A power distribution network and user-oriented energy storage cooperation configuration optimization method and storage medium

Abstract

The application discloses a kind of energy storage cooperation configuration optimization method and storage medium for distribution network and user, method includes: the collaborative energy storage system model including distribution network side energy storage and serving multiple users user side energy storage is established;The objective function with the minimum sum of collaborative energy storage system cost, distribution network loss cost and user energy cost is constructed, the operation constraint of collaborative energy storage system, the power flow safety constraint of distribution network and the power balance constraint of user are set;The objective function and constraint condition are solved using iterative method embedded mixed integer linear programming method, and the optimal configuration capacity of distribution network side and user side energy storage and the best access point scheme of distribution network side energy storage are obtained.The application can improve the operation performance of distribution network, and optimize the energy storage configuration of distribution network and user side.

Description

Technical Field

[0001] This invention relates to a method for optimizing the collaborative configuration of energy storage for distribution networks and users, as well as a storage medium, belonging to the field of energy storage planning technology. Background Technology

[0002] Currently, renewable energy sources, such as photovoltaic and wind power, are widely integrated into the power distribution network, significantly increasing the randomness and volatility of power supply. Meanwhile, the proactive response characteristics of users further exacerbate the uncertainty on both the source and load sides. Against this backdrop, energy storage systems, especially electrochemical energy storage with flexible power and energy time-shifting capabilities, have become a key technological means to improve the resilience of the power distribution network, promote the consumption of renewable energy, and reduce energy costs for users.

[0003] From the distribution network perspective, distribution operators have a need to configure energy storage to improve grid operation indicators such as reducing network losses, alleviating line congestion, and smoothing voltage fluctuations. However, independent energy storage on the distribution network side typically faces bottlenecks such as high initial investment costs and long investment recovery periods. From the user side, users configure energy storage to achieve "low-storage, high-generation" to reduce electricity costs. In addition, shared energy storage configured by multiple users further improves the economics of user-side energy storage configuration. However, existing user-side energy storage configurations only consider their own economic characteristics, and their charging and discharging behavior may conflict with the overall operational needs of the distribution network. For example, concentrated charging and discharging by users in pursuit of electricity cost savings may actually create new load peaks at the distribution network level, deteriorating the network's operating status.

[0004] Furthermore, existing energy storage cooperation configuration models often neglect the impact of energy storage lifetime on the configuration results, and even more so lack the impact of differences in energy storage lifetime under different service targets / demands on joint configuration. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method and storage medium for optimizing the cooperative configuration of energy storage for distribution networks and users, which can improve the operating performance of distribution networks and optimize the energy storage configuration on both the distribution network and user sides. To achieve the above objective, this invention employs the following technical solution:

[0006] In a first aspect, the present invention provides a method for optimizing the cooperative configuration of energy storage for distribution networks and users, comprising:

[0007] Establish a collaborative energy storage system model that includes distribution network-side energy storage and user-side energy storage serving multiple users;

[0008] Construct an objective function that minimizes the sum of the cost of the collaborative energy storage system, the network loss cost of the distribution network, and the user's energy consumption cost, and set the operating constraints of the collaborative energy storage system, the power flow security constraints of the distribution network, and the power balance constraints of the user;

[0009] An iterative method with embedded mixed-integer linear programming is used to solve the objective function and constraints, resulting in the optimized configuration capacity of energy storage on the distribution network side and the user side, as well as the optimal access point scheme for energy storage on the distribution network side.

[0010] In conjunction with the first aspect, optionally, the collaborative energy storage system model satisfies:

[0011] The total rated power of the collaborative energy storage system model is the sum of the rated power of the distribution network-side energy storage and the rated power of the user-side energy storage;

[0012] The total rated capacity of the collaborative energy storage system model is the sum of the rated capacity of energy storage on the distribution network side and the rated capacity of energy storage on the user side.

[0013] The allocation of charging and discharging power obtained by each user from user-side energy storage is limited by the rated power of user-side energy storage;

[0014] The charging and discharging power of energy storage on the distribution network side is limited by the rated power of energy storage on the distribution network side at various times and in various scenarios.

[0015] In conjunction with the first aspect, optionally, the cost of the collaborative energy storage system includes configuration costs and operation and maintenance costs;

[0016] The configuration cost is calculated based on the one-time investment cost of the rated power of the distribution network-side energy storage, the one-time investment cost of the rated capacity of the distribution network-side energy storage, the one-time investment cost of the rated power of the user-side energy storage, the one-time investment cost of the rated capacity of the user-side energy storage, and the capital recovery coefficient related to the energy storage lifespan; wherein, the capital recovery coefficient related to the energy storage lifespan is determined based on the lifespan of the distribution network-side energy storage and the user-side energy storage and the discount rate;

[0017] The operation and maintenance cost is calculated based on the rated power of the collaborative energy storage system and the unit operation and maintenance cost.

[0018] In conjunction with the first aspect, optionally, the distribution network loss cost is calculated based on branch current, branch resistance, unit network loss cost, and operating scenario duration; the user energy cost includes power cost and energy cost.

[0019] The power cost is calculated based on power price, maximum net load power, and operating scenario duration.

[0020] The energy cost is calculated based on the electricity price per unit, net load power, and operating duration.

[0021] In conjunction with the first aspect, optionally, the operational constraints of the collaborative energy storage system include:

[0022] The overall installation power limit and capacity limit constraints of the collaborative energy storage system;

[0023] The operational constraints of user-side energy storage and distribution network-side energy storage in the collaborative energy storage system.

[0024] In conjunction with the first aspect, optionally, the operational constraints of user-side energy storage in the collaborative energy storage system include:

[0025] Non-negative constraint on the charging and discharging power of user-side energy storage;

[0026] User-side energy storage is subject to mutual exclusion constraints on its charging and discharging states at any given time.

[0027] The charging and discharging power of user-side energy storage is limited by both the rated power and the charging and discharging status flag.

[0028] The dynamic balance constraint of user-side energy storage means that the remaining power at the current moment is determined by the remaining power at the previous moment and the current total charge / discharge.

[0029] The remaining energy capacity of user-side energy storage is maintained within the range determined based on the rated capacity and the upper and lower limits of the state of charge.

[0030] The lifetime constraints of user-side energy storage include the total effective discharge being limited by the theoretical discharge calculated based on the rated number of cycles and the rated depth of discharge.

[0031] In conjunction with the first aspect, optionally, the operational constraints of the distribution network-side energy storage in the collaborative energy storage system include:

[0032] The charging and discharging states of energy storage on the distribution network side are mutually exclusive at any given time.

[0033] The charging and discharging power of energy storage on the distribution network side is limited by both the rated power and the charging and discharging status flag.

[0034] The dynamic balance constraint of energy storage on the distribution network side means that the remaining energy at the current moment is determined by the remaining energy at the previous moment and the charging / discharging amount at the current moment.

[0035] The remaining energy capacity of the energy storage on the distribution network side is maintained within a range determined based on its rated capacity and upper and lower limits of state of charge;

[0036] The lifespan constraints of energy storage on the distribution network side include the total effective discharge capacity being limited by the theoretical discharge capacity calculated based on the rated number of cycles and the rated depth of discharge.

[0037] In conjunction with the first aspect, optionally, the power flow security constraints of the distribution network include: node power balance constraints, node voltage security limit constraints, branch power flow constraints, and coupling constraints of node voltage, branch current, and power.

[0038] In conjunction with the first aspect, optionally, the method of using an iterative method embedded with a mixed-integer linear programming method to solve the objective function and constraints to obtain the optimized configuration capacity of energy storage on the distribution network side and the user side, as well as the optimal access point scheme for energy storage on the distribution network side, includes:

[0039] Step a: Initialize the lifetime of distribution network-side energy storage, the lifetime of user-side energy storage, and the access point of distribution network-side energy storage;

[0040] Step b: Using the lifetime of energy storage on the distribution network side, the lifetime of energy storage on the user side, and the access point of energy storage on the distribution network side as known quantities, call the mixed integer linear programming solver to solve for the configuration capacity of energy storage on the distribution network side and the user side.

[0041] Step c: Based on the solution results, update the lifetime of distribution network-side energy storage, the lifetime of user-side energy storage, and the access point of distribution network-side energy storage;

[0042] Step d: Repeat steps b and c until the iteration termination condition is met, and output the final optimized configuration capacity of energy storage on the distribution network side and the user side, and the optimal access point for energy storage on the distribution network side.

[0043] In a second aspect, the present invention provides a computer-readable storage medium having a computer program / instruction stored thereon, which, when executed by a processor, implements the steps of the energy storage cooperative configuration optimization method for distribution networks and users described in the first aspect.

[0044] Compared with existing technologies, the beneficial effects achieved by the energy storage cooperative configuration optimization method and storage medium for distribution networks and users provided in this embodiment of the invention include:

[0045] This invention establishes a collaborative energy storage system model that includes distribution network-side energy storage and user-side energy storage serving multiple users. This invention couples and optimizes the distribution network operation status with the energy consumption behavior of multiple users, which can overcome the conflict of operation objectives caused by the independent configuration of distribution network-side energy storage and user-side energy storage in the prior art. This invention can generate configuration schemes that take into account both the overall operation performance of the distribution network and the energy consumption needs of the user side, thereby improving the comprehensive application efficiency of the energy storage system in the distribution network.

[0046] This invention constructs an objective function aimed at minimizing the sum of the cost of the collaborative energy storage system, the distribution network loss cost, and the user's energy consumption cost. It sets operational constraints for the collaborative energy storage system, power flow security constraints for the distribution network, and power balance constraints for users. An iterative method embedding a mixed-integer linear programming approach is used to solve the objective function and constraints, yielding the optimized configuration capacity of energy storage on both the distribution network and user sides, as well as the optimal access point scheme for energy storage on the distribution network side. This invention considers the lifetime of energy storage on both the distribution network and user sides, making the configuration results more consistent with the actual physical laws and long-term operating conditions of energy storage devices, thus enhancing the accuracy of the planning scheme and its application value in practical engineering.

[0047] This invention ultimately yields the specific capacity of energy storage on the distribution network side and the user side, as well as the clear access location of energy storage on the distribution network side. It can provide a technical basis for the planning and construction of energy storage systems and help to achieve the rational layout and efficient utilization of energy storage in the distribution network. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating an energy storage cooperative configuration optimization method for distribution networks and users, as described in Embodiment 1 of the present invention. Detailed Implementation

[0049] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0050] Example 1:

[0051] like Figure 1 As shown in the figure, this embodiment provides a method for optimizing the cooperative configuration of energy storage for distribution networks and users, including:

[0052] Establish a collaborative energy storage system model that includes distribution network-side energy storage and user-side energy storage serving multiple users;

[0053] Construct an objective function that minimizes the sum of the cost of the collaborative energy storage system, the network loss cost of the distribution network, and the user's energy consumption cost, and set the operating constraints of the collaborative energy storage system, the power flow security constraints of the distribution network, and the power balance constraints of the user;

[0054] An iterative method with embedded mixed-integer linear programming is used to solve the objective function and constraints, resulting in the optimized configuration capacity of energy storage on the distribution network side and the user side, as well as the optimal access point scheme for energy storage on the distribution network side.

[0055] The specific steps are as follows.

[0056] Step 1: Establish a collaborative energy storage system model that includes distribution network-side energy storage and user-side energy storage serving multiple users.

[0057] Due to the requirements of collaborative configuration, the energy storage system consists of two parts: distribution network energy storage and user-side energy storage. Among them, user-side energy storage serves multiple users simultaneously.

[0058] The collaborative energy storage system model satisfies:

[0059] The total rated power of the collaborative energy storage system model is the sum of the rated power of the distribution network-side energy storage and the rated power of the user-side energy storage, expressed by the following formula:

[0060] ,(1)

[0061] In equation (1), The total rated power of the collaborative energy storage system model. The rated power for user-side energy storage. This refers to the rated power of energy storage on the distribution network side.

[0062] The total rated capacity of the collaborative energy storage system model is the sum of the rated capacity of the distribution network-side energy storage and the rated capacity of the user-side energy storage, expressed by the following formula:

[0063] (2),

[0064] In equation (2), The total rated capacity of the collaborative energy storage system model. The rated capacity for user-side energy storage The rated capacity of energy storage on the distribution network side.

[0065] In equation (1), the rated power of user-side energy storage and the rated power of distribution network-side energy storage satisfy the following condition:

[0066] , (3).

[0067] In equation (2), the rated capacity of user-side energy storage and the rated capacity of distribution network-side energy storage satisfy the following condition:

[0068] , (4).

[0069] The allocation of charging and discharging power obtained by each user from user-side energy storage is limited by the rated power of user-side energy storage, as expressed by the following formula:

[0070] (5)

[0071] In equation (5), For users In the scene Below Constantly using the discharge power of the stored energy. For users In the scene Below Always use the charging power of the energy storage. For user groups.

[0072] The charging and discharging power of distribution network-side energy storage at various times and under various scenarios is limited by the rated power of distribution network-side energy storage, which can be expressed by the following formula:

[0073] (6)

[0074] In equation (6), For distribution networks in scenarios Below Constantly using the discharge power of the stored energy. For distribution networks in scenarios Below The charging power of the energy storage is used at all times.

[0075] This embodiment couples and optimizes the distribution network operation status with the energy consumption behavior of multiple users, which can overcome the conflict of operation objectives caused by the independent configuration of energy storage on the distribution network side and energy storage on the user side in the prior art. The present invention can generate a configuration scheme that takes into account both the overall operation performance of the distribution network and the energy consumption demand of the user side, thereby improving the comprehensive application efficiency of the energy storage system in the distribution network.

[0076] Step 2: Construct an objective function that aims to minimize the sum of the cost of the collaborative energy storage system, the cost of distribution network losses, and the cost of user energy consumption.

[0077] The objective function is optimized on an annual time scale and consists of three parts: the cost of the collaborative energy storage system, the cost of distribution network losses, and the cost of user energy consumption.

[0078] Step 2.1: Calculate the cost of the collaborative energy storage system.

[0079] The cost of a collaborative energy storage system includes configuration costs and operation and maintenance costs;

[0080] The configuration cost is calculated based on the one-time investment cost of the rated power of the distribution network-side energy storage, the one-time investment cost of the rated capacity of the distribution network-side energy storage, the one-time investment cost of the rated power of the user-side energy storage, the one-time investment cost of the rated capacity of the user-side energy storage, and the capital recovery factor related to the energy storage lifespan. The capital recovery factor related to the energy storage lifespan is determined based on the lifespan of the distribution network-side energy storage and the user-side energy storage, as well as the discount rate.

[0081] Operation and maintenance costs are calculated based on the rated power of the collaborative energy storage system and the unit operation and maintenance cost.

[0082] The cost of a collaborative energy storage system, taking into account the differences in energy storage lifespan, is expressed by the following formula:

[0083] (7)

[0084] In equation (7), To coordinate the total cost of the energy storage system, To account for the configuration cost of collaborative energy storage systems, To reduce the operation and maintenance costs of collaborative energy storage systems. The one-time investment cost per unit of rated power of energy storage The one-time investment cost per unit of rated capacity of energy storage The annual operation and maintenance cost per unit power of energy storage.

[0085] Considering that funds have a time attribute, in equation (7), The one-time investment cost for user-side energy storage is converted into an equivalent annual return on investment factor. The capital recovery factor is used to convert the one-time investment cost of energy storage on the distribution network side into an equivalent annual value. This factor is related to the entire life cycle of energy storage, and the specific calculation formula is as follows:

[0086] (8)

[0087] In equation (8), The discount rate is... For user-side energy storage lifespan, This refers to the lifespan of energy storage on the distribution network side.

[0088] Step 2.2: Calculate the network loss cost of the distribution network.

[0089] Distribution network loss cost is calculated based on branch current, branch resistance, unit loss cost, and operating scenario duration, and is expressed by the following formula:

[0090] (9)

[0091] In equation (9), For distribution network loss costs, Cost per unit of network loss For the scene , For scene collection, The number of days for each scenario, For a moment , For time-based assembly, branch road Taking the trend as the right direction as the node To the node , The set of all branches in the network. , For the scene Down Time-of-day branch Current on Let be the resistance of branch ij.

[0092] Step 2.3: Calculate the user's energy cost.

[0093] User energy costs include power costs and energy costs;

[0094] Power cost is calculated based on power price, maximum net load power, and operating scenario duration;

[0095] Energy costs are calculated based on the electricity price per unit, net load power, and operating duration.

[0096] The user's energy cost is expressed by the following formula:

[0097] (10)

[0098] In equation (10), For users' energy costs, For users' power costs under a two-part electricity pricing scenario, This refers to the energy cost for users under a two-part electricity pricing scenario. For users , For user collection, The number of months for each scenario, The power price of electricity, This is the maximum net load power (monthly setpoint). The number of days for each scenario, The price per unit of electricity. Net load power, It is a time series with intervals.

[0099] Step 2.4: Construct an objective function that minimizes the sum of the costs of the collaborative energy storage system, the distribution network loss cost, and the user's energy consumption cost. The objective function is expressed by the following formula:

[0100] , (11).

[0101] Step 3: Set the operating constraints of the collaborative energy storage system, the power flow security constraints of the distribution network, and the power balance constraints of users.

[0102] In addition to satisfying the equations and inequalities in step 1, the operational constraints of the collaborative energy storage system include:

[0103] Overall installation power and capacity limits for collaborative energy storage systems;

[0104] Operational constraints of user-side energy storage and distribution network-side energy storage in collaborative energy storage systems.

[0105] Step 3.1: Set the overall installed power limit constraint and capacity limit constraint of the collaborative energy storage system, expressed by the following formula:

[0106] (12)

[0107] In equation (12), The maximum allowable installed power for a collaborative energy storage system. The maximum capacity that can be installed for a collaborative energy storage system.

[0108] Step 3.2: Set the operational constraints for user-side energy storage in the collaborative energy storage system, including:

[0109] The non-negativity constraint of the charging and discharging power of user-side energy storage is expressed by the following formula:

[0110] (13)

[0111] In equation (13), For users In the scene Below Constantly using the discharge power of the stored energy. For users In the scene Below The charging power of the energy storage is used at all times.

[0112] The mutual exclusion constraint of the charging and discharging states of user-side energy storage at any given time is expressed by the following formula:

[0113] (14)

[0114] In equation (14), For the scene Below The discharge status flag of the user-side energy storage at all times. For the scene Below The charging status flag of the user-side energy storage at all times.

[0115] The charging and discharging power of user-side energy storage is limited by both the rated power and the charging and discharging status flag, as expressed by the following formula:

[0116] , (15).

[0117] The dynamic balance constraint of user-side energy storage, that is, the remaining energy at the current moment is determined by the remaining energy at the previous moment and the current total charge / discharge, is expressed by the following formula:

[0118] (16)

[0119] In equation (16), For the scene User-side energy storage Remaining battery level at any given time For the scene User-side energy storage Remaining battery level at any given time To improve the charging efficiency of shared energy storage, For the discharge efficiency of shared energy storage; For the scene The remaining energy of the user-side energy storage at time 1. For the scene The remaining energy of the user-side energy storage at the initial moment. For users In the scene The charging power of the energy storage at time 1. For users In the scene The discharge power of the stored energy is used at time 1.

[0120] The remaining energy capacity of user-side energy storage remains within a range determined based on rated capacity and upper and lower limits of state of charge, as expressed by the following formula:

[0121] (17)

[0122] In equation (17), This is the minimum state of charge value for energy storage. This represents the maximum state of charge value for energy storage.

[0123] The lifetime constraints of user-side energy storage, including the total effective discharge capacity limited by the theoretical discharge capacity calculated based on the rated cycle number and rated discharge depth, are expressed by the following formula:

[0124] (18)

[0125] In equation (18), The total effective discharge of user-side energy storage. This refers to the number of cycles under rated discharge conditions of the energy storage. This refers to the rated depth of discharge under rated discharge conditions for energy storage. For user-side energy storage lifespan, The number of days for each scenario.

[0126] Step 3.3: Set the operational constraints for distribution network-side energy storage in the collaborative energy storage system, including:

[0127] The mutual exclusion constraint of the charging and discharging states of energy storage on the distribution network side at any given time is expressed by the following formula:

[0128] , (19)

[0129] In equation (19), For the scene Below The discharge status flag of the energy storage on the distribution network side is constantly updated. For the scene Below The charging status flag of the energy storage on the distribution network side at all times.

[0130] The charging and discharging power of energy storage on the distribution network side is limited by both the rated power and the charging / discharging status flag, as expressed by the following formula:

[0131] (20)

[0132] In equation (20), For distribution networks in scenarios Below Constantly using the discharge power of the stored energy. For distribution networks in scenarios Below Always use the charging power of the energy storage. The maximum power that can be installed for a collaborative energy storage system.

[0133] The dynamic balance constraint of energy storage on the distribution network side, that is, the remaining energy at the current moment is determined by the remaining energy at the previous moment and the charging / discharging amount at the current moment, is expressed by the following formula:

[0134] ,(twenty one),

[0135] In equation (21), For the scene Energy storage on the distribution network side Remaining battery level at any given time For the scene Energy storage on the distribution network side The remaining battery power at any given time; For the scene The remaining energy of the energy storage on the downstream distribution network side at time 1. For the scene The remaining energy of the energy storage on the downstream distribution network at the initial moment. For the distribution network side in the scenario The charging power of the energy storage at time 1. For the distribution network side in the scenario The discharge power of the stored energy is used at time 1.

[0136] The remaining energy storage capacity on the distribution network side is maintained within a range determined based on its rated capacity and upper and lower limits of state of charge, as expressed by the following formula:

[0137] ,(twenty two),

[0138] In equation (22), This is the minimum state of charge value for energy storage. The rated capacity of energy storage on the distribution network side. For the scene Energy storage on the distribution network side Remaining battery level at any given time This represents the maximum state of charge value for energy storage.

[0139] The lifetime constraint of energy storage on the distribution network side, including the total effective discharge capacity limited by the theoretical discharge capacity calculated based on the rated cycle number and rated discharge depth, is expressed by the following formula:

[0140] ,(twenty three),

[0141] In equation (23), The total effective discharge of user-side energy storage. This refers to the number of cycles under rated discharge conditions of the energy storage. This refers to the rated depth of discharge under rated discharge conditions for energy storage. For the lifespan of energy storage on the distribution network side, The number of days for each scenario.

[0142] Step 3.3: Set power flow security constraints for the distribution network, including: node power balance constraints, node voltage security limit constraints, branch power flow constraints, and coupling constraints between node voltage, branch current, and power, expressed by the following formula:

[0143] ,(twenty four),

[0144] In equation (24), For Let be the set of branch end nodes of the first node. For Let be the set of the starting nodes of the branches of the terminal nodes. for The set of power supply on the node (i.e., grid-side power supply). For flow through branch road active power, branch road The resistance, The active power flowing through branch jm, For the scene Next node exist Active power of load at any given time For the scene Next node exist Renewable energy access power at any given time For the scene Next node exist Active power of power supply at any given time For nodes The 0-1 flag indicating whether to connect to grid-side energy storage. The charging power of the energy storage connected to the grid side at node j. The discharge power of the energy stored on the grid side of node j. For nodes The electrical conductivity;

[0145] In equation (24), For flow through branch road reactive power, branch road Reactance, The reactive power flowing through branch jm, For the scene Next node exist Reactive power of load at any given time For the scene Next node exist Reactive power of power supply at any given time For nodes susceptance;

[0146] In equation (24), Let be the square of the voltage at node j at time t in scenario s, i.e. , Let be the square of the voltage at node i , Let be the lower limit of the allowable voltage value at node j. Let be the upper limit of the allowable voltage value for node j. Let the square of the current in branch ij be... .

[0147] Further relax the coupling constraints of node voltage, branch current, and power (the last line of Equation 24) into the form of a rotating second-order cone, expressed by the following equation:

[0148] (25)

[0149] The standard second-order cone form of the above equation is:

[0150] , (26).

[0151] Step 3.4: Set the power balance constraints for users, expressed by the following formula:

[0152] ,(27)

[0153] In equation (27), Let s be the net load of user n at time t in scenario s. For users In the scene Down The original load at any given moment, For users In the scene Down The power generation capacity of distributed generation is always available. This is the maximum net load power (monthly setpoint).

[0154] This embodiment takes into account the lifespan of energy storage on the distribution network side and the lifespan of energy storage on the user side, making the configuration result more consistent with the actual physical laws and long-term operating status of energy storage equipment, thereby enhancing the accuracy of the planning scheme and its application value in actual engineering.

[0155] Step 4: Solve the objective function and constraints using an iterative method with embedded mixed-integer linear programming to obtain the optimal configuration capacity of energy storage on the distribution network side and the user side, as well as the optimal access point scheme for energy storage on the distribution network side.

[0156] The nonlinear terms in the above model are analyzed. When the distribution network energy storage lifetime, the user-side energy storage lifetime, and the distribution network energy storage access point are constants, this model degenerates into a mixed-integer linear programming model. Therefore, an iterative method nested with mixed-integer linear programming can be used to solve it.

[0157] Step 4-a: Initialize the lifetime of distribution network-side energy storage, the lifetime of user-side energy storage, and the access point of distribution network-side energy storage;

[0158] Step 4-b: Using the lifetime of energy storage on the distribution network side, the lifetime of energy storage on the user side, and the access point of energy storage on the distribution network side as known quantities, call the mixed integer linear programming solver to solve for the configuration capacity of energy storage on the distribution network side and the user side.

[0159] Step 4-c: Based on the solution results, update the lifetime of distribution network-side energy storage, the lifetime of user-side energy storage, and the access point of distribution network-side energy storage;

[0160] Step 4-d: Repeat steps 4-b and 4-c until the iteration termination condition is met, and output the final optimized configuration capacity of energy storage on the distribution network side and the user side, and the optimal access point for energy storage on the distribution network side.

[0161] In this embodiment, when the iterative algorithm is selected as particle swarm optimization, the specific solution process is as follows:

[0162] 1) Initialize the particle swarm optimization algorithm parameters and randomly generate an initial population. Each particle contains three variables: distribution network energy storage access point, distribution network-side energy storage lifetime, and user-side energy storage lifetime.

[0163] 2) The fitness function is called to calculate the configuration cost of each particle. The fitness function calls the mixed integer linear programming solver to determine the rated power, capacity and charging and discharging strategy of energy storage on the distribution network side / user side, thereby obtaining the objective function value, which is the fitness value in the particle swarm algorithm.

[0164] 3) Update the particle's velocity and position based on the fitness value;

[0165] 4) Repeat steps 2)-3) until the convergence condition is met, output the lifetime parameters and the final optimized configuration capacity of energy storage on the distribution network side and the user side, and the optimal access point for energy storage on the distribution network side.

[0166] This embodiment ultimately obtains the specific capacity of energy storage on the distribution network side and the user side, as well as the clear access location of energy storage on the distribution network side. It can provide a technical basis for the planning and construction of energy storage systems and help to achieve the rational layout and efficient utilization of energy storage in the distribution network.

[0167] Example 2:

[0168] Based on the energy storage cooperative configuration optimization method for distribution networks and users provided in Example 1, this example example is for a 16-node distribution network system with a base voltage of 10kV and a base capacity of 10MVA. The line parameters are shown in Table 1.

[0169] Table 1 Line Parameters

[0170]

[0171] The users participating in the cooperative configuration are large industrial users connected to nodes 12, 14, and 16. The photovoltaic power station is connected to the distribution network via node 7. The unit capacity configuration cost of energy storage is 2234 yuan / kWh, the unit power configuration cost is 1173 yuan / kW, the energy storage charge and discharge efficiency is 90%, and the minimum and maximum values ​​of state of charge are set to 0.1 and 0.9, respectively. The peak-hour (10:00–15:00, 18:00–21:00), normal-hour (7:00–10:00, 15:00–18:00, 21:00–24:00), and off-hour (24:00–7:00) electricity prices are RMB 1.0697 / kWh, RMB 0.6418 / kWh, and RMB 0.3139 / kWh, respectively, while the demand-based electricity price is RMB 48 / kWh. The particle swarm optimization algorithm is set to a population size of 20 and an evolution count of 100. The distribution network-side energy storage configuration is 2.11MW / 7.13MWh with an optimal lifetime of 10 years; the user-side energy storage configuration is 12MW / 86MWh with an optimal lifetime of 9.74 years, and the total annual cost is RMB 2.17 × 10⁸.

[0172] Three comparison scenarios were set up, and the energy storage configuration results under multiple scenarios are shown in Table 2.

[0173] Scenario 1: Neither the distribution network nor the users have installed energy storage;

[0174] Scenario 2: Multi-user collaborative configuration of energy storage without considering the integration of energy storage into the distribution network;

[0175] Scenario 3: The method provided in Example 1, in which the distribution network and users cooperate to configure energy storage.

[0176] Table 2 Energy storage configuration results in multiple scenarios

[0177]

[0178] As shown in Table 2, collaborative configuration can effectively reduce distribution network losses and user energy costs. Compared to schemes that only configure energy storage for multiple users without considering the distribution network, the method provided in Example 1 has significant economic advantages. Furthermore, since the method provided in Example 1 considers the energy storage lifetime under differentiated service provisioning, it avoids modeling deviations from reality due to lifetime settings that are too low or too high.

[0179] Example 3:

[0180] This embodiment provides a computer-readable storage medium storing a computer program / instruction. When the computer program / instruction is executed by a processor, it implements the steps of the energy storage cooperative configuration optimization method for distribution networks and users described in Embodiment 1.

[0181] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0182] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0183] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0184] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0185] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for optimizing the collaborative configuration of energy storage for distribution networks and users, characterized in that, include: Establish a collaborative energy storage system model that includes distribution network-side energy storage and user-side energy storage serving multiple users; Construct an objective function that minimizes the sum of the cost of the collaborative energy storage system, the network loss cost of the distribution network, and the user's energy consumption cost, and set the operating constraints of the collaborative energy storage system, the power flow security constraints of the distribution network, and the power balance constraints of the user; The cost of the collaborative energy storage system includes configuration costs, which are based on the one-time investment costs of the rated power of the distribution network-side energy storage, the one-time investment costs of the rated capacity of the distribution network-side energy storage, the one-time investment costs of the rated power of the user-side energy storage, the one-time investment costs of the rated capacity of the user-side energy storage, and a capital recovery coefficient related to the energy storage lifespan. The capital recovery coefficient related to the energy storage lifespan is determined based on the lifespans of the distribution network-side and user-side energy storage and the discount rate, and is obtained through the following formula: ，（8）， In equation (8), The one-time investment cost for user-side energy storage is converted into an equivalent annual return on investment factor. The one-time investment cost of energy storage on the distribution network side is converted into an equivalent annual return on investment factor. The discount rate is... For user-side energy storage lifespan, For the lifespan of energy storage on the distribution network side; The operational constraints of the collaborative energy storage system include: operational constraints of user-side energy storage and operational constraints of distribution network-side energy storage in the collaborative energy storage system; The operational constraints of user-side energy storage in the collaborative energy storage system include: The lifetime constraints of user-side energy storage include the total effective discharge being limited by the theoretical discharge calculated based on the rated cycle number and rated discharge depth; The operational constraints of the distribution network-side energy storage in the collaborative energy storage system include: The lifespan constraints of energy storage on the distribution network side include the total effective discharge capacity being limited by the theoretical discharge capacity calculated based on the rated cycle number and rated discharge depth; An iterative method with embedded mixed-integer linear programming is used to solve the objective function and constraints, resulting in the optimal configuration capacity of energy storage on the distribution network side and the user side, as well as the optimal access point scheme for energy storage on the distribution network side. The method of solving the objective function and constraints by embedding a mixed-integer linear programming approach using an iterative method includes: Step a: Initialize the distribution network-side energy storage lifetime, the user-side energy storage lifetime, and the access point of the distribution network-side energy storage; Step b: Using the distribution network-side energy storage lifetime, the user-side energy storage lifetime, and the access point of the distribution network-side energy storage as known quantities, call the mixed integer linear programming solver to solve the objective function and constraints, and obtain the configuration capacity of distribution network-side and user-side energy storage. Step c: Based on the solution results, update the distribution network-side energy storage lifetime, the user-side energy storage lifetime, and the access point of the distribution network-side energy storage; Step d: Repeat steps b and c until the iteration termination condition is met, and output the final optimized configuration capacity of energy storage on the distribution network side and the user side, and the optimal access point for energy storage on the distribution network side.

2. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 1, characterized in that, The collaborative energy storage system model satisfies: The total rated power of the collaborative energy storage system model is the sum of the rated power of the distribution network-side energy storage and the rated power of the user-side energy storage; The total rated capacity of the collaborative energy storage system model is the sum of the rated capacity of energy storage on the distribution network side and the rated capacity of energy storage on the user side. The allocation of charging and discharging power obtained by each user from user-side energy storage is limited by the rated power of user-side energy storage; The charging and discharging power of energy storage on the distribution network side is limited by the rated power of energy storage on the distribution network side at various times and in various scenarios.

3. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 1, characterized in that, The cost of the collaborative energy storage system includes operation and maintenance costs; The operation and maintenance cost is calculated based on the rated power of the collaborative energy storage system and the unit operation and maintenance cost.

4. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 1, characterized in that, The distribution network loss cost is calculated based on branch current, branch resistance, unit loss cost, and operating scenario duration; the user energy cost includes power cost and energy cost. The power cost is calculated based on power price, maximum net load power, and operating scenario duration. The energy cost is calculated based on the electricity price per unit, net load power, and operating duration.

5. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 1, characterized in that, The operational constraints of the collaborative energy storage system include: The overall installation power limit and capacity limit constraints of the collaborative energy storage system; The operational constraints of user-side energy storage and distribution network-side energy storage in the collaborative energy storage system.

6. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 5, characterized in that, The operational constraints of user-side energy storage in the collaborative energy storage system include: Non-negative constraint on the charging and discharging power of user-side energy storage; User-side energy storage is subject to mutual exclusion constraints on its charging and discharging states at any given time. The charging and discharging power of user-side energy storage is limited by both the rated power and the charging and discharging status flag. The dynamic balance constraint of user-side energy storage means that the remaining power at the current moment is determined by the remaining power at the previous moment and the current total charge / discharge. The remaining energy capacity of user-side energy storage is maintained within the range determined based on the rated capacity and the upper and lower limits of the state of charge. The lifetime constraints of user-side energy storage include the total effective discharge being limited by the theoretical discharge calculated based on the rated number of cycles and the rated depth of discharge.

7. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 5, characterized in that, The operational constraints of the distribution network-side energy storage in the collaborative energy storage system include: The charging and discharging states of energy storage on the distribution network side are mutually exclusive at any given time. The charging and discharging power of energy storage on the distribution network side is limited by both the rated power and the charging and discharging status flag. The dynamic balance constraint of energy storage on the distribution network side means that the remaining energy at the current moment is determined by the remaining energy at the previous moment and the charging / discharging amount at the current moment. The remaining energy capacity of the energy storage on the distribution network side is maintained within a range determined based on its rated capacity and upper and lower limits of state of charge; The lifespan constraints of energy storage on the distribution network side include the total effective discharge capacity being limited by the theoretical discharge capacity calculated based on the rated number of cycles and the rated depth of discharge.

8. The energy storage cooperative configuration optimization method for distribution networks and users according to claim 5, characterized in that, The power flow security constraints of the distribution network include: node power balance constraints, node voltage security limit constraints, and coupling constraints of node voltage, branch current, and power.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the energy storage cooperative configuration optimization method for distribution networks and users as described in any of claims 1-8.

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