Power distribution networking morphological architecture optimization method giving consideration to economy and reliability

Abstract

The invention discloses an economical and reliable distribution network form architecture optimization method, which comprises the following steps of: calculating economical and reliable indexes according to basic architecture information of a distribution network and basic information of a load point; taking the minimum economic and reliable indexes as a multi-objective function, and taking the voltage, current, power balance and net rack of the distribution network line as constraint conditions to construct a multi-objective optimization model; a multi-objective optimization quantity value is solved through an ant colony algorithm, an optimal solution set is described to represent an optimized distribution network networking form architecture, a power grid form architecture with higher robustness, convergence and reliability is built, the power failure area is reduced, the influence caused by power failure is reduced, and economic operation of the power distribution network is achieved.

Description

Technical Field

[0001] The present invention relates to the field of electric power systems, and in particular to a method for optimizing a power distribution network structure that takes both economy and reliability into consideration. Background Art

[0002] At present, the large-scale grid connection of new energy and electric vehicles and other multiple elements has caused the grid to change from a single flow to a dual flow direction, which has a great impact on the grid loss, reliability, power quality and other aspects. In order to ensure the safe and stable operation of the power grid, meet the electricity demand of users, reduce grid investment, and improve grid redundancy. Domestic and foreign scholars have conducted research from multiple angles such as the carrying capacity of the distribution network, the absorption capacity, and the reliability assessment of large-scale new energy grid connection to solve the existing problems such as reverse overload of the power grid. However, the current research is based on a single factor, and the distribution network architecture is based on conventional planning awareness, considering whether the output of new energy in the grid or the power supply area is mainly input or output, and identifying its network architecture form, and has not fully considered the optimal combination form architecture under the dual factors of economy and reliability of the entire system, so there is a certain degree of subjectivity.

[0003] In response to the above problems, the present invention fully takes the optimization of the dual factor indicators of economy and reliability as the goal, takes the safe and stable operation of the power grid as the constraint condition, constructs a multi-objective optimization goal, forms an optimal set through the ant colony algorithm search path, and then determines a distribution network form architecture solution that takes into account both economy and reliability. Summary of the invention

[0004] The present invention provides a method for optimizing the distribution network architecture that takes into account both economy and reliability. The method uses an ant colony algorithm to solve multi-objective optimization problems, realizes distribution network optimization networking, and ensures low line loss and high reliability of the power grid.

[0005] The technical solution adopted by the present invention is:

[0006] A method and system for optimizing the architecture of a power distribution network that takes both economy and reliability into consideration, comprising the following steps:

[0007] S1. Obtaining basic information of the distribution network structure to calculate the economic index line loss of the distribution network, wherein the basic information of the power grid structure includes the current, voltage, resistance, quantity and topological structure of the distribution network line;

[0008] S2. Obtaining the distribution network load point information to calculate the reliability indicator power shortage and reliability, wherein the load point information includes the number of load points, average load, average annual power outage time, and failure rate to calculate the total power shortage of the load points and the average power outage frequency per household;

[0009] S4. Taking the minimum economic and reliability index as the multi-objective function and the distribution network line voltage, current, power balance and grid as the constraint conditions, a multi-objective optimization model is constructed;

[0010] S5. Solve multi-objective optimization values ​​through ant colony algorithm, characterize the optimal solution set to represent the optimized distribution network architecture.

[0011] Compared with the prior art, the present invention has the following beneficial effects: the present invention fully takes the optimization of the dual factor indicators of economy and reliability as the goal, takes the safe and stable operation of the power grid as the constraint condition, constructs a multi-objective optimization goal, forms an optimal set through the ant colony algorithm search path, and then determines a distribution network form architecture solution that takes into account both economy and reliability, greatly reduces network losses, has higher robustness, convergence, and reliability, reduces the area of ​​power outages and reduces the impact of power outages, and realizes the economic operation of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the flow chart of the method for optimizing the power distribution network form architecture that takes into account both economy and reliability in the present invention; DETAILED DESCRIPTION

[0013] like Figure 1 As shown, a method for optimizing the power distribution network architecture that takes into account both economy and reliability includes the following steps:

[0014] S1. Obtaining basic information of the distribution network structure to calculate the economic index line loss of the distribution network, wherein the basic information of the power grid structure includes the current, voltage, resistance, quantity and topological structure of the distribution network line;

[0015] S2. Obtaining the distribution network load point information to calculate the reliability indicator power shortage and reliability, wherein the load point information includes the number of load points, average load, average annual power outage time, and failure rate to calculate the total power shortage of the load points and the average power outage frequency per household;

[0016] S4. Taking the minimum economic and reliability index as the multi-objective function and the distribution network line voltage, current, power balance and grid as the constraint conditions, a multi-objective optimization model is constructed;

[0017] S5. Solve multi-objective optimization values ​​through ant colony algorithm, characterize the optimal solution set to represent the optimized distribution network architecture.

[0018] 1. The distribution network form architecture optimization method of the ant colony algorithm according to claim 1, characterized in that the calculation formula for obtaining the economic index line loss in step S1 is as follows:

[0019]

[0020] In formula (1), br is the distribution network line; N br is the number of distribution network lines in normal operation; I br is the distribution network line current; R br is the resistance of the distribution network line; f1 is the network loss of the distribution network line.

[0021] 2. The method for optimizing the distribution network architecture of an ant colony algorithm according to claim 1, characterized in that the calculation formula for obtaining the reliability indicator power shortage and the average frequency per household in step S2 is as follows:

[0022]

[0023] In formula (2), j is the load point; N D is the number of load points j; P j is the average load at each load point, t j is the average annual power outage time of load point j; f2 is the total power shortage at load point j.

[0024] The formula for calculating the average power outage frequency of users is as follows:

[0025]

[0026] In formula (3), j is the load point; N D is the number of load points; C j is the number of users at the load point, τ j is the failure rate of the load point; f3 is the average power outage frequency of users.

[0027] 4. The method for optimizing the distribution network architecture using an ant colony algorithm according to claim 1, wherein the objective function formula in step S4 is as follows:

[0028] obj=min(f1,f2,f3) (4)

[0029] In formula (4), f1 is the network loss of the distribution network; f2 is the total power shortage at the load point; f3 is the average power outage frequency of users; min(f) represents the minimum value of the objective function.

[0030] 5. The method for optimizing the distribution network architecture using an ant colony algorithm according to claim 1, wherein the constraint conditions in step S4 include:

[0031] 1) Control variable constraint, that is, the number of distribution network lines in the disconnected state is less than the number of distribution network lines in normal operation, expressed as:

[0032] 1≤br o.j ≤N br ,j=1,2,3,…,N br.o(5)

[0033] In formula (5), br o.j N is the distribution network line in the disconnected state. br is the number of distribution network lines in normal operation;

[0034] 2) Voltage constraint, that is, the voltage at the load point is greater than the minimum allowable voltage and less than the maximum allowable voltage, expressed as:

[0035] V j.min ≤V j ≤V j.max (6)

[0036] In formula (6), j is the load point; V j.min The minimum voltage allowed at the load point; V j is the voltage at the load point; V j.max The maximum voltage allowed at the load point;

[0037] 3) Current constraint, that is, the distribution network line current is less than the maximum allowable current of the distribution network line, expressed as:

[0038] |I br |≤I br.max , br=1,2,3,…,N br (7)

[0039] In formula (7), I br I is the distribution network line current; br.max N is the maximum allowable current of the distribution network line; br is the number of distribution network lines in normal operation;

[0040] 4) Power balance constraint, that is, the power balance of the load point is an equality constraint, expressed as:

[0041] P j +Q j =V j |I j | * , j = 1, 2, 3, ..., N D (8)

[0042] In formula (8), j is the load point; P j , Q j are the active and reactive power of the load point respectively; V j is the voltage at the load point; I j is the current flowing into the load point; N D is the number of load points j;

[0043] 5) Grid constraint, that is, the network topology of the distribution network line is set to N D ×Nbr The matrix, whose grid constraints are based on the operation mode, is expressed as:

[0044]

[0045] In formula (9), A ij It is the radial structure of the distribution line operation mode, the outgoing line is 1, the ongoing line is -1, and the connected line is 0; i is the distribution network line; j is the busbar in the distribution network line.

[0046] 6. The method for optimizing the power distribution network architecture that takes into account both economy and reliability according to claim 1, characterized in that the specific process of multi-objective optimization solution in step S5 includes:

[0047] S51, setting parameters, including the search space, the number of ants in the ant colony, and the maximum number of iterations, wherein the number of ant colonies is the target number for optimization;

[0048] S52, initialize the ant colony, the formula is as follows:

[0049] JF i (It+1)=4Y0(1-JF i ),0≤Y0≤1,i=1,2,…,N JF (10)

[0050] In formula (10), JF i (It+1) is the position of each ant in the ant colony, Y0 is a random number between [0,1], It is the number of iterations, and the initial value is set to 1;

[0051] S53, evaluating the fitness of each ant in the ant colony and selecting the current optimal position of all ants;

[0052] S54, updating the position of each ant in the ant colony and summarizing the updated position elements of the ants;

[0053] S55. Continuously repeat the above steps S53 to S54 until a maximum number of iterations is reached to obtain an optimal solution set, wherein the optimal solution set represents an optimized distribution network architecture.

[0054] 7. The method for optimizing the power distribution network architecture that takes into account both economy and reliability according to claim 1, wherein the updating formula in step S54 is as follows:

[0055]

[0056] In formula (11), U b and L b are the upper and lower limits of the control variable, JF i(It+1) is the corresponding position of each ant in the ant colony.

[0057] The embodiments described above are merely descriptions of preferred implementation modes of the present invention and are not intended to limit the scope of the present invention. Without departing from the principles and essence of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for optimizing the power distribution network architecture that takes into account both economy and reliability, characterized in that: Calculate the values ​​of economic indicators and reliability indicators, where economic indicators include line loss and reliability indicators include power shortage and power outage frequency; based on economic and reliability indicators, build a multi-objective optimization model to solve and obtain the optimized distribution network architecture, including the following steps: S1. Obtaining basic information of the distribution network structure to calculate the economic index line loss of the distribution network, wherein the basic information of the power grid structure includes the current, voltage, resistance, quantity and topological structure of the distribution network line; S2. Obtaining the distribution network load point information to calculate the reliability indicator power shortage and reliability, wherein the load point information includes the number of load points, average load, average annual power outage time, and failure rate to calculate the total power shortage of the load points and the average power outage frequency per household; S4. Taking the minimum economic and reliability index as the multi-objective function and the distribution network line voltage, current, power balance and grid as the constraint conditions, a multi-objective optimization model is constructed; S5. Solve multi-objective optimization values ​​through ant colony algorithm, characterize the optimal solution set to represent the optimized distribution network architecture.

2. The method for optimizing the distribution network structure using the ant colony algorithm according to claim 1, characterized in that: The calculation formula for obtaining the economic index line loss in step S1 is as follows: In formula (1), br is the distribution network line; N br is the number of distribution network lines in normal operation; I br is the distribution network line current; R br is the resistance of the distribution network line; f1 is the network loss of the distribution network line.

3. The method for optimizing the network architecture of a distribution network using an ant colony algorithm according to claim 1, characterized in that: The calculation formula for obtaining the reliability indicator power shortage and household average frequency in step S2 is as follows: In formula (2), j is the load point; N D is the number of load points j; P j is the average load at each load point, t j is the average annual power outage time of load point j; f2 is the total power shortage at load point j. The formula for calculating the average power outage frequency of users is as follows: In formula (3), j is the load point; N D is the number of load points; C j is the number of users at the load point, τ j is the failure rate of the load point; f3 is the average power outage frequency of users.

4. The method for optimizing the distribution network architecture of an ant colony algorithm according to claim 1, characterized in that: The objective function formula in step S4 is as follows: obj=min(f1,f2,f3) (4) In formula (4), f1 is the network loss of the distribution network; f2 is the total power shortage at the load point; f3 is the average power outage frequency of users; min(f) represents the minimum value of the objective function.

5. The method for optimizing the distribution network architecture of an ant colony algorithm according to claim 1, characterized in that: The constraints in step S4 include: 1) Control variable constraint, that is, the number of distribution network lines in the disconnected state is less than the number of distribution network lines in normal operation, expressed as: 1≤br o.j ≤N br ,j,1,2,3,…,N br.o (5) In formula (5), br o.j N is the distribution network line in the disconnected state. br is the number of distribution network lines in normal operation; 2) Voltage constraint, that is, the voltage at the load point is greater than the minimum allowable voltage and less than the maximum allowable voltage, expressed as: In j.min ≤V j ≤V j.max (6) In formula (6), j is the load point; V j.min The minimum voltage allowed at the load point; V j is the voltage at the load point; V j.max The maximum voltage allowed at the load point; 3) Current constraint, that is, the distribution network line current is less than the maximum allowable current of the distribution network line, expressed as: |I br |≤I br.max ,br=1,2,3,…,N br (7) In formula (7), I br I is the distribution network line current; br.max N is the maximum allowable current of the distribution network line; br is the number of distribution network lines in normal operation; 4) Power balance constraint, that is, the power balance of the load point is an equality constraint, expressed as: P j +Q j =V j |I j | * ,j=1,2,3,…,N D (8) In formula (8), j is the load point; P j , Q j are the active and reactive power of the load point respectively; V j is the voltage at the load point; I j is the current flowing into the load point; N D is the number of load points j; 5) Grid constraint, that is, the network topology of the distribution network line is set to N D ×N br The matrix, whose grid constraints are based on the operation mode, is expressed as: In formula (9), A ij It is the radial structure of the distribution line operation mode, the outgoing line is 1, the ongoing line is -1, and the connected line is 0; i is the distribution network line; j is the busbar in the distribution network line.

6. The method for optimizing the power distribution network architecture that takes into account both economy and reliability according to claim 1, characterized in that: The specific process of multi-objective optimization solution in step S5 includes: S51, setting parameters, including the search space, the number of ants in the ant colony, and the maximum number of iterations, wherein the number of ant colonies is the target number for optimization; S52, initialize the ant colony, the formula is as follows: JF i (It+1)=4Y0(1-JF i ),0≤Y0≤1,i=1,2,...,N JF (10) In formula (10), JF i (It+1) is the position of each ant in the ant colony, Y0 is a random number between [0,1], It is the number of iterations, and the initial value is set to 1; S53, evaluating the fitness of each ant in the ant colony and selecting the current optimal position of all ants; S54, updating the position of each ant in the ant colony and summarizing the updated position elements of the ants; S55. Continuously repeat the above steps S53 to S54 until a maximum number of iterations is reached to obtain an optimal solution set, wherein the optimal solution set represents an optimized distribution network architecture.

7. The method for optimizing the power distribution network architecture that takes into account both economy and reliability according to claim 1, characterized in that: The updating formula in step S54 is as follows: In formula (11), U b and L b are the upper and lower limits of the control variable, JF i (It+1) is the corresponding position of each ant in the ant colony.

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