Optimization planning method for demand response load in power distribution network

Abstract

The invention relates to the technical field of demand response load planning, in particular to an optimization planning method for demand response loads in a power distribution network, the response time and response capacity of the demand response loads are obtained through the optimization planning method, and a linear planning model with the aim of minimizing the comprehensive economic cost of the whole society is provided. The response time and capacity of the demand response load are optimized, and the operation mode of the energy storage system configured at the user side is optimized, so that the electricity purchase cost is reduced, the load peak value is reduced, the scheduling strategy of flexible resources is embodied, the optimal operation of the demand response load in the source-network-load-storage comprehensive power distribution system is realized, and the power consumption is reduced. The economical efficiency of the system is improved, peak load shifting is further achieved, and the problem of power supply tension is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of demand response load planning, and in particular to an optimization planning method for demand response loads in a distribution network. Background Art

[0002] With the continuous advancement of global energy transformation and power market reform, demand response load planning has become an important part of power system management. Demand response can alleviate the pressure on power supply by shaving peaks and filling valleys, especially during the peak electricity consumption period in summer and winter, and reduce power rationing caused by power shortages; secondly, demand response helps promote the consumption of renewable energy, and by flexibly adjusting the load curve, it can better match the output characteristics of fluctuating power sources such as wind power and photovoltaics, and improve the utilization rate of new energy power generation. In the context of dynamic changes in power supply and demand, how to effectively utilize demand-side resources and achieve the stability and economy of the power grid through reasonable load planning and management has become an urgent problem to be solved.

[0003] In the study of demand response load planning on the distribution network side, a linear programming model with the goal of minimizing the comprehensive economic cost of the whole society was proposed. It not only optimizes the response time and capacity of the demand response load, but also optimizes the operation mode of the energy storage system configured on the user side to reduce the electricity purchase cost and reduce the load peak. It reflects the scheduling strategy of flexible resources and realizes the optimal operation of the demand response load under the "source-grid-load-storage" integrated distribution system. Summary of the invention

[0004] The purpose of the present invention is to provide an optimization planning method for demand response loads in a distribution network to solve the problems raised in the above-mentioned background technology. By planning the demand response loads, the advantages of the demand response loads and the energy storage system are fully utilized to further achieve peak shaving and valley filling, thereby alleviating the problem of power supply shortage.

[0005] To achieve the above object, the present invention provides the following technical solution: an optimization planning method for demand response load in a distribution network, which obtains the response time and response capacity of the demand response load in the "source-grid-load-storage" integrated distribution system through the optimization planning method, characterized in that the optimization planning method includes the following steps: S1. According to the “source-grid-load-storage” integrated distribution system, i.e. the selected distribution network model, the line parameters, load parameters, system reference voltage, reference power initial value, capacity of the energy storage system, new energy output and other information are loaded respectively; S2. Describe the operation mode of the demand response load. According to the information such as the number, capacity and response time of the demand response load, construct a demand response load operation model including shiftable load and interruptible load. The main decision variables are response time and response capacity. S3. Based on the “source-grid-load-storage” integrated distribution system, with the goal of minimizing the comprehensive economic cost of the whole society, including the total cost of demand response expenditure, the user’s electricity purchase cost, the network loss cost during the power transmission process of the distribution network, and the maintenance cost of the energy storage system and the new energy generator set, a linear model of the objective function is established; S4. According to the operation mode of the distribution system, a grid-side operation model is constructed, including node voltage constraints, power flow equation constraints, and branch current constraints; S5. Construct an energy storage operation model based on the characteristics of the energy storage system, including charge and discharge state constraints, charge state change constraints, and charge and discharge power constraints; S6. Based on the above optimization objectives and constraints, the Matlab+Yalmip+Cplex solver is used to obtain the response mode of the demand response load under the "source-grid-load-storage" integrated distribution system.

[0006] As a preferred technical solution of the present invention, in S2, the response model expressions of the shiftable load response and the interruptible load response are: (1) Translable load In the formula, , are the powers of the ith ML before and after the response in time period t; the shiftable load can be moved in and out. From the perspective of load movement, is the operating power in period t before the i-th ML responds; is an auxiliary variable that reflects the operating power of the i-th ML in a certain period before the response; is the starting running time after the i-th ML response; is the duration of the continuous operation of the i-th ML; t0 is the time auxiliary variable; [ , ]、[ , ] are the time ranges that can be run before and after the i-th ML response, respectively.

[0007] (2) Interruptible load The reduction of IL should be within a certain range, namely: In the formula, is the power cut after the i-th IL responds in period t; The state variable of the interruptible load in time period t can be 0 or 1. 1 means the load is reduced, otherwise it does not participate in the reduction; [ , ] is the time range in which the i-th IL can participate in the response; is the operating power of the i-th IL in period t; , are the upper and lower limits of the proportion that can be reduced for the i-th IL.

[0008] As a preferred technical solution of the present invention, in S3, the comprehensive economic cost of the whole society is expressed as: In the formula, CDR is the total cost of demand response expenditure; Cbuy is the electricity purchase cost of the distribution network; Closs is the network loss cost during the power transmission process of the distribution network; Cess,om and CnewG,om are the maintenance costs of the energy storage system and the new energy generator set respectively. The specific expressions of each component are as follows: (1) Demand response costs Grid companies provide users with certain subsidies based on the type of demand response load and the compensation method for interrupted power. The specific expenditure costs are shown in the following formula: Where CML and CIL are the costs of shiftable load and interruptible load participating in demand response respectively; cML and cIL are the costs of shiftable load and interruptible load participating in demand response per unit of electricity respectively.

[0009] (2) Power purchase cost Where Ni is the number of distribution network nodes, is the power consumed by the i-th node in period t; is the unit price of electricity purchased during period t, is the length of a typical daily cycle, which is 24h; is the simulation step length, which is 1h.

[0010] (3) Network loss cost Where Iij is the current of the branch from node i to node j; Rij is the resistance of the branch from node i to node j; closs is the unit network loss cost.

[0011] (4) Energy storage maintenance costs Where Ness is the number of energy storage systems; and are the charging power and discharging power of the i-th energy storage system in period t respectively; cess is the maintenance cost per unit charge and discharge of energy storage.

[0012] (5) Maintenance cost of new energy units Where NPV is the number of photovoltaic units; NW is the number of wind turbines; is the output of the i-th photovoltaic unit in period t; is the output of the i-th wind turbine in period t; cnewG is the maintenance cost per unit of power generation of the new energy unit.

[0013] As a preferred technical solution of the present invention, in S4, according to the operation mode of the power distribution system, the grid side operation model expression is: (1) Node voltage constraints Where Uimin and Uimax are the lower and upper limits of the voltage Ui at the i-th node, respectively; n is the total number of distribution network nodes.

[0014] (2) Power flow equation constraints (must be satisfied in any time period, the time subscript t is omitted here) Where PG,i, QG,i are the active and reactive outputs of the power source at node i, respectively; PL,i, QL,i are the active and reactive loads at node i, respectively; Ui, Uj are the voltage amplitudes at nodes i and j, respectively; Gij, Bij are the real and imaginary parts of the node admittance matrix elements, respectively; is the voltage phase angle difference between node i and node j.

[0015] (3) Branch current constraints Where Iijmax is the upper limit of the current Iij of the i-th branch; d is the total number of branches.

[0016] As a preferred technical solution of the present invention, in S5, an energy storage operation model is constructed according to the characteristics of the energy storage system, and its expression is: The energy storage system cannot be charged and discharged at the same time: State of charge during the charging process: State of charge during discharge process: In the formula, represents the remaining power level of BESS at time t; It represents the hourly loss rate of the remaining power of BESS, referred to as the self-discharge rate, % / h; α and β represent the charging and discharging efficiency of BESS respectively; Ei,e is the capacity of BESS.

[0017] The charging and discharging power of the battery has certain constraints during the charging and discharging process, as shown in the following formula: In the formula, is the charging or discharging power at time t; represents the rated power of the i-th energy storage system; , are all 0-1 decision variables, 1 or 0 respectively indicates that the energy storage is charged or not charged during period t. 1 or 0 indicates that the energy storage is discharged or not discharged during time period t, respectively.

[0018] The life of BESS is greatly affected by the depth of discharge, and the power needs to be controlled within a certain range. The specific details are shown in the following formula: Where Socmin and Socmax are the minimum remaining power level and the maximum remaining power level of the battery respectively.

[0019] As a preferred technical solution of the present invention, in S6, this planning problem includes discrete variables such as the charging and discharging state of energy storage, and can be classified as a mixed integer linear programming problem. The Matlab+Yalmip+Cplex solver is used to obtain the response mode of the demand response load under the "source-grid-load-storage" integrated distribution system.

[0020] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention is an optimization planning method for demand response loads in a distribution network. The present invention proposes a linear programming model with the goal of minimizing the comprehensive economic cost of the whole society. It not only optimizes the response time and capacity of the demand response load, but also optimizes the operation mode of the energy storage system configured on the user side to reduce the electricity purchase cost and reduce the load peak. It embodies the scheduling strategy of flexible resources and realizes the optimal operation of the demand response load under the "source-grid-load-storage" integrated distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A flow chart of an optimization planning method for demand response loads in a distribution network; Figure 2 The schematic diagram of the algorithm flow of the application example of the optimization planning method of demand response load in the distribution network; Figure 3 A comparison chart of the economic results of the optimal planning method for demand response loads in the distribution network and other optimization methods applied to the distribution system; Figure 4 A comparison chart of the net load curves of the demand response load optimization planning method in the distribution network and other optimization methods applied to the distribution system; Figure 5 This is a schematic diagram of the IEEE33 node power distribution system; Figure 6 The output of photovoltaic and wind power in the distribution system; Figure 7 is the translatable load response state of the method proposed in this paper; Figure 8 It is the interruptible load response state of the method proposed in this paper. DETAILED DESCRIPTION

[0023] Below, the invention is further described in conjunction with the accompanying drawings and specific embodiments: See also Figure 1-8 According to an optimization planning method for demand response load in a distribution network according to an embodiment of the present invention, the response time and response capacity of the demand response load in the "source-grid-load-storage" integrated distribution system are obtained by the optimization planning method, and the optimization planning method is characterized in that the optimization planning method includes the following steps: S1. According to the “source-grid-load-storage” integrated distribution system, i.e. the selected distribution network model, the line parameters, load parameters, system reference voltage, reference power initial value, capacity of the energy storage system, new energy output and other information are loaded respectively; S2. Describe the operation mode of the demand response load. According to the information such as the number, capacity and response time of the demand response load, construct a demand response load operation model including shiftable load and interruptible load. The main decision variables are response time and response capacity. S3. Based on the “source-grid-load-storage” integrated distribution system, with the goal of minimizing the comprehensive economic cost of the whole society, including the total cost of demand response expenditure, the user’s electricity purchase cost, the network loss cost during the power transmission process of the distribution network, and the maintenance cost of the energy storage system and the new energy generator set, a linear model of the objective function is established; S4. According to the operation mode of the distribution system, a grid-side operation model is constructed, including node voltage constraints, power flow equation constraints, and branch current constraints; S5. Construct an energy storage operation model based on the characteristics of the energy storage system, including charge and discharge state constraints, charge state change constraints, and charge and discharge power constraints; S6. Based on the above optimization objectives and constraints, the Matlab+Yalmip+Cplex solver is used to obtain the response mode of the demand response load under the "source-grid-load-storage" integrated distribution system.

[0024] 2. The demand response load operation model according to claim 1, characterized in that: In S2, the response model expressions of the shiftable load response and the interruptible load response are: (1) Translable load In the formula, , are the powers of the ith ML before and after the response in time period t; the shiftable load can be moved in and out. From the perspective of load movement, is the operating power in period t before the i-th ML responds; is an auxiliary variable that reflects the operating power of the i-th ML in a certain period before the response; is the starting running time after the i-th ML response; is the duration of the continuous operation of the i-th ML; t0 is the time auxiliary variable; [ , ]、[ , ] are the time ranges that can be run before and after the i-th ML response, respectively.

[0025] (2) Interruptible load The reduction of IL should be within a certain range, namely: In the formula, is the power cut after the i-th IL responds in period t; The state variable of the interruptible load in time period t can be 0 or 1. 1 means the load is reduced, otherwise it does not participate in the reduction; [ , ] is the time range in which the i-th IL can participate in the response; is the operating power of the i-th IL in period t; , are the upper and lower limits of the proportion that can be reduced for the i-th IL.

[0026] 3. The method for optimizing planning of demand response load in distribution network according to claims 1 and 2, characterized in that: In S3, the comprehensive economic cost of the whole society is expressed as: In the formula, CDR is the total cost of demand response expenditure; Cbuy is the electricity purchase cost of the distribution network; Closs is the network loss cost during the power transmission process of the distribution network; Cess,om and CnewG,om are the maintenance costs of the energy storage system and the new energy generator set respectively. The specific expressions of each component are as follows: (1) Demand response costs Grid companies provide users with certain subsidies based on the type of demand response load and the compensation method for interrupted power. The specific expenditure costs are shown in the following formula: Where CML and CIL are the costs of shiftable load and interruptible load participating in demand response respectively; cML and cIL are the costs of shiftable load and interruptible load participating in demand response per unit of electricity respectively.

[0027] (2) Power purchase cost Where Ni is the number of distribution network nodes, is the power consumed by the i-th node in period t; is the unit price of electricity purchased during period t, is the length of a typical daily cycle, which is 24h; is the simulation step length, which is 1h.

[0028] (3) Network loss cost Where Iij is the current of the branch from node i to node j; Rij is the resistance of the branch from node i to node j; closs is the unit network loss cost.

[0029] (4) Energy storage maintenance costs Where Ness is the number of energy storage systems; and are the charging power and discharging power of the i-th energy storage system in period t respectively; cess is the maintenance cost per unit charge and discharge of energy storage.

[0030] (5) Maintenance cost of new energy units Where NPV is the number of photovoltaic units; NW is the number of wind turbines; is the output of the i-th photovoltaic unit in period t; is the output of the i-th wind turbine in period t; cnewG is the maintenance cost per unit of power generation of the new energy unit.

[0031] 4. The method for optimizing planning of demand response load in distribution network according to claim 1, characterized in that: In S4, according to the operation mode of the power distribution system, the grid side operation model expression is: (1) Node voltage constraints Where Uimin and Uimax are the lower and upper limits of the voltage Ui at the i-th node, respectively; n is the total number of distribution network nodes.

[0032] (2) Power flow equation constraints (must be satisfied in any time period, the time subscript t is omitted here) Where PG,i, QG,i are the active and reactive outputs of the power source at node i, respectively; PL,i, QL,i are the active and reactive loads at node i, respectively; Ui, Uj are the voltage amplitudes at nodes i and j, respectively; Gij, Bij are the real and imaginary parts of the node admittance matrix elements, respectively; is the voltage phase angle difference between node i and node j.

[0033] (3) Branch current constraints Where Iijmax is the upper limit of the current Iij of the i-th branch; d is the total number of branches.

[0034] 5. The method for optimizing planning of demand response load in distribution network according to claim 1, characterized in that: In S5, an energy storage operation model is constructed according to the characteristics of the energy storage system, and its expression is: The energy storage system cannot be charged and discharged at the same time: State of charge during the charging process: State of charge during discharge process: In the formula, represents the remaining power level of BESS at time t; It represents the hourly loss rate of the remaining power of BESS, referred to as the self-discharge rate, % / h; α and β represent the charging and discharging efficiency of BESS respectively; Ei,e is the capacity of BESS.

[0035] The charging and discharging power of the battery has certain constraints during the charging and discharging process, as shown in the following formula: In the formula, is the charging or discharging power at time t; represents the rated power of the i-th energy storage system; , are all 0-1 decision variables, 1 or 0 respectively indicates that the energy storage is charged or not charged during period t. 1 or 0 indicates that the energy storage is discharged or not discharged during time period t, respectively.

[0036] The life of BESS is greatly affected by the depth of discharge, and the power needs to be controlled within a certain range. The specific details are shown in the following formula: Where Socmin and Socmax are the minimum remaining power level and the maximum remaining power level of the battery respectively.

[0037] 6. The method for optimizing planning of demand response load in distribution network according to claim 1, characterized in that: In S6, this planning problem includes discrete variables such as the charging and discharging state of energy storage, which can be classified as a mixed integer linear programming problem. The Matlab+Yalmip+Cplex solver is used to obtain the response mode of the demand response load under the "source-grid-load-storage" integrated distribution system; In this embodiment, an operation optimization method of a "source-grid-load-storage" integrated power distribution system is implemented to reduce peak loads and fill valleys, thereby alleviating the power supply pressure of the power grid, including: The first step is to input data of the "source, grid, load and storage" integrated distribution system, including line parameters, load parameters, system reference voltage, initial reference power value, capacity of the energy storage system and new energy output.

[0038] Step 2: Establish an optimization planning model for demand response loads in distribution networks.

[0039] (1) Based on the quantity, capacity, and response time of the demand response load, a demand response load operation model including shiftable loads and interruptible loads is constructed.

[0040] (2) Based on the “source-grid-load-storage” integrated distribution system, with the goal of minimizing the comprehensive economic cost of the whole society, a linear model of the objective function is established, which includes the total cost of demand response expenditure, the user's electricity purchase cost, the network loss cost during the power transmission process of the distribution network, and the maintenance cost of the energy storage system and new energy generators.

[0041] (3) According to the operation mode of the distribution system of IEEE33 nodes, a grid-side operation model is constructed, which includes node voltage constraints, power flow equation constraints, and branch current constraints.

[0042] (4) Based on the characteristics of the energy storage system, an energy storage operation model is constructed, including charging and discharging state constraints, charge state change constraints, and charging and discharging power constraints.

[0043] Step 3: Model solving. According to the characteristics of the planning model, Matlab+Yalmip+Cplex solver is selected for solving to obtain the response mode and economic cost of the demand response load under the "source-grid-load-storage" integrated distribution system.

[0044] Step 4: Compare the economic results of different optimization schemes and the effects of achieving peak shaving and valley filling.

[0045] The demand response load planning method of this embodiment is applied to the power distribution system. Figure 3 and Figure 4 They are the economic results and net load curves under different optimization scenarios, with a total of 2 scenarios, specifically: Solution 1: Conduct demand response load planning during the operation of the “source-grid-load-storage” integrated distribution system; Option 2: No demand response load planning is performed during the operation of the “source-grid-load-storage” integrated distribution system; From the above results, it can be seen that the use of this optimization method to plan demand response loads can reduce the economic cost of the system, achieve peak shaving and valley filling, and alleviate the problem of power supply shortage.

[0046] In specific applications, the schematic diagram of the IEEE 33 node power distribution system in the present invention is as follows: Figure 5 This system includes two wind turbines, 300kW at node 15 and 400kW at node 26; and one photovoltaic unit, 500kW at node 5. The output of photovoltaic and wind power is shown in Figure 6This system also includes two energy storage systems, 800kWh at node 17 and 500kWh at node 24, with a rated power and energy storage capacity ratio of 0.3. There are three load shifting locations, ML1 at node 4, ML2 at node 15, and ML3 at node 30. There are two load interruption locations, IL1 at node 29 and IL2 at node 24.

[0047] The economic results under each scenario are obtained as follows Figure 3 As shown, the net load result is Figure 4 As shown. Figure 3 It can be seen that because scenario 1 takes into account the planned operation of demand response loads, the total operating cost is reduced by 1,187.5 yuan compared to scenario 2. Specifically, the cost of demand response is 1,110.5 yuan, but the reduction in electricity purchase costs is enough to cover the demand response costs. In addition, after the flexible load response, the network loss cost of the distribution network also decreased, and the maintenance cost of the energy storage unit and the new energy unit did not change. In general, planning demand response loads improves the economy of system operation. Figure 4 It can be seen that after the introduction of demand response load, the load during peak electricity price periods has been effectively reduced, because the shiftable load has been transferred to periods with relatively low electricity prices, and the interruptible load has been directly reduced, which has a certain peak-shaving and valley-filling effect and alleviates the operating pressure of the distribution network.

[0048] The response states of the movable load and interruptible load in scenario 1 are as follows: Figure 7 and Figure 8 As shown. The total amount of electricity that can be transferred by load translation is 1005kWh, and the total amount of electricity that can be reduced by load interruption is 1172.9kWh. Figure 7 It can be seen that in order to ensure the economical operation of the system, all the shiftable loads are transferred from the period with higher electricity prices (peak period of electricity load) to the period with relatively more low electricity prices, thereby reducing the peak period of electricity load and electricity purchase cost. Figure 8 It can be seen that the periods of load reduction are all periods with higher electricity prices. Due to the constraints on the number of load reduction periods, choosing to reduce load during the period with the largest load can fully reduce the load and minimize the cost of purchasing electricity.

[0049] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An optimization planning method for demand response load in a distribution network, which obtains the response time and response capacity of the demand response load in the "source-grid-load-storage" integrated distribution system through the optimization planning method, characterized in that: The optimization planning method includes the following steps: S1. According to the "source-grid-load-storage" integrated distribution system, that is, the selected distribution network model, the line parameters, load parameters, system reference voltage, reference power initial value, energy storage system capacity, new energy output and other information are loaded respectively; S2. Describe the operation mode of the demand response load. According to the information such as the number, capacity and response time of the demand response load, construct a demand response load operation model including shiftable load and interruptible load. The main decision variables are response time and response capacity. S3. Based on the "source-grid-load-storage" integrated distribution system, with the goal of minimizing the comprehensive economic cost of the whole society, including the total cost of demand response expenditure, the user's electricity purchase cost, the network loss cost during the power transmission process of the distribution network, and the maintenance cost of the energy storage system and new energy generator sets, a linear model of the objective function is established; S4. According to the operation mode of the distribution system, a grid-side operation model is constructed, including node voltage constraints, power flow equation constraints, and branch current constraints; S5. Construct an energy storage operation model based on the characteristics of the energy storage system, including charge and discharge state constraints, charge state change constraints, and charge and discharge power constraints; S6. Based on the above optimization objectives and constraints, the Matlab+Yalmip+Cplex solver is used to obtain the response mode of the demand response load under the "source-grid-load-storage" integrated distribution system.

2. The demand response load operation model according to claim 1, characterized in that: In S2, the response model expressions of the shiftable load response and the interruptible load response are: (1) Translable load In the formula, , are the powers of the ith ML before and after the response in time period t; the shiftable load can be moved in and out. From the perspective of load movement, is the operating power in period t before the i-th ML responds; is an auxiliary variable that reflects the operating power of the i-th ML in a certain period before the response; is the starting running time after the i-th ML response; is the duration of the continuous operation of the i-th ML; t0 is the time auxiliary variable; [ , ]、[ , ] are the time ranges that can be run before and after the i-th ML response, respectively. (2) Interruptible load The reduction of IL should be within a certain range, namely: In the formula, is the power cut after the i-th IL responds in period t; The state variable of the interruptible load in time period t can be 0 or 1. 1 means the load is reduced, otherwise it does not participate in the reduction; [ , ] is the time range in which the i-th IL can participate in the response; is the operating power of the i-th IL in period t; , are the upper and lower limits of the proportion that can be reduced for the i-th IL.

3. The method for optimizing planning of demand response load in distribution network according to claims 1 and 2, characterized in that: In S3, the comprehensive economic cost of the whole society is expressed as: Where, the total cost of CDR demand response expenditure; Cbuy is the electricity purchase cost of the distribution network; Closs is the network loss cost during the power transmission process of the distribution network; Cess,om and CnewG,om are the maintenance costs of the energy storage system and the new energy generator set respectively. The specific expressions of each component are as follows: (1) Demand response costs Grid companies provide users with certain subsidies based on the type of demand response load and the compensation method for interrupted power. The specific expenditure costs are shown in the following formula: Where CML and CIL are the costs of shiftable load and interruptible load participating in demand response respectively; cML and cIL are the costs of shiftable load and interruptible load participating in demand response per unit of electricity respectively. (2) Power purchase cost Where Ni is the number of distribution network nodes, is the power consumed by the i-th node in period t; is the unit price of electricity purchased during period t, is the length of a typical daily cycle, which is 24h; is the simulation step length, which is 1h. (3) Network loss cost Where Iij is the current of the branch from node i to node j; Rij is the resistance of the branch from node i to node j; closs is the unit network loss cost. (4) Energy storage maintenance costs Where Ness is the number of energy storage systems; and are the charging power and discharging power of the i-th energy storage system in period t respectively; cess is the maintenance cost per unit charge and discharge of energy storage. (5) Maintenance cost of new energy units Where NPV is the number of photovoltaic units; NW is the number of wind turbines; is the output of the i-th photovoltaic unit in period t; is the output of the i-th wind turbine in period t; cnewG is the maintenance cost per unit of power generation of the new energy unit.

4. The method for optimizing planning of demand response loads in a distribution network according to claim 1, characterized in that: In S4, according to the operation mode of the power distribution system, the grid side operation model expression is: (1) Node voltage constraints In the formula, Uimin and Uimax are the lower limit and upper limit of the voltage Ui at the i-th node respectively; n is the total number of distribution network nodes. (2) Power flow equation constraints (must be satisfied in any time period, the time subscript t is omitted here) Where PG,i, QG,i are the active and reactive outputs of the power source at node i, respectively; PL,i, QL,i are the active and reactive loads at node i, respectively; Ui and Uj are the voltage amplitudes of nodes i and j respectively; Gij and Bij are the real and imaginary parts of the node admittance matrix elements respectively; is the voltage phase angle difference between node i and node j. (3) Branch current constraints Where Iijmax is the upper limit of the current Iij of the i-th branch; d is the total number of branches.

5. The method for optimizing planning of demand response load in a distribution network according to claim 1, characterized in that: In S5, an energy storage operation model is constructed according to the characteristics of the energy storage system, and its expression is: The energy storage system cannot be charged and discharged at the same time: State of charge during the charging process: State of charge during discharge process: In the formula, represents the remaining power level of BESS at time t; It represents the hourly loss rate of the remaining power of BESS, referred to as the self-discharge rate, % / h; α and β represent the charging and discharging efficiency of BESS respectively; Ei,e is the capacity of BESS. The charging and discharging power of the battery has certain constraints during the charging and discharging process, as shown in the following formula: In the formula, is the charging or discharging power at time t; represents the rated power of the i-th energy storage system; , are all 0-1 decision variables, 1 or 0 respectively indicates that the energy storage is charged or not charged during period t. 1 or 0 indicates that the energy storage is discharged or not discharged during time period t, respectively. The life of BESS is greatly affected by the depth of discharge, and the power needs to be controlled within a certain range. The specific details are shown in the following formula: Where Socmin and Socmax are the minimum remaining power level and the maximum remaining power level of the battery respectively.

6. The method for optimizing planning of demand response loads in a distribution network according to claim 1, characterized in that: In S6, this planning problem includes discrete variables such as the charging and discharging state of energy storage, and can be classified as a mixed integer linear programming problem. The Matlab+Yalmip+Cplex solver is used to obtain the response mode of the demand response load under the "source-grid-load-storage" integrated distribution system.

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