marginal cost of power system operation when the system is operating at a specific energy storage investment; the flexible adjustment capacity indicator is the minimum value of the system adjustment capacity in each period when the system is operating at a specific energy storage investment level;

[0010] Based on the capacity adequacy index, a storage capacity adequacy value assessment model is established with the minimum power system operation cost as the objective function; and

[0011] The amount of energy storage investment in the system is increased stage by stage, and the marginal benefit and saturation effect of the system energy storage capacity adequacy value are considered. The energy storage capacity adequacy value evaluation model is solved with power abandonment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints as constraints to obtain the configuration optimization result, where the energy storage investment includes the investment energy capacity and the investment installed capacity.

[0012] Furthermore, the supply risk index, economic benefit index and flexible adjustment capability index are specifically as follows:

[0013] Supply risk indicators:

[0014] ER α (M)=E(y|y≥R α ) (1);

[0015] In the formula, ER α (M) is the expected loss value when the loss exceeds the threshold value when the confidence level α is set under the corresponding energy storage investment, M is the energy storage investment amount, R α is the acceptable loss threshold, y represents the loss caused by power shortage;

[0016] Economic benefit indicators:

[0017]

[0018] SW(M)=f(t,P t g ,P t re ,P t c ,P t d ,Ld t ) (3);

[0019] Where W(M) is the marginal operating cost of the power system, SW(M) is the corresponding power system operating cost under the energy storage investment M, is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, is the new energy output of the new energy unit k at time t, Ld i,t is the amount of lost load, and the power system operation cost calculation function f(·) represents the relationship between the operation cost and the output of each unit in the system;

[0020] Flexible adjustment capability indicators:

[0021] F M =min{F1 M ,F2 M ,...,F t M ,...,F T M} (4);

[0022] F t M =(P t cg +P t ce ) (5);

[0023] In the formula, F t M P is the flexible adjustment capability of the system at the time t and the amount of energy storage M. t cg is the sum of the adjustable capacities of all thermal power units in the system at time t, P t ce It is the sum of the adjustable capacities of all energy storage devices in the system at time t.

[0024] Furthermore, the objective function is specifically as follows:

[0025]

[0026] In the formula, FF represents the total cost of power system operation; the five terms on the right side of the equation represent the energy storage investment cost, the fuel cost of thermal power units, the energy storage operation and maintenance cost, the new energy curtailment cost and the load loss cost respectively; c f 、c s 、c re 、c d They are thermal power output, energy storage operation and maintenance, penalties for new energy power abandonment, and unit costs for load loss; is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, Ld is the new energy output of the new energy unit k at time t; i,t is the load loss at time t; To provide policy recommendations on the level of new energy consumption, is the maximum power generation capacity of the new energy unit at time t; r is the discount rate of funds, LC is the life cycle of the corresponding investment project, C E , C P They are the unit capacity cost and unit power cost of energy storage respectively. P e in They are respectively the energy capacity of energy storage node e in the current stage and the installed capacity of energy storage in the current stage.

[0027] Furthermore, the energy storage capacity in the system is increased stage by stage, and the specific increasing relationship of the energy storage investment between each stage is as follows:

[0028]

[0029] In the formula, is the energy capacity of energy storage that has been invested and constructed before the i+1th stage, The installed capacity of energy storage that has been built before the i+1th stage; and are the energy capacity of energy storage that has been built before the i-th stage and the energy capacity of energy storage planned to be built in the i-th stage, P i in0 and P i in They are respectively the installed capacity of energy storage that has been built before the i-th stage and the installed capacity of energy storage that is planned to be built in the i-th stage.

[0030] Furthermore, the model is solved using an optimization solver, and the solution is completed when the indicators show a stable saturation effect.

[0031] One or more embodiments of this specification provide a device for evaluating energy storage capacity adequacy, including:

[0032] The indicator construction module is used to construct the capacity adequacy index of the high-proportion new energy power system, including the supply risk index, the economic benefit index and the flexible adjustment capacity index; among which, the supply risk index is the expected loss value when the loss value caused by power shortage under the preset confidence exceeds the acceptable threshold when the system is operating under a specific energy storage investment; the economic benefit index is the marginal cost of the power system operation when the system is operating under a specific energy storage investment; the flexible adjustment capacity index is the minimum value of the system adjustment capacity in each time period when the system is operating under a specific energy storage investment level;

[0033] A model building module is used to establish an energy storage capacity adequacy value assessment model based on the capacity adequacy index and taking the minimum power system operation cost as the objective function; and

[0034] The multi-stage capacity configuration optimization module is used to gradually increase the amount of energy storage investment in the system, taking into account the marginal benefits and saturation effects of the system's energy storage capacity adequacy value, and solving the energy storage capacity adequacy value evaluation model under the conditions of power abandonment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints to obtain configuration optimization results.

[0035] Furthermore, the supply risk index, economic benefit index and flexible adjustment capability index are specifically as follows:

[0036] Supply risk indicators:

[0037] ER α (M)=E(y|y≥R α ) (9);

[0038] In the formula, ER α (M) is the expected loss value when the loss exceeds the threshold value when the confidence level α is set under the corresponding energy storage investment, M is the energy storage investment amount, R α is the acceptable loss threshold, y represents the loss caused by power shortage;

[0039] Economic benefit indicators:

[0040]

[0041] SW(M)=f(t,P t g ,P t re ,P t c ,P t d ,Ld t ) (11);

[0042] Where W(M) is the marginal operating cost of the power system, SW(M) is the corresponding power system operating cost under the energy storage investment M, is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, is the new energy output of the new energy unit k at time t, Ld i,t is the amount of lost load, and the power system operation cost calculation function f(·) represents the relationship between the operation cost and the output of each unit in the system;

[0043] Flexible adjustment capability indicators:

[0044] F M =min{F1 M ,F2 M ,...,F t M ,...,F T M} (12);

[0045] F t M =(P t cg +P t ce ) (13);

[0046] In the formula, F t M P is the flexible adjustment capability of the system at the time t and the amount of energy storage M. t cg is the sum of the adjustable capacities of all thermal power units in the system at time t, P t ce It is the sum of the adjustable capacities of all energy storage devices in the system at time t.

[0047] Furthermore, the objective function is specifically as follows:

[0048]

[0049] In the formula, FF represents the total cost of power system operation; the five terms on the right side of the equation represent the energy storage investment cost, the fuel cost of thermal power units, the energy storage operation and maintenance cost, the new energy curtailment cost and the load loss cost respectively; c f 、c s 、c re 、c d They are thermal power output, energy storage operation and maintenance, penalties for new energy power abandonment, and unit costs for load loss; is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, Ld is the new energy output of the new energy unit k at time t; i,t is the load loss at time t; To provide policy recommendations on the level of new energy consumption, is the maximum power generation capacity of the new energy unit at time t; r is the discount rate of funds, LC is the life cycle of the corresponding investment project, C E , C P They are the unit capacity cost and unit power cost of energy storage respectively. P e in They are respectively the energy capacity of energy storage node e in the current stage and the installed capacity of energy storage in the current stage.

[0050] Furthermore, the energy storage capacity in the system is increased stage by stage, and the specific increasing relationship of the energy storage investment between each stage is as follows:

[0051]

[0052] In the formula, is the energy capacity of energy storage that has been invested and constructed before the i+1th stage, The installed capacity of energy storage that has been built before the i+1th stage; and are the energy capacity of energy storage that has been built before the i-th stage and the energy capacity of energy storage planned to be built in the i-th stage, P i in0 and P i in They are respectively the installed capacity of energy storage that has been built before the i-th stage and the installed capacity of energy storage that is planned to be built in the i-th stage.

[0053] One or more embodiments of the present specification provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the energy storage capacity adequacy assessment method as described above when executing the computer program.

[0054] One or more embodiments of the present specification provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the energy storage capacity adequacy assessment method as described above is implemented.

[0055] The present disclosure provides a method, device, equipment and medium for evaluating the adequacy of energy storage capacity. The advantages are that the present disclosure considers the marginal benefit and saturation effect of system adequacy in the evaluation process of energy storage capacity adequacy. First, a capacity adequacy index is established that considers the safety, economy and flexibility requirements of a high-proportion new energy power system to quantify the value of energy storage adequacy. Based on the capacity adequacy index, an energy storage capacity adequacy value evaluation model is established with the minimum power system operating cost as the objective function. Then, the energy storage investment is accurately quantified, and the energy storage investment in the system is increased stage by stage. The marginal benefit and saturation effect of the system energy storage capacity adequacy value are considered to solve the model to evaluate the application value under various energy storage capacity planning schemes. The method of this embodiment studies the marginal benefit and saturation benefit presented by the adequacy value as the capacity of energy storage resources changes, so as to achieve the optimal layout of energy storage resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 A flow chart of a method for evaluating energy storage capacity adequacy provided for one or more embodiments of this specification;

[0058] Figure 2 A graph showing changes in supply risk indicators versus energy storage installed capacity for one or more embodiments of this specification;

[0059] Figure 3 A graph showing changes in economic benefit indicators with energy storage installed capacity for one or more embodiments of this specification;

[0060] Figure 4 A graph showing changes in the flexible adjustment capability index along with the energy storage installed capacity provided in one or more embodiments of this specification;

[0061] Figure 5 A block diagram of an energy storage capacity adequacy assessment device provided for one or more embodiments of this specification;

[0062] as well as

[0063] Figure 6 A schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0065] The present invention is described in detail below in conjunction with specific implementation methods and the accompanying drawings.

[0066] Method Embodiment

[0067] According to an embodiment of the present invention, a method for evaluating the adequacy of energy storage capacity is provided, taking into account the safety, economy, and flexibility requirements of a high-proportion new energy power system. Figure 1 As shown, it is a flow chart of the energy storage capacity adequacy evaluation method provided in this embodiment. The energy storage capacity adequacy evaluation method according to the embodiment of the present invention comprises the following steps:

[0068] Step S1, constructing a capacity adequacy index of a high-proportion new energy power system, including a supply risk index, an economic benefit index, and a flexible adjustment capability index; wherein the supply risk index is an expected loss value when the loss value caused by power shortage exceeds an acceptable threshold under a preset confidence level when the system is operating under a specific energy storage investment;

[0069] The economic benefit indicator is the marginal cost of power system operation when the system is operated at a specific amount of energy storage investment;

[0070] The flexible adjustment capability index is the minimum value of the system adjustment capability in each period when the system operates at a specific energy storage investment level. The system adjustment capability includes the sum of the adjustable capacity of all thermal power units and the sum of the adjustable capacity of all energy storage devices.

[0071] Step S2, based on the capacity adequacy index, a value assessment model for energy storage capacity adequacy is established with the minimum power system operating cost as the objective function.

[0072] Step S3, increasing the amount of energy storage investment in the system stage by stage, considering the marginal benefit and saturation effect of the system energy storage capacity adequacy value, and solving the energy storage capacity adequacy value evaluation model with power abandonment constraint, load loss constraint, energy storage constraint, thermal power unit constraint and system operation constraint as constraint conditions to obtain the configuration optimization result, wherein the energy storage investment includes the investment energy capacity and the investment installed capacity.

[0073] In step S3 of this embodiment, an optimization solver such as Gurobi is used to solve the model, and the iterative optimization process of the energy storage investment amount can be stopped when the indicator shows a stable saturation effect.

[0074] The energy storage capacity adequacy evaluation method provided in this embodiment considers the marginal benefit and saturation effect of system adequacy. First, a capacity adequacy index considering the safety, economy, and flexibility requirements of a high-proportion new energy power system is established to quantify the value of energy storage adequacy. Based on the capacity adequacy index, an energy storage capacity adequacy value evaluation model is established with the minimum power system operating cost as the objective function. Then, the energy storage investment is accurately quantified, and the energy storage investment in the system is increased stage by stage. The marginal benefit and saturation effect of the system energy storage capacity adequacy value are considered to solve the model, so as to realize the evaluation of the application value under various energy storage investment planning schemes. The method in this embodiment studies the marginal benefit and saturation benefit presented by the adequacy value as the energy storage resource capacity changes, so as to realize the optimal layout of energy storage resources.

[0075] In step S1 of this embodiment, the supply risk index, the economic benefit index and the flexible adjustment capability index are specifically expressed as follows.

[0076] The supply risk indicator is as follows:

[0077] ER α (M)=E(y|y≥R α ) (1);

[0078] Among them, ER α (M) is the expected loss value when the loss exceeds the threshold value when the confidence level α is set under the corresponding energy storage investment, M is the energy storage investment amount, R α is the acceptable loss threshold, and y represents the loss caused by insufficient power.

[0079] The economic benefit index is as follows:

[0080]

[0081] SW(M)=f(t,P t g ,P t re ,P t c ,P t d ,Ld t ) (3);

[0082] Among them, W(M) is the marginal operating cost of the power system, SW(M) is the corresponding power system operating cost under the energy storage investment M, is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, is the new energy output of the new energy unit k at time t, Ld i,t is the load loss, and the power system operation cost calculation function f(·) represents the relationship between the operation cost and the output of each unit in the system.

[0083] In this embodiment, the marginal operating cost of the power system is the difference between the power system operating costs in the two system operation simulation results after increasing the unit energy storage installed capacity under a specific energy storage investment, which is the marginal operating cost of the power system under this state.

[0084] The flexible adjustment capability index is as follows:

[0085] F M =min{F1 M ,F2 M ,...,F t M ,...,F T M} (4);

[0086] F t M =(P t cg +P t ce ) (5);

[0087] Among them, F is the flexible adjustment capability of the system when the amount of energy storage investment is M, F t M P is the flexible adjustment capability of the system when the energy storage investment is M at time t, t cg is the sum of the adjustable capacities of all thermal power units in the system at time t, P t ce It is the sum of the adjustable capacities of all energy storage devices in the system at time t.

[0088] In this embodiment, a value assessment model for energy storage capacity adequacy is established with the minimum power system operation cost as the objective function, including the objective function considering the total power system operation cost and the constraint conditions of the value assessment model;

[0089] Furthermore, the objective function is expressed as:

[0090]

[0091] Among them, FF represents the total cost of power system operation; the five terms on the right side of the equation represent the energy storage investment cost, the fuel cost of thermal power units, the energy storage operation and maintenance cost, the new energy power abandonment cost and the load loss cost respectively; c f 、cs 、c re 、c d They are thermal power output, energy storage operation and maintenance, penalties for new energy power abandonment, and unit costs for lost load; is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, Ld is the new energy output of the new energy unit k at time t; i,t is the load loss at time t; To provide policy recommendations on the level of new energy consumption, is the maximum power generation capacity of the new energy unit at time t;

[0092] In this embodiment, the investment cost of energy storage resources in the system is converted using the equal annual value method, where r is the discount rate of funds, LC is the life cycle of the corresponding investment project, and C E , C P They are the unit capacity cost and unit power cost of energy storage respectively. P e in They are respectively the energy capacity of energy storage planned to be built at the current stage of energy storage node e, the installed capacity of energy storage planned to be built at the current stage, and;

[0093] The constraints include power curtailment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints, as shown in the following formula.

[0094] Power curtailment constraints:

[0095] 0≤Ld i,t ≤L i,t (7);

[0096] Loss of load restraint:

[0097]

[0098] Energy storage constraints:

[0099]

[0100] Constraints on thermal power units:

[0101]

[0102]

[0103] System operation constraints:

[0104]

[0105] Among the above constraints, in formula (7-8), L i,t is the load of node i at time t, is the maximum output of the new energy unit k at time t, and the load loss constraint and power abandonment constraint limit the load loss and new energy power abandonment within a reasonable range;

[0106] Formula (9-11) is the energy storage investment constraint, and formula (12-17) is the energy storage operation constraint; where s e is a binary decision variable, used to represent whether to build energy storage at energy storage node e; are the maximum and minimum energy capacities allowed for energy storage node e; P e max , P e min are the maximum and minimum installed capacity allowed for energy storage node e respectively; P e in , P e in0 They are the energy capacity of energy storage planned to be built at the current stage of energy storage node e, the installed capacity of energy storage planned to be built at the current stage, the energy capacity of energy storage built at the previous stage, and the installed capacity of energy storage built at the previous stage; C max , C min They represent the maximum and minimum charge and discharge rates of energy storage, respectively, and are used to limit the relationship between the energy storage capacity and installed capacity of the corresponding node; E e,t is the amount of electricity stored in the energy storage node e at time t; is a 0 / 1 decision variable, which limits the energy storage charging and discharging to not be performed simultaneously; S max , S min are the upper and lower limits of energy storage charge state respectively; η c , η d are energy storage charging and discharging efficiency; S ini is the initial value of the energy storage charge state; They are respectively the energy storage charging power and discharging power of the energy storage node e at time t;

[0107] Formula (18-26) is the constraint of thermal power unit, among which formula (18-21) is the reserve constraint and unit output constraint, formula (22) is the upward and downward climbing constraint of thermal power unit, and formula (23-26) is the start-stop time constraint of thermal power unit; among which, fg j,t is the start and stop mark of the thermal power unit j at time t; is the upper and lower reserve of the thermal power unit j at time t; R is the maximum climbing capacity of the thermal power unit; are the minimum startup and shutdown time of thermal power unit j respectively; are the startup and shutdown time of thermal power unit j at time t respectively;

[0108] Formulas (27-30) are system operation constraints, where formula (27) is the node balance constraint expressed in the form of transfer distribution factor, formula (28) is the power flow safety constraint, and formula (29-30) is the system safety reserve constraint; where K G is the node-thermal power unit matrix, K L is the node-load matrix, K RE is the node-new energy matrix, K E is the node-energy storage matrix, SF is the node-branch association matrix, φ G ,φ D are the corresponding reserve ratio coefficients, which are used to limit the upper and lower reserves to the new energy power generation capacity and the upper and lower reserves to the load to meet a certain reserve ratio at time t.

[0109] In this embodiment, in the multi-stage power system operation simulation, the amount of energy storage investment in the system is increased stage by stage. For example, the expansion of energy storage investment is based on the energy storage optimization configuration result obtained by the power system simulation operation in the previous stage, and the expansion of energy storage investment in the next stage is further completed on the previous energy storage optimization configuration result. For example, assuming that there is energy storage in the power system before, which is scattered in multiple energy storage candidate nodes, with a total installed capacity of X megawatts, and the plan for phase i is to configure energy storage with a total installed capacity of A megawatts, at this time, the power system operation simulation will consider the impact of the energy storage with a total installed capacity of X megawatts on the grid flow, and further optimize the configuration of the energy storage with a total installed capacity of A megawatts in this stage.

[0110] The increasing relationship between energy storage investment and construction in each stage is as follows:

[0111]

[0112]

[0113] in, is the energy capacity of energy storage that has been invested and constructed before the i+1th stage, The installed capacity of energy storage that has been built before the i+1th stage; and are the energy capacity of energy storage that has been built before the i-th stage and the energy capacity of energy storage planned to be built in the i-th stage, P i in0 and P i in They are respectively the installed capacity of energy storage that has been built before the i-th stage and the installed capacity of energy storage that is planned to be built in the i-th stage.

[0114] The effectiveness and beneficial effects of the method of this embodiment are illustrated below through specific experimental cases.

[0115] This case uses the IEEE118 node system as the implementation environment. The system has a total of 54 thermal power units, connected to 5 wind farms, and 8 nodes to be configured with energy storage; the 5 wind farms are connected to nodes 4, 25, 31, 69, and 74 respectively; energy storage is to be configured at nodes 8, 30, 75, 76, 92, 93, 109, and 110; considering the uncertainty of both ends of the source and load, the reserve ratio is 6%;

[0116] In this case, the unit installed capacity cost of energy storage is 587,200 yuan / MW, and the unit capacity cost of energy storage is 200,000 yuan / MWh; the unit power generation cost of thermal power units is 400 yuan / MW, and the energy storage discharge cost (operation and maintenance cost) is 10 yuan / MW; the discount rate is 10%, and the life of energy storage equipment is 20 years; the maximum and minimum charging multiples C max , C min Take 1 and 1 / 3 respectively; the minimum, maximum and initial energy load state coefficient S of the energy storage system min , S max , S ini Take 0.1, 0.9, and 0.2 respectively; the maximum energy storage capacity allowed for the energy storage candidate node Minimum energy storage investment capacity Take 10000MWh and 3MWh respectively; allow the maximum and minimum energy storage installed capacity to be invested and constructed Take 10000MW and 1MW respectively. The charging and discharging efficiency is 0.89;

[0117] Assuming that there is no energy storage in the initial state of the system, a total installed capacity of 200MW of energy storage is planned to be configured in the power system operation simulation at each stage;

[0118] refer to Figure 2-4 As shown, Figure 2 The supply risk indicator for this case changes with the installed capacity of energy storage. Figure 3 The economic benefit index provided for this case changes with the energy storage installed capacity. Figure 4 A graph showing the change in the flexible adjustment capability index as a function of energy storage installed capacity provided for this case.

[0119] like Figure 2It can be determined that with the increase of the staged energy storage capacity adequacy, the expected loss shows an overall downward trend, indicating that energy storage has a positive effect on ensuring supply; the adequacy value of energy storage regarding supply risk presents a staged characteristic. In the process of increasing the energy storage investment capacity from 0MW to 800MW, the risk loss expectation decreases rapidly, and the marginal benefit reaches the maximum when the installed capacity is about 700MW. After the system energy storage installed capacity is greater than 1000MW, the marginal benefit is close to zero, showing the saturation effect of this risk indicator; when the energy storage installed capacity is 1000MW, the safety value of energy storage adequacy reaches initial saturation, at which time the energy storage installed capacity accounts for about 7.52%, and the expected risk loss is reduced by about 44.79%;

[0120] pass Figure 3 It can be seen that the marginal operating cost of the power system shows a downward trend with the increase of the system energy storage capacity adequacy, which proves that energy storage has certain economic benefits. When it forms a certain scale, it can play a positive role in reducing the system operating cost. Assuming that the marginal operating cost is greater than 0.1, the adequacy of energy storage capacity has good economic benefits for reducing the system operating cost. When the system energy storage installed capacity is less than 800MW, that is, before the energy storage installed capacity accounts for 6.11%, the adequacy of the energy storage system has good economic benefits. When the energy storage installed capacity is between 800MW and 1600MW, that is, when the energy storage installed capacity accounts for 6.11% to 11.52%, the economic value of the energy storage capacity adequacy is poor, but at this time, the increase in capacity adequacy can still reduce the marginal operating cost. When the energy storage installed capacity accounts for more than 11.52%, the marginal operating cost is less than 0, and further increase in energy storage capacity adequacy will increase the system operating cost.

[0121] like Figure 4 It can be seen that the regulation capacity shows a nearly linear growth trend with the increase of energy storage installed capacity, indicating that the sufficient capacity of energy storage in the system is beneficial to increasing the flexibility of the system. Overall, in this case, the system's downward regulation capacity is greater than the upward regulation capacity, and with the increase of energy storage installed capacity, the growth rate of the system's upward regulation capacity is less than the growth rate of the system's downward regulation capacity, that is, the marginal benefit of the upward regulation capacity is greater than the marginal benefit of the downward regulation capacity; the existing energy storage has a fast regulation speed. In the time scale of 1h, the working conditions of the energy storage in two adjacent time periods can be different, that is, the charging and discharging states can be flexibly switched in adjacent time scales. This characteristic is called bidirectional regulation. In multiple intervals, the increment of the system's flexible regulation capacity is greater than the increment of the installed capacity in the interval, reflecting its bidirectional regulation and efficient regulation capacity.

[0122] Through the above case experimental data, we can intuitively observe the influencing factors (supply risk, economic benefits, and flexible adjustment capabilities) considered in the energy storage capacity adequacy assessment method provided in this embodiment. In view of these factors, through the integration of pictures and data, the energy storage capacity adequacy value assessment model constructed in this embodiment enables system operators to make reasonable assessments of the capacity adequacy of energy storage in existing power systems, consider the various roles of energy storage in new power systems, and further provide an important basis for achieving optimal planning and reasonable allocation of energy storage resources.

[0123] Device Embodiment

[0124] According to an embodiment of the present invention, a device for evaluating the adequacy of energy storage capacity is provided. Figure 5 As shown, it is a block diagram of a test device for interval evacuation based on subway emergency failure provided in this embodiment. The device for monitoring, displaying and interactive optimization of complex scenes according to an embodiment of the present invention includes:

[0125] The indicator construction module 10 is used to construct the capacity adequacy index of the high-proportion new energy power system, including the supply risk index, the economic benefit index and the flexible adjustment capability index; wherein the supply risk index is the expected loss value when the loss value caused by power shortage exceeds the acceptable threshold under the preset confidence when the system is running under a specific energy storage investment amount;

[0126] The economic benefit indicator is the marginal cost of power system operation when the system is operated at a specific amount of energy storage investment;

[0127] The flexible adjustment capability index is the minimum value of the system adjustment capability in each period when the system operates at a specific energy storage investment level. The system adjustment capability includes the sum of the adjustable capacity of all thermal power units and the sum of the adjustable capacity of all energy storage devices.

[0128] The model building module 20 is used to establish an energy storage capacity adequacy value assessment model based on the capacity adequacy index and taking the minimization of the power system operation cost as the objective function.

[0129] The multi-stage capacity configuration optimization module 30 is used to increase the energy storage investment in the system stage by stage, taking into account the marginal benefits and saturation effects of the system energy storage capacity adequacy value, and solving the energy storage capacity adequacy value evaluation model under the conditions of power abandonment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints to obtain the configuration optimization result, wherein the energy storage investment includes the investment energy capacity and the investment installed capacity.

[0130] The energy storage capacity adequacy evaluation device provided in this embodiment takes into account the marginal benefit and saturation effect of system adequacy. First, the indicator construction module 10 establishes a capacity adequacy index that takes into account the safety, economy, and flexibility requirements of a high-proportion new energy power system to quantify the energy storage adequacy value. Based on the capacity adequacy index, the model construction module 20 establishes an energy storage capacity adequacy value evaluation model with the minimum power system operating cost as the objective function, and then accurately quantifies the energy storage investment. Finally, the multi-stage capacity configuration optimization module 30 increases the energy storage investment in the system stage by stage, and solves the model considering the marginal benefit and saturation effect of the system energy storage capacity adequacy value, so as to realize the evaluation of the application value under various energy storage investment planning schemes. The method of this embodiment studies the marginal benefit and saturation benefit presented by the adequacy value as the energy storage resource capacity changes, so as to realize the optimal layout of energy storage resources.

[0131] In this embodiment, the supply risk index, the economic benefit index and the flexible adjustment capability index are specifically expressed as follows.

[0132] The supply risk indicator is as follows:

[0133] ER α (M)=E(y|y≥R α ) (33);

[0134] Among them, ER α (M) is the expected loss value when the loss exceeds the threshold when the confidence level α is set under the corresponding energy storage investment, M is the energy storage investment amount, R α is the acceptable loss threshold, and y represents the loss caused by insufficient power.

[0135] The economic benefit index is as follows:

[0136]

[0137] SW(M)=f(t,P t g ,P t re ,P t c ,P t d ,Ld t ) (35);

[0138] Among them, W(M) is the marginal operating cost of the power system, SW(M) is the corresponding power system operating cost under the energy storage investment M, They are thermal power output, energy storage discharge and new energy output, Ld i,t is the load loss, and the power system operation cost calculation function f(·) represents the relationship between the operation cost and the output of each unit in the system.

[0139] In this embodiment, the marginal operating cost of the power system is the difference between the power system operating costs in the two system operation simulation results after increasing the unit energy storage installed capacity under a specific energy storage investment, which is the marginal operating cost of the power system under this state.

[0140] The flexible adjustment capability index is as follows:

[0141] F M =min{F1 M ,F2 M ,...,F t M ,...,F T M} (36);

[0142] F t M =(P t cg +P t ce ) (37);

[0143] Among them, F is the flexible adjustment capability of the system when the amount of energy storage investment is M, F t M P is the flexible adjustment capability of the system when the energy storage investment is M at time t, t cg is the sum of the adjustable capacities of all thermal power units in the system at time t, P t ce It is the sum of the adjustable capacities of all energy storage devices in the system at time t.

[0144] In this embodiment, the objective function is expressed as:

[0145]

[0146] Among them, FF represents the total cost of power system operation; the five terms on the right side of the equation represent the energy storage investment cost, the fuel cost of thermal power units, the energy storage operation and maintenance cost, the new energy power abandonment cost and the load loss cost respectively; c f 、c s 、c re 、c d They are thermal power output, energy storage operation and maintenance, penalties for new energy power abandonment, and unit costs for lost load; is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, Ld is the new energy output of the new energy unit k at time t; i,t is the load loss at time t; To provide policy recommendations on the level of new energy consumption, is the maximum power generation capacity of the new energy unit at time t;

[0147] In this embodiment, the investment cost of energy storage resources in the system is converted using the equal annual value method, where r is the discount rate of funds, LC is the life cycle of the corresponding investment project, and C E , C P They are the unit capacity cost and unit power cost of energy storage respectively. P e in They are respectively the energy capacity of energy storage planned to be built at the current stage of energy storage node e and the installed capacity of energy storage planned to be built at the current stage;

[0148] The constraints include power curtailment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints, as shown in the following formula.

[0149] Power curtailment constraints:

[0150] 0≤Ld i,t ≤L i,t (39);

[0151] Loss of load restraint:

[0152]

[0153] Energy storage constraints:

[0154]

[0155]

[0156] Constraints on thermal power units:

[0157]

[0158] System operation constraints:

[0159]

[0160]

[0161] Among the above constraints, in formula (39-40), L i,t is the load of node i at time t, is the maximum output of the new energy unit k at time t, and the load loss constraint and power abandonment constraint limit the load loss and new energy power abandonment within a reasonable range;

[0162] Formula (41-43) is the energy storage investment constraint, and formula (44-49) is the energy storage operation constraint; where s e is a binary decision variable, used to represent whether to build energy storage at energy storage node e; are the maximum and minimum energy capacities allowed for energy storage node e; P e max , P e min are the maximum and minimum installed capacity allowed for energy storage node e respectively; P e in , P e in0 They are the energy capacity of energy storage planned to be built at the current stage of energy storage node e, the installed capacity of energy storage planned to be built at the current stage, the energy capacity of energy storage built at the previous stage, and the installed capacity of energy storage built at the previous stage; C max , C min They represent the maximum and minimum charge and discharge rates of energy storage, respectively, and are used to limit the relationship between the energy storage capacity and installed capacity of the corresponding node; E e,t is the amount of electricity stored in the energy storage node e at time t; is a 0 / 1 decision variable, which limits the energy storage charging and discharging to not be performed simultaneously; S max , S min are the upper and lower limits of energy storage charge state respectively; η c , η d are energy storage charging and discharging efficiency; S ini is the initial value of the energy storage charge state; They are respectively the energy storage charging power and discharging power of the energy storage node e at time t;

[0163] Formula (50-58) is the constraint of thermal power unit, among which formula (50-53) is the reserve constraint and unit output constraint, formula (54) is the upward and downward climbing constraint of thermal power unit, and formula (55-58) is the start-stop time constraint of thermal power unit; among which, fg j,t is the start and stop mark of the thermal power unit j at time t; is the upper and lower reserve of the thermal power unit j at time t; R is the maximum climbing capacity of the thermal power unit; are the minimum startup and shutdown time of thermal power unit j respectively; are the startup and shutdown time of thermal power unit j at time t respectively;

[0164] Formulas (59-62) are system operation constraints, where formula (59) is the node balance constraint expressed in the form of transfer distribution factor, formula (60) is the power flow safety constraint, and formula (61-62) is the system safety reserve constraint; where K G is the node-thermal power unit matrix, K L is the node-load matrix, K RE is the node-new energy matrix, K E is the node-energy storage matrix, SF is the node-branch association matrix, φG ,φ D are the corresponding reserve ratio coefficients, which are used to limit the upper and lower reserves to the new energy power generation capacity and the upper and lower reserves to the load to meet a certain reserve ratio at time t.

[0165] In this embodiment, in the multi-stage power system operation simulation, the energy storage capacity in the system is increased stage by stage.

[0166] The increasing relationship between energy storage investment and construction in each stage is as follows:

[0167]

[0168] in, is the energy capacity of energy storage that has been invested and constructed before the i+1th stage, The installed capacity of energy storage that has been built before the i+1th stage; and are the energy capacity of energy storage that has been built before the i-th stage and the energy capacity of energy storage planned to be built in the i-th stage, P i in0 and P i in They are respectively the installed capacity of energy storage that has been built before the i-th stage and the installed capacity of energy storage that is planned to be built in the i-th stage.

[0169] The embodiment of the present invention is an apparatus embodiment corresponding to the above-mentioned method embodiment. The specific operations of the processing steps of each module can be understood by referring to the description of the method embodiment, which will not be repeated here.

[0170] like Figure 6 As shown, the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the energy storage capacity adequacy evaluation method in the above embodiment is implemented, or when the computer program is executed by a processor, the energy storage capacity adequacy evaluation method in the above embodiment is implemented. When the computer program is executed by the processor, the following method steps are implemented:

[0171] Step S1, constructing a capacity adequacy index of a high-proportion new energy power system, including a supply risk index, an economic benefit index, and a flexible adjustment capability index; wherein the supply risk index is an expected loss value when the loss value caused by power shortage exceeds an acceptable threshold under a preset confidence level when the system is operating under a specific energy storage investment;

[0172] The economic benefit indicator is the marginal cost of power system operation when the system is operated at a specific amount of energy storage investment;

[0173] The flexible adjustment capability index is the minimum value of the system adjustment capability in each period when the system operates at a specific energy storage investment level. The system adjustment capability includes the sum of the adjustable capacity of all thermal power units and the sum of the adjustable capacity of all energy storage devices.

[0174] Step S2, based on the capacity adequacy index, a value assessment model for energy storage capacity adequacy is established with the minimum power system operating cost as the objective function.

[0175] Step S3, increasing the amount of energy storage investment in the system stage by stage, considering the marginal benefit and saturation effect of the system energy storage capacity adequacy value, and solving the energy storage capacity adequacy value evaluation model with power abandonment constraint, load loss constraint, energy storage constraint, thermal power unit constraint and system operation constraint as constraint conditions to obtain the configuration optimization result, wherein the energy storage investment includes the investment energy capacity and the investment installed capacity.

[0176] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0177] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system 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. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0178] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for evaluating energy storage capacity adequacy, characterized in that The following steps are involved: Construct capacity adequacy indicators for high-proportion new energy power systems, including supply risk indicators, economic benefit indicators and flexible adjustment capacity indicators; among them, the supply risk indicator is the expected loss value when the loss value caused by power shortage under the preset confidence exceeds the acceptable threshold when the system is operating at a specific energy storage investment; the economic benefit indicator is the marginal cost of power system operation when the system is operating at a specific energy storage investment; the flexible adjustment capacity indicator is the minimum value of the system adjustment capacity in each period when the system is operating at a specific energy storage investment level; Based on the capacity adequacy index, a storage capacity adequacy value assessment model is established with the minimum power system operation cost as the objective function; and The amount of energy storage investment in the system is increased stage by stage, and the marginal benefit and saturation effect of the system energy storage capacity adequacy value are considered. The energy storage capacity adequacy value evaluation model is solved with power abandonment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints as constraints to obtain the configuration optimization result, where the energy storage investment includes the investment energy capacity and the investment installed capacity.

2. The method for evaluating energy storage capacity adequacy according to claim 1, characterized in that: The supply risk index, economic benefit index and flexible adjustment capability index are specifically as follows: Supply risk indicators: IS α (M)=E(y|y≥R α ) (1); In the formula, ER α (M) is the expected loss value when the loss exceeds the threshold when the confidence level α is set under the corresponding energy storage investment, M is the energy storage investment amount, R α is the acceptable loss threshold, y represents the loss caused by power shortage; Economic benefit indicators: SW(M)=f(t,P t g ,P t re ,P t c ,P t d ,Ld t ) (3); Where W(M) is the marginal operating cost of the power system, SW(M) is the corresponding power system operating cost under the energy storage investment M, is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, is the new energy output of the new energy unit k at time t, Ld i,t is the amount of lost load, and the power system operation cost calculation function f(·) represents the relationship between the operation cost and the output of each unit in the system; Flexible adjustment capability indicators: F M =min{F1 M ,F2 M ,...,F t M ,...,F T M } (4); F t M =(P t cg +P t ce ) (5); In the formula, F t M P is the flexible adjustment capability of the system at the time t and the amount of energy storage M. t cg is the sum of the adjustable capacities of all thermal power units in the system at time t, P t ce It is the sum of the adjustable capacities of all energy storage devices in the system at time t.

3. The method for evaluating energy storage capacity adequacy according to claim 1, characterized in that: The objective function is specifically as follows: In the formula, FF represents the total cost of power system operation; the five terms on the right side of the equation represent the energy storage investment cost, the fuel cost of thermal power units, the energy storage operation and maintenance cost, the new energy curtailment cost and the load loss cost respectively; c f 、c s 、c re 、c d They are thermal power output, energy storage operation and maintenance, penalties for new energy power abandonment, and unit costs for load loss; is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, Ld is the new energy output of the new energy unit k at time t; i,t is the load loss at time t; To provide policy recommendations on the level of new energy consumption, is the maximum power generation capacity of the new energy unit at time t; r is the discount rate of funds, LC is the life cycle of the corresponding investment project, C E , C P They are the unit capacity cost and unit power cost of energy storage respectively. They are respectively the energy capacity of energy storage node e in the current stage and the installed capacity of energy storage in the current stage.

4. The method for evaluating energy storage capacity adequacy according to claim 1, characterized in that: The energy storage capacity in the system is increased step by step. The increasing relationship of the energy storage investment in each stage is as follows: In the formula, is the energy capacity of energy storage that has been invested and constructed before the i+1th stage, The installed capacity of energy storage that has been built before the i+1th stage; and are the energy capacity of energy storage that has been built before the i-th stage and the energy capacity of energy storage planned to be built in the i-th stage, P i in0 and P i in They are respectively the installed capacity of energy storage that has been built before the i-th stage and the installed capacity of energy storage that is planned to be built in the i-th stage.

5. The method for evaluating energy storage capacity adequacy according to claim 1, characterized in that: The model is solved using an optimization solver and is solved when the indicators show a stable saturation effect.

6. A device for evaluating the adequacy of energy storage capacity, characterized in that include: The indicator construction module is used to construct the capacity adequacy index of the high-proportion new energy power system, including the supply risk index, the economic benefit index and the flexible adjustment capacity index; among which, the supply risk index is the expected loss value when the loss value caused by power shortage under the preset confidence exceeds the acceptable threshold when the system is operating under a specific energy storage investment; the economic benefit index is the marginal cost of the power system operation when the system is operating under a specific energy storage investment; the flexible adjustment capacity index is the minimum value of the system adjustment capacity in each time period when the system is operating under a specific energy storage investment level; A model building module is used to establish an energy storage capacity adequacy value assessment model based on the capacity adequacy index and taking the minimum power system operation cost as the objective function; and The multi-stage capacity configuration optimization module is used to gradually increase the amount of energy storage investment in the system, taking into account the marginal benefits and saturation effects of the system's energy storage capacity adequacy value, and solving the energy storage capacity adequacy value evaluation model under the conditions of power abandonment constraints, load loss constraints, energy storage constraints, thermal power unit constraints and system operation constraints to obtain configuration optimization results.

7. The energy storage capacity adequacy assessment device according to claim 6, characterized in that: The supply risk index, economic benefit index and flexible adjustment capability index are specifically as follows: Supply risk indicators: IS α (M)=E(y|y≥R α ) (9); In the formula, ER α (M) is the expected loss value when the loss exceeds the threshold when the confidence level α is set under the corresponding energy storage investment, M is the energy storage investment amount, R α is the acceptable loss threshold, y represents the loss caused by power shortage; Economic benefit indicators: SW(M)=f(t,P t g ,P t re ,P t c ,P t d ,Ld t ) (11); Where W(M) is the marginal operating cost of the power system, SW(M) is the corresponding power system operating cost under the energy storage investment M, is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, is the new energy output of the new energy unit k at time t, Ld i,t is the amount of lost load, and the power system operation cost calculation function f(·) represents the relationship between the operation cost and the output of each unit in the system; Flexible adjustment capability indicators: F M =min{F1 M ,F2 M ,...,F t M ,...,F T M } (12); F t M =(P t cg +P t ce ) (13); In the formula, F t M P is the flexible adjustment capability of the system at the time t and the amount of energy storage M. t cg is the sum of the adjustable capacities of all thermal power units in the system at time t, P t ce It is the sum of the adjustable capacities of all energy storage devices in the system at time t.

8. The energy storage capacity adequacy assessment device according to claim 6, characterized in that: The objective function is specifically as follows: In the formula, FF represents the total cost of power system operation; the five terms on the right side of the equation represent the energy storage investment cost, the fuel cost of thermal power units, the energy storage operation and maintenance cost, the new energy curtailment cost and the load loss cost respectively; c f 、c s 、c re 、c d They are thermal power output, energy storage operation and maintenance, penalties for new energy power abandonment, and unit costs for load loss; is the thermal power output of thermal power unit j at time t, is the energy storage discharge power of energy storage node e at time t, Ld is the new energy output of the new energy unit k at time t; i,t is the load loss at time t; To provide policy recommendations on the level of new energy consumption, is the maximum power generation capacity of the new energy unit at time t; r is the discount rate of funds, LC is the life cycle of the corresponding investment project, C E , C P They are the unit capacity cost and unit power cost of energy storage respectively. They are respectively the energy capacity of energy storage node e in the current stage and the installed capacity of energy storage in the current stage.

9. The energy storage capacity adequacy assessment device according to claim 6, characterized in that: The energy storage capacity in the system is increased step by step. The increasing relationship of the energy storage investment in each stage is as follows: In the formula, is the energy capacity of energy storage that has been invested and constructed before the i+1th stage, The installed capacity of energy storage that has been built before the i+1th stage; and are the energy capacity of energy storage that has been built before the i-th stage and the energy capacity of energy storage planned to be built in the i-th stage, P i in0 and P i in They are respectively the installed capacity of energy storage that has been built before the i-th stage and the installed capacity of energy storage that is planned to be built in the i-th stage.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the energy storage capacity adequacy assessment method according to any one of claims 1 to 5 is implemented.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the energy storage capacity adequacy assessment method according to any one of claims 1 to 5 is implemented.

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