Power distribution network energy-saving control method and system, power distribution network and electronic equipment

Abstract

The invention discloses a power distribution network energy-saving control method and system, a power distribution network and electronic equipment, and relates to the technical field of power distribution networks. According to the method, acquired operation parameters of each node in the power distribution network are input into an energy-saving planning model which takes minimization of user power consumption cost and power distribution network electric energy loss as objective functions and meets preset constraint conditions, so that an energy storage charging and discharging control strategy which is output by the model and aims at each node is obtained; the preset constraint conditions comprise an electric quantity constraint, a node power balance constraint, a tail end voltage constraint, a branch current constraint and a node voltage upper limit and lower limit constraint, and finally controlling the nodes based on an energy storage charging and discharging control strategy. Therefore, the problem of unsatisfactory planning of the active power distribution system in the prior art is solved, and reasonable planning of the active power distribution system is realized by applying the energy storage charging and discharging control strategy determined by the energy-saving planning model which takes minimization of user power consumption cost and power distribution network electric energy loss as objective functions and meets the preset constraint conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution networks, and more specifically, to a power distribution network energy-saving control method, system, power distribution network and electronic equipment. Background Art

[0002] Large-scale centralized development of renewable energy for power generation is not only prone to grid load fluctuations, but may also increase the burden of power consumption, resulting in unnecessary power loss or waste, and is in urgent need of adjustment and optimization. Energy storage devices can store and release electricity through electrochemical principles, shaving peaks and filling valleys according to power consumption, and smoothing fluctuations, fundamentally improving the reliability and economic benefits of renewable energy grid connection.

[0003] The goal of traditional distribution network planning is to solve operational problems (such as capacity matching) at the planning stage, while active distribution system planning should comprehensively consider operational and control issues to achieve optimal technical and economic performance. However, with the transition from traditional distribution networks to active distribution systems, the current planning for active distribution systems is not ideal. Therefore, how to control the active distribution system to operate under the optimal solution, that is, to achieve optimal energy storage charging and discharging control, is an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide a distribution network energy-saving control method, system, distribution network and electronic equipment to solve the problem of unsatisfactory planning of active distribution systems in the prior art, and to achieve reasonable planning of active distribution systems by applying an energy storage charging and discharging control strategy determined by an energy-saving planning model that takes minimizing user electricity costs and distribution network power losses as objective functions and satisfies preset constraints.

[0005] In a first aspect, the present invention provides a power distribution network energy-saving control method, comprising:

[0006] Obtain the operating parameters of each node in the distribution network;

[0007] Inputting the operating parameters into an energy-saving planning model to obtain an energy storage charging and discharging control strategy for each of the nodes output by the energy-saving planning model;

[0008] Based on the energy storage charging and discharging control strategy, controlling the node;

[0009] Among them, the energy-saving planning model is a multi-objective optimization model with the objective function of minimizing the user's electricity cost and the power loss of the distribution network, and satisfying the preset constraints. The preset constraints include: power constraint, node power balance constraint, terminal voltage constraint, branch current constraint, node voltage upper and lower limit constraints.

[0010] In a preferred embodiment, the operating parameters include: the electricity purchase price Electricity sales price The line resistance r between node i and node k ik , the square of the line current from node i to node k at time t l t,ik , line reactance x between node i and node k ik And the square of the voltage v at node j at time t t,j .

[0011] In a preferred embodiment, the objective function is:

[0012] F(ω)=(1-ω)F1+ωF2

[0013]

[0014] Among them, ω is the weight coefficient, F1 and F2 are the user's electricity cost and the power loss of the distribution network respectively, and are the power purchase and sales of node k at time t, ΔT is the time interval, T is the preset time range, and E is the set of network branches in the distribution network.

[0015] In a preferred solution, the power constraint includes:

[0016]

[0017] in, is the active power exchange between the grid user at node k and the distribution network, and B is the node set of the grid user;

[0018] The node power balance constraint includes:

[0019]

[0020] Among them, P t,ik and Q t,ik are the active power and reactive power flowing between node i and node k on network branch l at time t, respectively. t,km and Q t,km are the active power and reactive power flowing between node k and node m on network branch l at time t, is the reactive power exchange between the building and the distribution network at node k at time t;

[0021] The terminal voltage constraint includes:

[0022]

[0023] Among them, V t,k and V t,iare the squares of the voltages of nodes k and i on network branch l at time t respectively;

[0024] The branch current constraint includes:

[0025]

[0026] Among them, v t,ik is the square of the voltage between node i and node k on network branch l at time t;

[0027] The node voltage upper and lower limit constraints include:

[0028]

[0029] Among them, v t,j is the square of the voltage at node j at time t, v j and are respectively a preset lower limit value and a preset upper limit value of the square of the voltage at the node j.

[0030] In a preferred solution, the node power balance constraint further includes:

[0031]

[0032] in, and are respectively the active power and reactive power generated by the battery in the grid user at node k at time t, and are respectively the active power and reactive power generated by the photovoltaic power generation unit in the grid user at node k at time t, is the reactive power exchange between the grid user at node k and the distribution network, and are respectively the active power and reactive power required by the load of the power grid user at node k at time t, and are the maximum apparent powers of the inverter of the photovoltaic power generation unit and the inverter of the battery, respectively, and are the power factor angles of the inverter of the photovoltaic power generation unit and the inverter of the battery respectively.

[0033] In a preferred solution, the preset constraint condition further includes: a power constraint of the battery;

[0034] The battery power constraints include:

[0035]

[0036] in, and are the state of charge of the battery at node k at time t and time t+1 respectively, is the self-consumption power of the battery at node k, and as well as and They are respectively the preset upper limit and lower limit of the state of charge and the active power generated by the battery.

[0037] In a preferred embodiment, the preset constraint condition further includes: a power loss constraint of the battery;

[0038] The battery power loss constraints include:

[0039]

[0040] in, and are the discharge loss and charge loss of the battery at time t, and are the discharge loss coefficient and the charge loss coefficient of the battery respectively, and are the charging efficiency and discharging efficiency of the battery respectively.

[0041] In a second aspect, the present invention provides a power distribution network energy-saving control system, comprising:

[0042] A parameter acquisition unit, used to obtain the operating parameters of each node in the distribution network;

[0043] A strategy acquisition unit, used for inputting the operating parameters into an energy-saving planning model to obtain an energy storage charging and discharging control strategy for each of the nodes output by the energy-saving planning model;

[0044] A strategy execution unit, configured to control the node based on the energy storage charging and discharging control strategy;

[0045] Among them, the energy-saving planning model is a multi-objective optimization model with the objective function of minimizing the user's electricity cost and the power loss of the distribution network, and satisfying the preset constraints. The preset constraints include: power constraint, node power balance constraint, terminal voltage constraint, branch current constraint, node voltage upper and lower limit constraints.

[0046] In a third aspect, the present invention provides a distribution network, which includes a distribution network body and a distribution network energy-saving control system as provided in the second aspect of the present invention.

[0047] In a fourth aspect, the present invention provides an electronic device, the electronic device comprising:

[0048] processor;

[0049] a memory for storing instructions executable by the processor;

[0050] The processor is used to execute the distribution network energy-saving control method provided by the first aspect of the present invention.

[0051] In order to achieve the above-mentioned purpose, the present invention provides a distribution network energy-saving control method, system, distribution network and electronic equipment, by inputting the acquired operating parameters of each node in the distribution network into an energy-saving planning model, and the energy-saving planning model is a multi-objective optimization model with minimizing the user's electricity cost and the distribution network's power loss as the objective function, and satisfies preset constraints, and the preset constraints include: power constraint, node power balance constraint, terminal voltage constraint, branch current constraint, node voltage upper limit and lower limit constraints, so that when each node is controlled based on the energy storage charging and discharging control strategy output by the energy-saving planning model, the technical and economic efficiency of the active distribution system during operation is guaranteed, and the reliability of the system is also guaranteed, thereby reducing the load fluctuation and power consumption burden of the distribution network, and avoiding unnecessary power loss or waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a structural diagram of a typical distribution network with multiple sources and loads.

[0053] Figure 2 A flow chart of a distribution network energy-saving control method provided for the implementation of the present invention.

[0054] Figure 3 A structural diagram of a power distribution network energy-saving control system provided by an embodiment of the present invention.

[0055] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention is further described in detail below through the accompanying drawings and specific embodiments.

[0057] It is understandable that large-scale centralized development of new energy power generation will not only easily cause fluctuations in the grid load, but may also increase the burden of electricity consumption, causing unnecessary power loss or waste. Figure 1 It is a typical distribution network structure with multiple sources and multiple loads. Figure 1As shown in the figure, the power generation unit includes photovoltaic distributed power generation units and traditional power generation units (power plants), and the loads mainly include household loads and industrial loads, in addition to battery energy storage units. Among them, the battery energy storage unit can store and release electric energy through electrochemical principles. Therefore, if the battery energy storage unit can be controlled to reduce peaks and fill valleys and smooth fluctuations according to the power consumption situation, the reliability and economic benefits of new energy grid connection can be fundamentally improved.

[0058] Based on this, the present invention provides an energy-saving planning model which takes the acquired operating parameters of the nodes in the distribution network as the input to minimize the user's electricity cost and the power loss of the distribution network as the objective function and satisfies the preset constraints, and then obtains the energy storage charging and discharging control strategy for the node from the energy-saving planning model. The obtained energy storage charging and discharging control strategy not only ensures the technical and economic feasibility of the active distribution system during operation, but also ensures the reliability of the system, thereby reducing the load fluctuation and power consumption burden of the distribution network and avoiding unnecessary power loss or waste.

[0059] The distribution network energy-saving control method provided by the present invention is executed on an electronic device, which may be a controller configured on the distribution network, or a controller independent of the distribution network, or an intelligent terminal device such as a laptop computer, a personal computer, and a tablet computer that can be connected to the distribution network. Of course, in some cases, it may also be a server on the network side.

[0060] like Figure 2 As shown, the power distribution network energy-saving control method provided by the embodiment of the present invention mainly includes the following steps:

[0061] 110. Obtain the operating parameters of each node in the distribution network.

[0062] Specifically, a node refers to the connection point between a power grid user and a distribution network. Each network branch may include multiple nodes.

[0063] Furthermore, the grid users corresponding to a node may include one or more of a photovoltaic power generation unit, a household load, an industrial load, and a battery.

[0064] Based on this, grid users can also be understood as a combination of photovoltaic power generation units, household loads, batteries, etc., and the node is the connection point between this combination and the distribution network.

[0065] Based on the content of the above embodiment, the operating parameters include: the electricity purchase price Electricity sales price The line resistance r between node i and node k ik , the square of the line current from node i to node k at time t l t,ik , line reactance x between node i and node kik And the square of the voltage v at node j at time t t,j .

[0066] Specifically, considering that the electricity purchase price and electricity sales price of power grid users to the distribution network directly affect the electricity consumption cost of power grid users, the line resistance and line reactance between nodes affect the loss of electric energy, and the line current and voltage between nodes are related to the power of the line, therefore, in this embodiment, the operating parameters of each node in the distribution network obtained include: the electricity purchase price, the electricity sales price, the line resistance between node i and node k, the square of the line current between node i and node k at time t, the line reactance between node i and node k, and the square of the voltage at node j at time t.

[0067] 120. Input the operating parameters into the energy-saving planning model to obtain the energy storage charging and discharging control strategy for each node output by the energy-saving planning model.

[0068] Among them, the energy-saving planning model is a multi-objective optimization model with the objective function of minimizing the user's electricity cost and the power loss of the distribution network and meeting the preset constraints.

[0069] Furthermore, the preset constraints include: power constraints, node power balance constraints, terminal voltage constraints, branch current constraints, and node voltage upper and lower limit constraints.

[0070] Specifically, in the active distribution system, many factors such as the amount of electricity purchased, the amount of electricity sold, and the balance of node power will affect the reliability and economy of the distribution network when new energy is connected to the grid. Therefore, by setting the energy-saving planning model as a multi-objective optimization model with the objective function of minimizing the user's electricity cost and the power loss of the distribution network, and satisfying the preset constraints such as power constraints, node power balance constraints, terminal voltage constraints, and branch current constraints, the optimal energy storage charging and discharging control strategy for the active distribution system can be transformed into a multi-objective combined optimization problem.

[0071] 130. Control the nodes based on the energy storage charging and discharging control strategy.

[0072] Specifically, by inputting the operating parameters into the energy-saving planning model and performing multi-objective optimization solution through the energy-saving planning model, the optimal energy storage charging and discharging control strategy for each node can be obtained. By controlling the nodes based on the energy storage charging and discharging control strategy, active distribution system planning is realized, and the user's electricity cost and the energy loss of the distribution network are reduced, thereby achieving the purpose of energy saving.

[0073] Based on the content of the above embodiment, the objective function is:

[0074] F(ω)=(1-ω)F1+ωF2 (1)

[0075]

[0076] Among them, ω is the weight coefficient, F1 and G2 are the user's electricity cost and the distribution network's power loss, respectively. and are the power purchase and sales of node k at time t, ΔT is the time interval, T is the preset time range, and E is the set of network branches in the distribution network.

[0077] Specifically, as shown in formula (2), by adjusting the amount of electricity purchased and sold by the grid user within a preset time range (e.g., 24 hours, 48 ​​hours, etc.), the user's electricity cost can be determined. As shown in formula (3), by considering the power loss caused by the power line when the grid user buys, the power loss of the distribution network can be determined.

[0078] More specifically, the weight coefficient in formula (1) can be flexibly set according to actual needs, that is, by setting the weight coefficient, the influence of the user's electricity cost and the distribution network's power loss on the determination of the energy storage charging and discharging control strategy can be determined.

[0079] Based on the content of the above embodiment, the power constraint includes:

[0080]

[0081] in, is the active power exchange between the grid user and the distribution network at node k, and B is the node set of the grid user;

[0082] Node power balance constraints include:

[0083]

[0084]

[0085] Among them, P t,ik and Q t,ik are the active power and reactive power flowing between node i and node k on network branch l at time t, respectively. t,km and Q t,km are the active power and reactive power flowing between node k and node m on network branch l at time t, is the reactive power exchange between the building and the distribution network at node k at time t;

[0086] Terminal voltage constraints include:

[0087]

[0088] Among them, V t,k and V t,iare the squares of the voltages of nodes k and i on network branch l at time t respectively;

[0089] Branch current constraints include:

[0090]

[0091] Among them, v t,ik is the square of the voltage between node i and node k on network branch l at time t;

[0092] The node voltage upper and lower limit constraints include:

[0093]

[0094] Among them, v t,j is the square of the voltage at node j at time t, v j and are respectively a preset lower limit value and a preset upper limit value of the square of the voltage at the node j.

[0095] In this embodiment, the active power and reactive power interacting between the power grid user and the distribution network are balanced and constrained respectively by formula (4) to formula (10), and the upper and lower limits of the terminal voltage, branch current and node voltage of the distribution network are constrained. At the same time, the power purchase and sales of the power grid user are constrained, and it is ensured that the power interacting between the power grid user and the distribution network is equal to the power purchase minus the power sales, thereby improving the accuracy of the determined energy storage charging and discharging control strategy, and further improving the reliability and stability of the distribution network operation.

[0096] Based on the content of the above embodiment, the node power balance constraint also includes:

[0097]

[0098] in, and are the active power and reactive power generated by the battery in the grid user at node k at time t, and are the active power and reactive power generated by the photovoltaic power generation unit of the grid user at node k at time t, is the reactive power exchange between the grid user and the distribution network at node k, and are respectively the active power and reactive power required by the load of the power grid user at node k at time t, and are the maximum apparent powers of the inverter of the photovoltaic power generation unit and the inverter of the battery, and They are the power factor angles of the inverter of the photovoltaic power generation unit and the inverter of the battery respectively.

[0099] In this embodiment, constraints are established based on the relationship between the power generated by the batteries and photovoltaic power generation units in the grid users, the power of the electricity purchased / sold by the grid users from the distribution network, and the power demand of the loads in the grid users, so that the determined energy storage charging and discharging control strategy can control the purchase / sale of electricity more reasonably, thereby reducing the electricity costs of the grid users.

[0100] Based on the content of the above embodiment, the preset constraint conditions also include: battery power constraint;

[0101] Battery capacity constraints include:

[0102]

[0103] in, and are the state of charge of the battery at node k at time t and time t+1, is the self-consumption power of the battery at node k, and as well as and They are the preset upper and lower limits of the state of charge and the active power output by the battery respectively.

[0104] In this embodiment, constraint conditions are established through the relationship between the remaining power of the battery at the current moment and the remaining power at the next moment after the current moment, the relationship between the remaining power of the battery and the preset limit of the remaining power of the battery, and the relationship between the power emitted by the battery and the preset limit of the active power emitted by the battery, so as to ensure the reliability and rationality of the determined energy storage charging and discharging control strategy for battery control.

[0105] Based on the content of the above embodiment, the preset constraint conditions also include: battery power loss constraint;

[0106] The power loss constraints of the battery include:

[0107]

[0108]

[0109] in, and are the discharge loss and charge loss of the battery at time t, and are the discharge loss coefficient and charging loss coefficient of the battery respectively, and are the charging efficiency and discharging efficiency of the battery respectively.

[0110] In this embodiment, constraint conditions are established through the relationship between the battery's discharge loss and output power, the relationship between the battery's charging loss and output power, and the relationship between the battery's charge and discharge loss coefficient and the charge and discharge efficiency, thereby further ensuring the reliability and rationality of the determined energy storage charge and discharge control strategy for battery control.

[0111] The distribution network energy-saving control system provided in an embodiment of the present invention is introduced below. The distribution network energy-saving control system described below can be considered as a module architecture for implementing the distribution network energy-saving control method provided in an embodiment of the present invention; the content described below can be cross-referenced with the above.

[0112] Optional, see Figure 3 , Figure 3 : is a structural block diagram of a distribution network energy-saving control system provided by an embodiment of the present invention, and the system may include:

[0113] The parameter acquisition unit 10 is used to obtain the operating parameters of each node in the distribution network;

[0114] A strategy acquisition unit 20, used to input the operating parameters into the energy-saving planning model to obtain the energy storage charging and discharging control strategy for each node output by the energy-saving planning model;

[0115] A strategy execution unit 30, used to control the node based on the energy storage charging and discharging control strategy;

[0116] Among them, the energy-saving planning model is a multi-objective optimization model with the objective function of minimizing the user's electricity cost and the power loss of the distribution network, and meeting the preset constraints. The preset constraints include: power constraint, node power balance constraint, terminal voltage constraint, branch current constraint, node voltage upper and lower limit constraints.

[0117] Optional, operating parameters include: power purchase price Electricity sales price The line resistance r between node i and node k ik , the square of the line current from node i to node k at time t l t,ik , line reactance x between node i and node k ik And the square of the voltage v at node j at time t t,j .

[0118] Optionally, the objective function includes formula (1) to formula (3).

[0119] Optionally, the power constraint includes formula (4) and formula (5); the node power balance constraint includes formula (6) and formula (7); the terminal voltage constraint includes formula (8); the branch current constraint includes formula (9); and the node voltage upper and lower limit constraints include formula (10).

[0120] Optionally, the node power balance constraint also includes formula (11) to formula (16).

[0121] Optionally, the preset constraint condition also includes a battery power constraint;

[0122] The battery power constraints include equations (17) to (19).

[0123] Optionally, the preset constraints also include a battery power loss constraint;

[0124] The power loss constraints of the battery include equations (20) to (24).

[0125] Optionally, an embodiment of the present invention further provides a distribution network, including a distribution network body and a distribution network energy-saving control system as provided in any of the above embodiments.

[0126] Below, reference Figure 4 To describe the electronic device provided by the embodiment of the present application, the electronic device provided by the embodiment may include: at least one processor 100, at least one communication interface 200, at least one memory 300 and at least one communication bus 400;

[0127] In the embodiment of the present invention, the number of the processor 100, the communication interface 200, the memory 300, and the communication bus 400 is at least one, and the processor 100, the communication interface 200, and the memory 300 communicate with each other through the communication bus 400; obviously, Figure 4 The communication connections shown for the processor 100, the communication interface 200, the memory 300, and the communication bus 400 are merely optional;

[0128] Optionally, the communication interface 200 may be an interface of a communication module, such as an interface of a GSM module; the processor 100 may be a central processing unit CPU, or an application specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0129] The memory 300 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0130] The processor 100 is specifically used to execute the application program in the memory to implement the steps of the above-mentioned crane hoisting wire rope installation control method.

[0131] The above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A distribution network energy-saving control method, characterized in that: include: Obtain the operating parameters of each node in the distribution network; Inputting the operating parameters into an energy-saving planning model to obtain an energy storage charging and discharging control strategy for each of the nodes output by the energy-saving planning model; Based on the energy storage charging and discharging control strategy, controlling the node; Among them, the energy-saving planning model is a multi-objective optimization model with the objective function of minimizing the user's electricity cost and the power loss of the distribution network, and satisfying the preset constraints. The preset constraints include: power constraint, node power balance constraint, terminal voltage constraint, branch current constraint, node voltage upper and lower limit constraints.

2. The power distribution network energy-saving control method according to claim 1, characterized in that: The operating parameters include: electricity purchase price Electricity sales price The line resistance r between node i and node k ik , the square of the line current from node i to node k at time t l t,ik , line reactance x between node i and node k ik And the square of the voltage v at node j at time t t,j .

3. The power distribution network energy-saving control method according to claim 2, characterized in that: The objective function is: F(ω)=(1-ω)F1+ωF2 Among them, ω is the weight coefficient, F1 and F2 are the user's electricity cost and the power loss of the distribution network respectively, and are the power purchase and sales of node k at time t, ΔT is the time interval, T is the preset time range, and E is the set of network branches in the distribution network.

4. The power distribution network energy-saving control method according to claim 3, characterized in that: The power constraints include: in, is the active power exchange between the grid user at node k and the distribution network, and B is the node set of the grid user; The node power balance constraint includes: Among them, P t,ik and Q t,ik are the active power and reactive power flowing between node i and node k on network branch l at time t, respectively. t,km and Q t,km are the active power and reactive power flowing between node k and node m on network branch l at time t, is the reactive power exchange between the building and the distribution network at node k at time t; The terminal voltage constraint includes: Among them, V t,k and V t,i are the squares of the voltages of nodes k and i on network branch l at time t respectively; The branch current constraint includes: Among them, v t,ik is the square of the voltage between node i and node k on network branch l at time t; The node voltage upper and lower limit constraints include: Among them, v t,j is the square of the voltage at node j at time t, v j and are respectively a preset lower limit value and a preset upper limit value of the square of the voltage at the node j.

5. The power distribution network energy-saving control method according to claim 4, characterized in that: The node power balance constraint also includes: in, and are respectively the active power and reactive power generated by the battery in the grid user at node k at time t, and are respectively the active power and reactive power generated by the photovoltaic power generation unit in the grid user at node k at time t, is the reactive power exchange between the grid user at node k and the distribution network, and are respectively the active power and reactive power required by the load of the power grid user at node k at time t, and respectively is the maximum apparent power of the inverter of the photovoltaic power generation unit and the inverter of the battery, and are the power factor angles of the inverter of the photovoltaic power generation unit and the inverter of the battery respectively.

6. The power distribution network energy-saving control method according to claim 5, characterized in that: The preset constraint conditions also include: power constraint of the battery; The battery power constraints include: in, and are the state of charge of the battery at node k at time t and time t+1 respectively, is the self-consumption power of the battery at node k at time t, and as well as and They are respectively the preset upper limit and lower limit of the state of charge and the active power generated by the battery.

7. The power distribution network energy-saving control method according to claim 6, characterized in that: The preset constraints also include: power loss constraints of the battery; The battery power loss constraints include: in, and are the discharge loss and charge loss of the battery at time t, and are the discharge loss coefficient and the charge loss coefficient of the battery respectively, and are the charging efficiency and discharging efficiency of the battery respectively.

8. A distribution network energy-saving control system, characterized in that: include: A parameter acquisition unit, used to obtain the operating parameters of each node in the distribution network; A strategy acquisition unit, used for inputting the operating parameters into an energy-saving planning model to obtain an energy storage charging and discharging control strategy for each of the nodes output by the energy-saving planning model; A strategy execution unit is used to control the node based on the energy storage charging and discharging control strategy; wherein the energy-saving planning model is a multi-objective optimization model with minimizing the user's electricity cost and the distribution network's electricity loss as the objective function and satisfying preset constraints. The preset constraints include: power constraints, node power balance constraints, terminal voltage constraints, branch current constraints, and node voltage upper and lower limit constraints.

9. A distribution network, characterized in that: It comprises a distribution network body and the distribution network energy-saving control system as claimed in claim 8.

10. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to execute the distribution network energy-saving control method described in any one of claims 1 to 7 above.

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