Multi-element energy storage capacity configuration method and device

Abstract

The invention provides a multi-element energy storage capacity configuration method and device. The method comprises the steps that a multi-element energy storage configuration scheme is initialized; based on the system operation constraint optimization scheme; increasing the capacity of each energy storage type according to a fixed increment, and generating a plurality of schemes; calculating a net income increment according to green, safety, adjustability and economic indexes; calculating a net income micro-increasing rate; screening a net income micro-increasing rate gt; the maximum scheme is a new scheme; and repeatedly executing the optimization step until the energy storage capacity reaches the upper limit or the net income increment is less than or equal to 0, and outputting a new scheme. According to the method, the net income is calculated through multi-dimensional indexes, the energy storage capacity is gradually increased, complex calculation and characteristic loss are avoided, and screening of the optimal configuration scheme is achieved.

Description

Technical Field

[0001] This application belongs to the field of energy storage configuration, and particularly relates to a method and device for configuring the capacity of multiple energy storages. Background Art

[0002] With the large-scale access of renewable energy and the gradual opening of the power market, the power system's supply-demand balance faces unprecedented challenges. To ensure the stable operation of the power system and the efficient utilization of energy, energy storage technology, as an important regulatory means, is receiving increasing attention. However, there are various types of energy storage technologies, including lithium-ion batteries, sodium-sulfur batteries, compressed air energy storage, pumped-storage energy storage, etc. Each energy storage technology has its unique performance characteristics and economic costs. Therefore, how to reasonably configure the capacities of multiple energy storage technologies to optimize the greenness, safety, regulation, and economy of the system has become an important issue in the current power system planning field.

[0003] Traditional energy storage capacity configuration methods often only optimize for a single energy storage type, ignoring the complementarity and substitutability between multiple energy storage technologies. This method easily leads to unreasonable resource allocation and low efficiency. In addition, most existing configuration methods are based on static planning models and fail to fully consider the dynamic characteristics and uncertainty factors in the operation of the power system, thus affecting the practical feasibility and adaptability of the configuration scheme.

[0004] To overcome the above defects, the industry has begun to explore methods for configuring the capacity of multiple energy storages. This method comprehensively considers the performance characteristics and economic costs of multiple energy storage technologies, as well as the actual needs of the power system, aiming to maximize the overall benefits of the system by optimizing the configuration of energy storage capacity. However, existing methods for configuring the capacity of multiple energy storages still have certain limitations. For example, some methods are too complex and computationally intensive, making it difficult to apply in actual projects; while other methods are too simplistic and ignore important characteristics of the system, resulting in unreasonable configuration schemes. Summary of the Invention

[0005] The purpose of this application is to overcome the above defects in the prior art and provide a method and device for configuring the capacity of multiple energy storages.

[0006] This application provides a method for configuring the capacity of multiple energy storages, including:

[0007] S1 Initialize a configuration scheme for the capacity of multiple energy storages including multiple energy storage types;

[0008] S2 Optimize the configuration scheme for the capacity of multiple energy storages based on preset system operation constraint conditions;

[0009] S3 Increase the capacity of each energy storage type in the configuration scheme for the capacity of multiple energy storages by a fixed increment respectively to generate multiple configuration schemes;

[0010] S4 calculates the net income increment of each of the configuration schemes according to preset greenness indicators, safety indicators, regulatability indicators, and economic indicators;

[0011] S5 calculates the net income micro-increment rate of each configuration scheme according to the fixed increment and the net income increment;

[0012] S6 screens out the configuration scheme with the net income micro-increment rate > 0 and the largest net income micro-increment rate, and sets this configuration scheme as the new configuration scheme;

[0013] S7 repeats steps S2 to S6 for the new configuration scheme until the energy storage capacity of each energy storage type reaches the planned upper limit or the net income increment ≤ 0, and outputs the new configuration scheme.

[0014] Optionally, initializing a multi-energy storage capacity configuration scheme including multiple energy storage types includes:

[0015] Setting the upper and lower limits of the power of the conventional unit and the new energy unit, and giving the upper and lower limits of the energy storage capacity configuration.

[0016] Optionally, the fixed increment is preset according to system requirements and the technical characteristics of the energy storage type.

[0017] Optionally, the greenness indicators include: the reduced curtailment penalty cost of wind and light and the income from the reduced carbon emissions.

[0018] Optionally, the safety indicators include: the income brought by the enhanced system power supply guarantee ability caused by the newly added energy storage.

[0019] Optionally, the regulatability indicators include: the income brought by reducing the utilization hours of coal-fired units and the income brought by reducing the over-limit of the cross-river section tidal current.

[0020] Optionally, the economic indicators include: the income brought by the newly added energy storage to the system.

[0021] Optionally, the system operation constraint conditions include: system power balance constraint, reserve capacity constraint, conventional unit operation constraint, new energy output constraint, line capacity constraint, and energy storage operation constraint.

[0022] This application also provides a multi-energy storage capacity configuration device, including:

[0023] An initialization module that initializes a multi-energy storage capacity configuration scheme including multiple energy storage types;

[0024] An optimization module that optimizes the multi-energy storage capacity configuration scheme based on preset system operation constraint conditions;

[0025] Configuration module, which increases the capacity of each energy storage type in the diversified energy storage capacity configuration plan by a fixed increment respectively to generate multiple configuration plans;

[0026] Benefit module, which calculates the net benefit increment of each of the configuration plans according to the preset greenness index, safety index, regulation index and economic index;

[0027] Increment rate module, which calculates the net benefit increment rate of each configuration plan according to the fixed increment and the net benefit increment;

[0028] Screening module, which screens the configuration plan with the net benefit increment rate > 0 and the maximum net benefit increment rate, and sets this configuration plan as the new configuration plan;

[0029] Circular output module, which repeats the new configuration plan in steps S2 - S6 until the energy storage capacity of each energy storage type reaches the planned upper limit or the net benefit increment ≤ 0, and outputs the new configuration plan.

[0030] Optionally, the system operation constraint conditions include: system power balance constraint, reserve capacity constraint, conventional unit operation constraint, new energy output constraint, line capacity constraint and energy storage operation constraint.

[0031] The beneficial effects of this application are:

[0032] This application provides a method for configuring diversified energy storage capacity, including: S1 initializing a diversified energy storage capacity configuration plan including multiple energy storage types; S2 optimizing the diversified energy storage capacity configuration plan based on the preset system operation constraint conditions; S3 increasing the capacity of each energy storage type in the diversified energy storage capacity configuration plan by a fixed increment respectively to generate multiple configuration plans; S4 calculating the net benefit increment of each configuration plan according to the preset greenness index, safety index, regulation index and economic index; S5 calculating the net benefit increment rate of each configuration plan according to the fixed increment and the net benefit increment; S6 screening the configuration plan with the net benefit increment rate > 0 and the maximum net benefit increment rate, and setting this configuration plan as the new configuration plan; S7 repeating the new configuration plan in steps S2 - S6 until the energy storage capacity of each energy storage type reaches the planned upper limit or the net benefit increment ≤ 0, and outputting the new configuration plan. This application calculates the net benefit increment and the net benefit increment rate according to the preset multi - dimensional indexes, so as to screen out the optimal configuration plan. By gradually increasing the capacity of each energy storage type, complex calculations and characteristic losses are avoided. Description of the Drawings

[0033] Figure 1 is the schematic diagram of the diversified energy storage capacity configuration process in this application;

[0034] Figure 2 It is a schematic diagram of configuring the upper and lower layer relationships of the model in this application;

[0035] Figure 3 It is a schematic diagram of a multi - energy storage capacity configuration device in this application. Detailed implementation manners

[0036] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, the described embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0037] Multi - energy storage capacity configuration refers to the process of determining the energy storage capacity of various energy storage devices (such as supercapacitors, batteries, compressed air energy storage systems, heat storage tanks, cold storage tanks, etc.) in a multi - energy storage system according to actual needs and application scenarios. This process aims to ensure that the system can provide sufficient power or other forms of energy supply when needed, while considering economy, reliability, and efficiency.

[0038] The main technical problem to be solved in this application is how to configure the multi - energy storage capacity economically and efficiently.

[0039] Please refer to Figures 1 to 2 As shown, this application provides a multi - energy storage capacity configuration method, including:

[0040] S1. Initialize a multi - energy storage capacity configuration plan including multiple energy storage types;

[0041] The initialization includes initializing the range of system operation parameters. For example, set the upper and lower limits of energy storage capacity configuration, and set the upper and lower limits of the power of conventional units and new energy units. Set the initial value of the multi - energy storage capacity configuration set Z as {0, 0, …, 0}, where the number n of elements in Z is the number of multi - energy storage types to be configured in the system.

[0042] For example, in a multi - energy storage system, it may contain four types of energy storage, namely electrochemical energy storage, pumped - storage, compressed air energy storage, and gravitational energy storage. The multi - energy storage capacity configuration plan, that is, the plan for configuring the capacity of each energy storage type. For example, after initialization, the initial value of the multi - energy storage capacity configuration set Z is {0, 0, …, 0}, that is, the capacity configuration of each type of energy storage is 0, which is the initial configuration plan.

[0043] S2. Optimize the multi - energy storage capacity configuration plan based on preset system operation constraint conditions;

[0044] The multi - energy storage optimal configuration model includes: an upper - layer model for comprehensively evaluating the system operation status, and a lower - layer model for operation verification.

[0045] Based on the system time - series operation simulation, the lower - layer model aims to minimize the system operation cost. The constraint conditions include system network and power - heat balance constraints, and the characteristics constraints of various units and flexible power sources, to obtain the probability distribution of the system operation state. The objective function is as follows:

[0046]

[0047] Among them, C F is the output cost of conventional power sources; C ess,i is the operation and maintenance cost of the i - type energy storage power station.

[0048]

[0049] Among them, N gen is the number of conventional power sources; c gen is the cost of conventional power sources; T is the total number of optimized operation time periods; P(j, t) is the output of conventional power source j at time period t; Δt is the operation time scale of conventional power sources. In this application, the operation time scale of conventional units is set to 1h.

[0050]

[0051] Among them, c ess,i is the per - unit - energy operation and maintenance cost of the i - type energy storage; P essc,i (t) and P essd,i (t) are the charging and discharging powers of the i - type energy storage at time period t respectively; T i is the total number of optimized operation time periods of the i - type energy storage; Δt i is the operation time scale of the i - type energy storage. According to different types of energy storage, the operation time scales are different, but the different time scales are unified through the operation cost of the energy storage.

[0052] The constraint conditions of the lower - layer model mainly include: system operation constraints, conventional unit operation constraints, new - energy output constraints, line - capacity constraints, and energy - storage operation constraints.

[0053] System operation constraints:

[0054] System operation constraints are mainly composed of system power - balance constraints and reserve - capacity constraints. The power sources in the system are mainly composed of conventional units and new - energy units. At the same time, through the regulation of the energy - storage system, the power - system balance state is achieved:

[0055]

[0056] Among them, Pessc,i (t) and P essd,i (t) are the charging and discharging powers of energy storage type i in period t; P L,t is the load in period t; P new,k (t) is the discharging power of new energy of type k in period t, P j (t) is the discharging power of conventional power source of type j in period t.

[0057] The reserve demand of the system is mainly borne by the conventional units and energy storage with regulation ability in the system:

[0058]

[0059] Among them, R u,g,t and R D,g,t are the up and down spinning reserves that the conventional unit g can provide at time t, and are the adjustable up and down reserve capacities that the energy storage can provide at time t; and are the up and down reserve demands of the load at time t, and are the up and down regulation reserve demands of wind power at time t.

[0060] Conventional unit operation constraints:

[0061] (1) Output constraint under unit operation state:

[0062] u g,t P i，min ≤ P(i, t) ≤ u g，t P i，max

[0063] Among them, P i,max and P i,min are the upper and lower limits of the output of unit i, u g,t is the start-stop state of unit g in period t, u g,t = 1 represents the unit is started, u g,t = 0 represents the unit is shut down.

[0064] (2) Unit ramp constraint:

[0065]

[0066] Among them, P g,t is the output of unit g in period t, P g,t-1 is the output of unit g in period t - 1, and are the upper and lower limits of the ramp of thermal power units respectively, and T is the time interval, taking 1h.

[0067] (3) Reserve capacity constraint:

[0068]

[0069] Among them, R U,g,t and R D,g,t are the upward and downward spinning reserves that the conventional unit g can provide at time t, respectively.

[0070] (4) New energy power station operation constraint:

[0071] The output of the new energy power station at time t shall not exceed the maximum output of the new energy power station at that time:

[0072] 0 ≤ P new，k (i, t) ≤ PM new，k (i, t)

[0073] Among them, P Mnew,k (i, t) is the maximum output of new energy i in the time period t under scenario k.

[0074] (5) System operation constraints include:

[0075] 1) System power flow constraint:

[0076] -P l，max ≤ P l，t ≤ P l，max

[0077] Among them, P L,t is the load at time period t; P l,t is the transmission power of line l at time t, which can be obtained through DC power flow calculation; P l,max is the upper limit of the capacity of line l.

[0078] 2) Node voltage and phase constraints:

[0079]

[0080] Among them, δ i,t is the phase of node i at time t.

[0081] S3. Respectively increase the capacity of each energy storage type in the multiple energy storage capacity configuration schemes by a fixed increment to generate multiple configuration schemes;

[0082] In the upper-layer model of this application, during the refined multi-energy storage configuration process, multiple iterations are adopted. In each iteration process, based on the initial multi-energy storage configuration plan of this iteration, for the energy storage that can continue to increase its capacity, a certain amount of capacity is increased respectively to form the set of energy storage configuration plans for this iteration. Compare the magnitudes of the net revenue incremental rates of different energy storage configuration plans, and select the energy storage configuration plan with the largest net revenue incremental rate as the initial multi-energy storage configuration plan for the next iteration process.

[0083] Specifically, in the k-th iteration process, the initial capacity of the energy storage is {x 1s_k , x 2s_k , …, x ns_k}, assuming that each type of energy storage can increase its capacity by D xn , then the set of multi-energy storage configuration plans C k for this iteration is:

[0084]

[0085] That is, in the i-th iteration process, the set of multi-energy storage configuration plans C k has a total of n configuration plans.

[0086] S4. Calculate the net revenue increment of each of the said configuration plans according to the preset greenness index, safety index, regulation index, and economic index;

[0087] Taking the above n configuration plans as the inputs of the lower-layer model respectively, n time-series operation simulation output results can be obtained.

[0088] In the upper-layer model, calculate the system net revenue increment L(x1, x2, …, x n ) of the n time-series operation simulation output results respectively. It is a comprehensive evaluation index including the greenness, economy, coordination, and safety of the system operation.

[0089] This application selects an index group representing 4 dimensions of the power system, namely safety, economy, greenness, and coordination, and conducts the benefit evaluation of the energy storage system from the above 4 aspects to realize the evaluation of the multi-energy storage collaborative planning scheme. The system net revenue is the difference between the benefits and costs brought by the newly added energy storage and the investment cost of the newly added energy storage. Among them, the benefits brought by the newly added energy storage mainly include the improvement of new energy utilization rate due to the reduction of the power generation of traditional units in the system, the realization of power supply guarantee, and the benefits caused by enhancing the system regulation ability.

[0090] The expression of the system net revenue increment is shown as follows:

[0091] maxL(x1, x2, x3, x4)

[0092] Where

[0093] There are four types of energy storage, namely electrochemical energy storage, pumped storage, compressed air energy storage and gravity energy storage, which are defined as \(i = 1\sim4\), where \(i\) is the type of energy storage, and \(x\) i is the capacity of the \(i\)-th type of energy storage; \(L(x_1,x_2,x_3,x_4)\) reflects the impacts of the newly added energy storage on the system in terms of greenness, safety, regulation and economy respectively.

[0094] Greenness index reflects the improvement of the system greenness due to the newly added energy storage.

[0095] Due to the newly added \(x\) i The benefits brought about by the increase in the utilization rate of new energy caused by the newly added type of energy storage mainly include the curtailment penalty cost \(C\) reduced due to the increase in the new energy consumption rate pvloss_xi 、\(C\) wploss_xi and the carbon emission reduction income \(C\) reduced due to the increase in the new energy consumption rate co2loss_xi . That is:[[]]END]]

[0096]

[0097] Among them,[[]]END]] is the amount of renewable energy curtailed in the \(k\)-th cycle system. \(\lambda\) re is the renewable energy curtailment penalty price. \(\lambda\) co2 is the income coefficient caused by the reduction of carbon emissions,[[]]END]] is the carbon emission of the \(k\)-th cycle system.[[]]END]]

[0098] Safety index The income brought about by the enhancement of the system's power supply guarantee ability due to the newly added \(x\) i type of energy storage, that is:[[]]END]]

[0099]

[0100] Among them: The constant \(c\) cut is the loss of load penalty coefficient;[[]]END]] is the expected value of power shortage in the \(k\)-th cycle.[[]]END]]

[0101] Coordination index The income brought about by the enhancement of the system's coordination due to the newly added \(x\) i type of energy storage, including the income brought about by rationalizing the utilization hours of coal-fired generating units and the income brought about by reducing the over-limit of the cross-river section tidal current That is:[[]]END]]

[0102]

[0103] Among them:[[]]END]]

[0104]

[0105] c tur is the power generation cost adjustment coefficient of the coal-fired power unit, and P max is the full-load power of the coal-fired power unit, and c min is the unit electricity price at the full load of the coal-fired power unit, and P min is the minimum power of the coal-fired power unit, and c max is the unit electricity price at the minimum output of the coal-fired power unit. is the fixed coal cost for the k-th cycle; is the output power of the cross-river section for the k-th cycle, and E limit is the output capacity of the cross-river section, and a constant can be shared for each working condition.

[0106] The economic index ΔC i (x i ) represents the economic impact brought by the newly added energy storage to the system, and can be jointly represented by the cost per kilowatt-hour of the newly added energy storage and the increased energy storage power of the system:

[0107] ΔC i (x i ) = LOCE_xi·ΔE xi

[0108] where LOCE_xi is the cost per kilowatt-hour of the energy storage of type x i , and ΔE xi is the newly added capacity of the energy storage.

[0109] According to the calculation method of the net income increment and the system net income incremental rate, the system net income incremental rate set L for this iteration process can be obtained s :

[0110] L s = {γ 1_k , γ 2_k , …, γ n_k}

[0111] Select the energy storage configuration scheme corresponding to the maximum value max(L s ) in the system net income incremental rate set L s as the energy storage configuration result of this iteration, that is, the initial configuration scheme of the multi-energy storage for the next iteration process.

[0112] S5. Calculate the net income incremental rate of each configuration scheme according to the fixed increment and the net income increment;

[0113] Define the system net income incremental rate of each type of energy storage. Taking the system net income incremental rate in the case of the increase of the electrochemical energy storage capacity by △x1 as an example, its expression is shown as follows, where L(x1, x2, …, x n) is the expression for the net revenue increment of the system.

[0114]

[0115] S6. Screen the configuration plans where the net revenue incremental rate > 0 and the net revenue incremental rate is the largest, and set this configuration plan as the new configuration plan;

[0116] Calculate the net revenue incremental rates of n types of energy storage respectively. Sort the results where the net revenue incremental rate of the multi - energy storage is greater than zero from high to low, select the energy storage corresponding to the maximum value, increase its capacity by △x, and use it as the new energy storage capacity configuration plan.

[0117] S7. Repeat steps S2 - S6 for the new configuration plan until the energy storage capacity of each energy storage type reaches the planned upper limit or the net revenue increment ≤ 0, and output the new configuration plan.

[0118] Repeat the above steps S2 - S6 until the net revenue incremental rates of the multi - energy storage are all less than 0, or the capacity of the multi - energy storage reaches the configuration upper limit. The energy storage configuration plan before the iteration stops is the optimized energy storage configuration plan.

[0119] Finally, output the optimized multi - energy storage capacity configuration plan.

[0120] Please refer to Figure 3 As shown, the present application also provides a multi - energy storage capacity configuration device, including:

[0121] An initialization module 201, which initializes a multi - energy storage capacity configuration plan including multiple energy storage types;

[0122] An optimization module 202, which optimizes the multi - energy storage capacity configuration plan based on preset system operation constraint conditions;

[0123] A configuration module 203, which increases the capacity of each energy storage type in the multi - energy storage capacity configuration plan by a fixed increment respectively to generate multiple configuration plans;

[0124] A revenue module 204, which calculates the net revenue increment of each configuration plan according to preset greenness indicators, safety indicators, regulation indicators, and economic indicators;

[0125] An incremental rate module 205, which calculates the net revenue incremental rate of each configuration plan according to the fixed increment and the net revenue increment;

[0126] A screening module 206, which screens the configuration plan where the net revenue incremental rate > 0 and the net revenue incremental rate is the largest, and sets this configuration plan as the new configuration plan;

[0127] The loop output module 207 repeats steps S2 to S6 for the new configuration plan until the energy storage capacity of each energy storage type reaches the planned upper limit or the net revenue increment ≤ 0, and outputs the new configuration plan.

[0128] Further, the system operation constraint conditions include: system power balance constraint, reserve capacity constraint, conventional unit operation constraint, new energy output constraint, line capacity constraint, and energy storage operation constraint.

Claims

1. A method for configuring the capacity of a multi - energy storage, characterized in that, It includes: S1 Initialize a multi - energy - storage capacity configuration plan including multiple energy - storage types; S2 Optimize the multi - energy - storage capacity configuration plan based on preset system operation constraint conditions; S3 Increase the capacity of each energy - storage type in the multi - energy - storage capacity configuration plan by a fixed increment respectively to generate multiple configuration plans; S4 Calculate the net - income increment of each configuration plan according to preset greenness indicators, safety indicators, regulatability indicators and economic indicators; S5 Calculate the net - income incremental rate of each configuration plan according to the fixed increment and the net - income increment; S6 Screen out the configuration plan with the net - income incremental rate > 0 and the maximum net - income incremental rate, and set this configuration plan as the new configuration plan; S7 Repeat steps S2 - S6 for the new configuration plan until the energy - storage capacity of each energy - storage type reaches the planned upper limit or the net - income increment ≤ 0, and output the new configuration plan.

2. The multi-energy storage capacity configuration method according to claim 1, wherein Initializing a multi - energy - storage capacity configuration plan including multiple energy - storage types includes: Set the upper and lower limits of the power of conventional units and new - energy units, and give the upper and lower limits of the energy - storage capacity configuration.

3. The method for configuring the multi - energy storage capacity according to claim 1, wherein The fixed increment is preset according to system requirements and the technical characteristics of energy - storage types.

4. The method for configuring the multi - energy storage capacity according to claim 1, wherein The greenness indicators include: the reduced curtailment penalty cost of wind and light and the income from reduced carbon emissions.

5. The multi-energy storage capacity configuration method according to claim 1, characterized in that The safety indicators include: the income brought by the enhanced system power supply capacity caused by the newly added energy storage.

6. The multi-energy storage capacity configuration method according to claim 1, wherein The regulatability indicators include: the income brought by reducing the utilization hours of coal - fired units and the income brought by reducing the over - limit of the cross - river section power flow.

7. The method for configuring the multi - energy storage capacity according to claim 1, wherein The economic indicators include: the income brought by the newly added energy storage to the system.

8. The multi-energy storage capacity configuration method according to claim 1, wherein The system operation constraint conditions include: system power balance constraint, reserve capacity constraint, conventional unit operation constraint, new - energy output constraint, line capacity constraint and energy - storage operation constraint.

9. A multi - energy - storage capacity configuration device, characterized in that, It includes: An initialization module that initializes a multi - energy - storage capacity configuration plan including multiple energy - storage types; An optimization module that optimizes the multi - energy - storage capacity configuration plan based on preset system operation constraint conditions; A configuration module that increases the capacity of each energy - storage type in the multi - energy - storage capacity configuration plan by a fixed increment respectively to generate multiple configuration plans; A revenue module that calculates the net - income increment of each configuration plan according to preset greenness indicators, safety indicators, regulatability indicators and economic indicators; An incremental - rate module that calculates the net - income incremental rate of each configuration plan according to the fixed increment and the net - income increment; A screening module that screens out the configuration plan with the net - income incremental rate > 0 and the maximum net - income incremental rate, and sets this configuration plan as the new configuration plan; A loop - output module that repeats steps S2 - S6 for the new configuration plan until the energy - storage capacity of each energy - storage type reaches the planned upper limit or the net - income increment ≤ 0, and outputs the new configuration plan.

10. The multi-energy storage capacity configuration device according to claim 9, wherein, The system operation constraint conditions include: system power balance constraint, reserve capacity constraint, conventional unit operation constraint, new - energy output constraint, line capacity constraint and energy - storage operation constraint.

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