Economical operation method for medium and low voltage honeycomb power distribution network

Abstract

The invention discloses an economic operation method for a medium and low voltage honeycomb power distribution network. The method comprises the following steps: step 1) constructing a power exchange mechanism among a plurality of micro-grids based on a honeycomb power distribution network topological structure; 2) establishing a multi-objective optimization model of the honeycomb power distribution network based on the power exchange mechanism, and converting the multi-objective optimization model into a single-objective optimization model through a mode of defining fitness; and step 3), solving the established model based on a doliolaria algorithm, and completing scheduling of the medium and low voltage honeycomb power distribution network according to the obtained solution. The method has the beneficial effects that according to the characteristics of strong evolutionary ability, fast search ability and strong optimization ability of the doliolaria algorithm, the scheduling scheme of the power distribution network is obtained based on the doliolaria algorithm solving model, the method can adapt to complex and changeable operation scenes of the honeycomb power distribution network, and the operation economy of the honeycomb power distribution network is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution networks, and in particular to an economical operation method for medium and low voltage honeycomb distribution networks. Background Art

[0002] With the development of power electronics technology, distributed power generation represented by wind power generation and photovoltaic power generation has become a new development direction in the field of electrical engineering. Distributed power generation has the advantages of high energy efficiency, low environmental pollution, flexible power supply and low cost. However, its randomness and volatility seriously reduce the stability and reliability of the power system. The cellular distribution network has the characteristics of flexible operation mode and has become a hot topic in recent years; its economic optimization scheduling method has become a key issue in research. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art and provide a method for economic operation of a medium and low voltage honeycomb distribution network. The method aims to ensure the stability and reliability of the power system, solve the complex and changeable operation scenarios of the honeycomb distribution network, and has the characteristics of flexible operation mode, which is specifically implemented by the following technical solutions:

[0004] The economic operation method of the medium and low voltage cellular distribution network comprises the following steps:

[0005] Step 1) constructing a power exchange mechanism between multiple microgrids based on the cellular distribution network topology;

[0006] Step 2) establishing a multi-objective optimization model of the cellular distribution network based on the power exchange mechanism, and converting the multi-objective optimization model into a single-objective optimization model by defining fitness;

[0007] Step 3) Solve the established model based on the Salp Algorithm, and dispatch the cellular distribution network according to the solution.

[0008] A further design of the economic operation mode of the medium and low voltage cellular distribution network is that the power exchange mechanism between microgrids constructed in step 1) is specifically: constructing a cellular distribution network topology structure including an active microgrid, an exchange base station and an integrated control center, the active microgrid realizes power exchange through the exchange base station, the exchange base station monitors the load changes and power flow fluctuations of the microgrid in real time, and transmits the data to the integrated control center.

[0009] A further design of the economic operation mode of the medium and low voltage cellular distribution network is that each microgrid in the cellular distribution network topology is connected to an adjacent microgrid through a common coupling point and an exchange base station, the power supply boundary of the active microgrid is set as a hexagon, the exchange base stations are distributed on the vertices of the hexagon, each base station is connected to three microgrids, and each microgrid is connected to six base stations.

[0010] The further design of the economic operation mode of the medium and low voltage honeycomb distribution network is that the step 2) of establishing a multi-objective optimization model of the honeycomb distribution network specifically includes:

[0011] The first objective function is to minimize the net load variance:

[0012]

[0013] In formula (1), P net,t is the net load of the receiving power grid during period t; P net,ave is the average value of the net load of the honeycomb distribution network in the entire dispatching period; T is a dispatching period;

[0014]

[0015] In formula (2), P L,t is the initial load of the receiving power grid during period t; P w,t,m is the output power of the mth wind farm in period t; w,t represents the wind curtailment rate in period t, 0≤λ w,t ≤1;P pv,t,n is the output power of the nth photovoltaic power station in period t; pv,t represents the abandoned light rate in period t, 0≤λ pv,t ≤1; p c,t represents the charging power of the energy storage system during period t; η c Represents the charging efficiency of the energy storage system; p d,t represents the discharge power of the energy storage system during period t; η d Indicates the discharge efficiency of the energy storage system;

[0016] The second objective function is to minimize the operating cost of the cellular distribution network:

[0017] Z2=min(f a +f1+f2-f3+C WZ ) (3)

[0018] f a =(αλ pv,t +βλ w,t )·Δt (4)

[0019] In the formula, α and β are the unit costs of abandoned solar power and abandoned wind power, respectively, f1 is the cost of purchasing electricity from the upper power grid through the base station, f2 is the cost of gas turbine power generation, f3 is the income from selling electricity to the upper power grid through the base station, and C WZ is the maintenance and depreciation cost of the energy storage system; a is the total cost of abandoning solar power and wind power; Δt is the time interval;

[0020] And construct constraints including the solar power abandonment rate and wind power abandonment rate, system electricity sales and purchases, energy storage system and system operation.

[0021] The further design of the economic operation mode of the medium and low voltage cellular distribution network is to calculate the power purchase cost of the base station from the upper power grid according to formula (5):

[0022]

[0023] In formula (5), C buy is the unit cost of the microgrid purchasing electricity from the upper grid through the base station, P buy is the amount of electricity purchased by the microgrid at the ath base station. Since the microgrid in the cellular distribution network is connected to 6 base stations, a is a maximum of 6. The gas turbine power generation cost is calculated according to formula (6):

[0024]

[0025] In formula (6), C g is the unit cost of natural gas, G e,t is the power generation of the gas turbine;

[0026] The revenue from selling electricity to the upper grid through the base station is calculated according to formula (7):

[0027]

[0028] In formula (7), C sell is the unit cost of the microgrid selling electricity to the upper grid through the base station, P sell,a is the power sales volume of the microgrid at the ath base station;

[0029] The maintenance and depreciation costs of the energy storage system are calculated according to formula (8):

[0030]

[0031] In formula (8), M is the total number of energy storage devices; R OP.i is the maintenance cost coefficient of the i-th energy storage device; P OP.i is the output power of the i-th energy storage device; C G.i is the installation cost of the i-th energy storage device; l i is the operating life of the i-th energy storage device.

[0032] The further design of the economic operation mode of the medium and low voltage cellular distribution network is to construct the constraint conditions specifically including:

[0033] According to formula (9), the constraints of the abandoned solar power rate and abandoned wind power rate are established:

[0034]

[0035] In formula (9), K w,max Indicates the maximum wind abandonment rate allowed by the wind farm; K pv,max represents the maximum allowable abandonment rate of photovoltaic power station; the constraints of energy storage system are established according to formula (10):

[0036]

[0037] In formula (10), SOC t represents the remaining power of the energy storage system at time t; P bat,ch,t and P bat,disch,t Respectively represent the charging and discharging power of the energy storage system at time t;

[0038] According to formula (11), the system power sales and purchase constraints are established:

[0039]

[0040] P buy,min is the minimum value of electricity purchased from the upper grid; P buy,max is the maximum value of electricity purchased from the upper grid; P buy P is the amount of electricity purchased from the upper grid; sell,min is the minimum value of electricity sold to the upper grid; P sell,max is the maximum value of electricity sold to the upper grid; P sell Indicates the amount of electricity sold to the superior power grid;

[0041] According to formula (12), the constraints of system operation are established:

[0042]

[0043] The further design of the economic operation mode of the medium and low voltage honeycomb distribution network is that in the step 2), a new fitness Z is defined o The multi-objective optimization problem is transformed into a single-objective optimization problem, and the fitness Z is calculated according to formula (13): o , Z o The smaller it is, the closer the solution is to the optimal solution.

[0044]

[0045] In formula (13), Z 1,min Represents the minimum value of the net load variance, Z 2,min It represents the minimum value of the operating cost of the cellular distribution network.

[0046] The further design of the economic operation mode of the medium and low voltage cellular distribution network is that the model solving process based on the salp algorithm in step 3) specifically includes the following steps:

[0047] Step 3-1) Input the honeycomb distribution network system data, including the wind power generation of a single microgrid in the honeycomb distribution network, the photovoltaic power generation data, the load carried by the distribution network, the unit charging and discharging power of the energy storage system, and the unit cost of abandoning light and wind, and initialize the honeycomb distribution network system data;

[0048] Step 3-2) Define the individual and population of salps, and define the position vector of the individual salps as X = [λ w,t λ pv,t p c,t p d,t p buy,a p sell,a G e,t ], and randomly generate N individuals, the position vector X is composed of N salps individuals, and the salp population vector is obtained:

[0049] X=[x1,x2,…,x N ] (14)

[0050] Step 3-3) Taking the minimum net load variance and the operation cost of the honeycomb distribution network as food sources, the fitness of the model is calculated according to formula (13);

[0051] Step 3-4) Update the position of the salp leader according to formula (15);

[0052]

[0053]

[0054] In the formula, is the leader salp individual, and is the position in the j-th dimension; F j is the food source, i.e. the target of the salp colony, and its location in the j-th dimension; ub j , is the upper limit of each salp individual in the j-th dimension, lb j is the lower limit of each salp individual in the j-th dimension space; c2 and c3 are numbers randomly generated from the interval [0,1], l is the current iteration number, and L is the maximum iteration number;

[0055] Step 3-5) Update the position of the salp follower according to formula (17);

[0056]

[0057] Step 3-6) If the number of iterations has not reached the maximum, return to step 3-3); otherwise, output the result.

[0058] The present invention also provides an electronic device, comprising a memory, a processor and a computer program, wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the economic operation method of the medium and low voltage cellular distribution network.

[0059] The present invention also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program is executed by a processor to implement the economic operation method of the medium and low voltage cellular distribution network.

[0060] The advantages of the present invention are as follows:

[0061] The economic operation method of the medium and low voltage honeycomb distribution network of the present invention first establishes a multi-objective optimization model of the honeycomb distribution network, while considering the new energy consumption and operation cost issues of the honeycomb distribution network, and then transforms the multi-objective optimization model into a single-objective optimization model by defining the fitness. According to the characteristics of the Salp Sea Squib algorithm, which has strong evolutionary ability, fast search ability, and strong optimization ability, the dispatching scheme of the distribution network is obtained based on the Salp Sea Squib algorithm solution model, which can adapt to the complex and changeable operation scenarios of the honeycomb distribution network and effectively improve the economy of the operation of the honeycomb distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a schematic diagram of the topological structure of the honeycomb distribution network.

[0063] Figure 2 Flowchart for the salp algorithm optimization. DETAILED DESCRIPTION

[0064] The technical solution of the present invention is described in detail below.

[0065] The economic operation method of the medium and low voltage cellular distribution network of this embodiment includes the following steps:

[0066] Step 1) Construct a power exchange mechanism between multiple microgrids based on the cellular distribution network topology.

[0067] Step 2) A multi-objective optimization model of the cellular distribution network is established based on the power exchange mechanism, and the multi-objective optimization model is converted into a single-objective optimization model by defining fitness.

[0068] Step 3) Solve the established model based on the Salp Unicinus algorithm to obtain the economic operation method of the cellular distribution network under the maximum scenario of new energy consumption, and realize the economic optimization scheduling of the cellular distribution network.

[0069] The power exchange mechanism between microgrids in step 1) is specifically constructed as follows: a cellular distribution network topology structure including an active microgrid, an exchange base station and an integrated control center is constructed. The active microgrid realizes power exchange through the exchange base station. The exchange base station monitors the load changes and power flow fluctuations of the microgrid in real time and transmits the data to the integrated control center.

[0070] like Figure 1 ,In the honeycomb distribution network topology, each microgrid is connected to the adjacent microgrid through the common ,coupling point and the switching base station. The power boundary of the active microgrid is set as a hexagon. The switching base stations are distributed on the vertices of the hexagon. Each base station is connected to three microgrids, and each microgrid is connected to six base stations.

[0071] Step 2) Establishing a multi-objective optimization model for the honeycomb distribution network specifically includes:

[0072] The first objective function is to minimize the net load variance:

[0073]

[0074] In formula (1), P net,t is the net load of the receiving power grid during period t; P net,ave is the average value of the net load of the cellular distribution network during the entire dispatching period; T is a dispatching period.

[0075]

[0076] In formula (2), P L,t is the initial load of the receiving power grid during period t; P w,t,m is the output power of the mth wind farm in period t; w,t represents the wind curtailment rate in period t, 0≤λ w,t ≤1;P pv,t,n is the output power of the nth photovoltaic power station in period t; pv,t represents the abandoned light rate in period t, 0≤λ pv,t ≤1; p c,t represents the charging power of the energy storage system during period t; η c Represents the charging efficiency of the energy storage system; p d,t represents the discharge power of the energy storage system during period t; η d Indicates the discharge efficiency of the energy storage system;

[0077] The second objective function is to minimize the operating cost of the cellular distribution network:

[0078] Z2=min(f a +f1+f2-f3+C WZ ) (3)

[0079] f a=(αλ pv,t +βλ w,t )·Δt (4)

[0080] In the formula, α and β are the unit costs of abandoned solar power and abandoned wind power, respectively, f1 is the cost of purchasing electricity from the upper power grid through the base station, f2 is the cost of gas turbine power generation, f3 is the income from selling electricity to the upper power grid through the base station, and C WZ is the maintenance and depreciation cost of the energy storage system; a is the total cost of curtailing solar power and wind power; Δt is the time interval.

[0081] And construct constraints including the solar power abandonment rate and wind power abandonment rate, system electricity sales and purchases, energy storage system and system operation.

[0082] The power purchase cost of the base station from the upper power grid is calculated according to formula (5):

[0083]

[0084] In formula (5), C buy is the unit cost of the microgrid purchasing electricity from the upper grid through the base station, P buy is the amount of electricity purchased by the microgrid at the ath base station. Since the microgrid in the cellular distribution network is connected to 6 base stations, a is a maximum of 6. The gas turbine power generation cost is calculated according to formula (6):

[0085]

[0086] In formula (6), C g is the unit cost of natural gas, G e,t is the power generation of the gas turbine;

[0087] The revenue from selling electricity to the upper grid through the base station is calculated according to formula (7):

[0088]

[0089] In formula (7), C sell is the unit cost of the microgrid selling electricity to the upper grid through the base station, P sell,a is the power sales volume of the microgrid at the ath base station;

[0090] The maintenance and depreciation costs of the energy storage system are calculated according to formula (8):

[0091]

[0092] In formula (8), M is the total number of energy storage devices; R OP.i is the maintenance cost coefficient of the i-th energy storage device; P OP.i is the output power of the i-th energy storage device; C G.iis the installation cost of the i-th energy storage device; l i is the operating life of the i-th energy storage device.

[0093] The construction constraints include:

[0094] According to formula (9), the constraints of the abandoned solar power rate and abandoned wind power rate are established:

[0095]

[0096] In formula (9), K w,max Indicates the maximum wind abandonment rate allowed by the wind farm; K pv,max Indicates the maximum allowable abandonment rate of photovoltaic power station; P w,t,m is the output power of the mth wind farm in period t; P pv,t,n is the output power of the nth PV power station in period t.

[0097] According to formula (10), the constraints of the energy storage system are established:

[0098]

[0099] In formula (10), SOC t represents the remaining power of the energy storage system at time t; P bat,ch,t and P bat,disch,t Respectively represent the charging and discharging power of the energy storage system at time t;

[0100] According to formula (11), the system power sales and purchase constraints are established:

[0101]

[0102] P buy,min is the minimum value of electricity purchased from the upper grid; P buy,max is the maximum value of electricity purchased from the upper grid; P buy P is the amount of electricity purchased from the upper grid; sell,min is the minimum value of electricity sold to the upper grid, P sell,max is the maximum value of electricity sold to the upper grid, P sell Indicates the amount of electricity sold to the superior power grid.

[0103] According to formula (12), the constraints of system operation are established:

[0104]

[0105] In step 2) of this embodiment, a new fitness Z is defined o The multi-objective optimization problem is transformed into a single-objective optimization problem, and the fitness Z is calculated according to formula (13): o , Z o The smaller it is, the closer the solution is to the optimal solution.

[0106]

[0107] In formula (13), Z 1,min Represents the minimum value of the net load variance, Z 2,min It represents the minimum value of the operating cost of the cellular distribution network.

[0108] The model solving process based on the Salp Integrity Algorithm in step 3) specifically includes the following steps:

[0109] Step 3-1) Input the system data of the honeycomb distribution network, including the wind power generation of a single microgrid of the honeycomb distribution network, the data of photovoltaic power generation, the load carried by the distribution network, the unit charging and discharging power of the energy storage system, and the unit cost of abandoning light and wind, and initialize the system data of the honeycomb distribution network.

[0110] Step 3-2) Define the individual and population of salps, and define the position vector of the individual salps as X = [λ w,t λ pv,t p c,t p d,t p buy,a p sell,a G e,t ], and randomly generate N individuals, the position vector X is composed of N salps individuals, and the salp population vector is obtained:

[0111] X=[x1,x2,…,x N ] (14)

[0112] Step 3-3) Take the minimum net load variance and the operating cost of the honeycomb distribution network as food sources and calculate the fitness of the model according to formula (13).

[0113] Step 3-4) Update the position of the salp leader according to formula (15);

[0114]

[0115] In the formula, is the leader salp individual, and is the position in the j-th dimension; F j is the food source, i.e. the target of the salp colony, and its location in the j-th dimension; ub j , is the upper limit of each salp individual in the j-th dimension, lb j is the lower limit of each salp individual in the j-th dimension space; c2 and c3 are both randomly generated numbers in the interval [0,1], l is the current number of iterations, and L is the maximum number of iterations.

[0116] Step 3-5) Update the position of the salp follower according to formula (17);

[0117]

[0118] Step 3-6) If the number of iterations has not reached the maximum, return to step 3-3); otherwise, output the result.

[0119] This embodiment further provides an electronic device, including a memory, a processor, and a computer program, wherein the computer program is stored in the memory and is configured to be executed by the processor to implement a method for economic operation of a medium and low voltage cellular distribution network.

[0120] This embodiment also provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement an economical operation method for a medium and low voltage cellular distribution network.

[0121] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for economic operation of a medium and low voltage cellular distribution network, characterized in that: The following steps are involved: Step 1) constructing a power exchange mechanism between multiple microgrids based on the cellular distribution network topology; Step 2) establishing a multi-objective optimization model of the cellular distribution network based on the power exchange mechanism, and converting the multi-objective optimization model into a single-objective optimization model by defining fitness; Step 3) Solve the established model based on the Salp Algorithm, and dispatch the cellular distribution network according to the solution.

2. The economic operation mode of the medium and low voltage cellular distribution network according to claim 1 is characterized in that: The power exchange mechanism between microgrids constructed in step 1) is specifically as follows: a cellular distribution network topology structure including an active microgrid, an exchange base station and an integrated control center is constructed. The active microgrid realizes power exchange through the exchange base station. The exchange base station monitors the load changes and power flow fluctuations of the microgrid in real time and transmits the data to the integrated control center.

3. The economic operation method of the medium and low voltage honeycomb distribution network according to claim 2 is characterized in that In the honeycomb distribution network topology, each microgrid is connected to adjacent microgrids through a common coupling point and an exchange base station. The power boundary of the active microgrid is set as a hexagon. The exchange base stations are distributed on the vertices of the hexagon. Each base station is connected to three microgrids, and each microgrid is connected to six base stations.

4. The economic operation method of a medium and low voltage cellular distribution network according to claim 1 is characterized in that The step 2) of establishing a multi-objective optimization model for the honeycomb distribution network specifically includes: The first objective function is to minimize the net load variance: In formula (1), P net,t is the net load of the receiving power grid during period t; P net,ave is the average value of the net load of the honeycomb distribution network in the entire dispatching period; T is a dispatching period; In formula (2), P L,t is the initial load of the receiving power grid during period t; P w,t,m is the output power of the mth wind farm in period t; w,t represents the wind curtailment rate in period t, 0≤λ w,t ≤1;P pv,t,n is the output power of the nth photovoltaic power station in period t; pv,t represents the abandoned light rate in period t, 0≤λ pv,t ≤1; p c,t represents the charging power of the energy storage system during period t; η c Represents the charging efficiency of the energy storage system; p d,t represents the discharge power of the energy storage system during period t; η d Indicates the discharge efficiency of the energy storage system; The second objective function is to minimize the operating cost of the cellular distribution network: <h2 style=";text-align:left;direction:ltr">Z2 = min(f<h2 style=";text-align:left;direction:ltr"> a <h2 style=";text-align:left;direction:ltr"> +f1+f2-f3+C<h2 style=";text-align:left;direction:ltr"> WZ <h2 style=";text-align:left;direction:ltr"> ) (3) f a =(al pv,t +see w,t )·Δt (4) In the formula, α and β are the unit costs of abandoned solar power and abandoned wind power, respectively, f1 is the cost of purchasing electricity from the upper power grid through the base station, f2 is the cost of gas turbine power generation, f3 is the income from selling electricity to the upper power grid through the base station, and C WZ is the maintenance and depreciation cost of the energy storage system; a is the total cost of abandoning solar power and wind power; Δt is the time interval; And construct constraints including the solar power abandonment rate and wind power abandonment rate, system electricity sales and purchases, energy storage system and system operation.

5. The economic operation method of the medium and low voltage honeycomb distribution network according to claim 4 is characterized in that The power purchase cost of the base station from the upper power grid is calculated according to formula (5): In formula (5), C buy is the unit cost of the microgrid purchasing electricity from the upper grid through the base station, P buy is the amount of electricity purchased by the microgrid at the ath base station. Since the microgrid in the cellular distribution network is connected to 6 base stations, the maximum value of a is 6; The cost of gas turbine power generation is calculated according to formula (6): In formula (6), C g is the unit cost of natural gas, G e,t is the power generation of the gas turbine; The revenue from selling electricity to the upper grid through the base station is calculated according to formula (7): In formula (7), C sell is the unit cost of the microgrid selling electricity to the upper grid through the base station, P sell,a is the power sales volume of the microgrid at the ath base station; The maintenance and depreciation costs of the energy storage system are calculated according to formula (8): In formula (8), M is the total number of energy storage devices; R OP.i is the maintenance cost coefficient of the i-th energy storage device; P OP.i is the output power of the i-th energy storage device; C G.i is the installation cost of the i-th energy storage device; l i is the operating life of the i-th energy storage device.

6. The economic operation method of a medium and low voltage honeycomb distribution network according to claim 4 is characterized in that The construction constraints include: According to formula (9), the constraints of the abandoned solar power rate and abandoned wind power rate are established: In formula (9), K w,max Indicates the maximum wind abandonment rate allowed by the wind farm; K pv,max represents the maximum allowable abandonment rate of photovoltaic power station; the constraints of energy storage system are established according to formula (10): In formula (10), SOC t represents the remaining power of the energy storage system at time t; P bat,ch,t and P bat,disch,t Respectively represent the charging and discharging power of the energy storage system at time t; According to formula (11), the system power sales and purchase constraints are established: P buy,min is the minimum value of electricity purchased from the upper grid; P buy,max is the maximum value of electricity purchased from the upper power grid; P buy P is the amount of electricity purchased from the upper grid; sell,min is the minimum value of electricity sold to the upper grid; P sell,max is the maximum value of electricity sold to the upper grid; P sell Indicates the amount of electricity sold to the superior power grid; According to formula (12), the constraints of system operation are established:

7. The economic operation method of a medium and low voltage honeycomb distribution network according to claim 4 is characterized in that In step 2), a new fitness Z is defined o The multi-objective optimization problem is transformed into a single-objective optimization problem, and the fitness Z is calculated according to formula (13): o , Z o The smaller it is, the closer the solution is to the optimal solution. In formula (13), Z 1,min Represents the minimum value of the net load variance, Z 2,min It represents the minimum value of the operating cost of the cellular distribution network.

8. The economic operation method of a medium and low voltage cellular distribution network according to claim 7 is characterized in that The model solving process based on the Salp Integrity Algorithm in step 3) specifically includes the following steps: Step 3-1) Input the honeycomb distribution network system data, including the wind power generation of a single microgrid in the honeycomb distribution network, the photovoltaic power generation data, the load carried by the distribution network, the unit charging and discharging power of the energy storage system, and the unit cost of abandoning light and wind, and initialize the honeycomb distribution network system data; Step 3-2) Define the individual and population of salps, and define the position vector of the individual salps as X = [λ w,t λ pv,t p c,t p d,t p buy,a p sell,a G e,t ], and randomly generate N individuals, the position vector X is composed of N salps individuals, and the salp population vector is obtained: X=[x1,x2,…,x N ] (14) Step 3-3) Taking the minimum net load variance and the operation cost of the honeycomb distribution network as food sources, the fitness of the model is calculated according to formula (13); Step 3-4) Update the position of the salp leader according to formula (15); In the formula, is the leader salp individual, and is the position in the j-th dimension; F j is the food source, i.e. the target of the salp colony, and its location in the j-th dimension; ub j , is the upper limit of each salp individual in the j-th dimension, lb j is the lower limit of each salp individual in the j-th dimension space; c2 and c3 are numbers randomly generated from the interval [0,1], l is the current iteration number, and L is the maximum iteration number; Step 3-5) Update the position of the salp follower according to formula (17); Step 3-6) If the number of iterations has not reached the maximum, return to step 3-3); otherwise, output the result.

9. An electronic device, characterized in that: It comprises a memory, a processor and a computer program, wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the economic operation method of a medium and low voltage cellular distribution network as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program is executed by a processor to implement the economic operation method of a medium and low voltage cellular distribution network according to any one of claims 1 to 8.

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