Distribution network voltage reduction and load shedding operation method and system based on guanghao porcupine optimization algorithm

Abstract

The application discloses a power distribution network voltage reduction and load reduction operation method and system based on a Guan Hao pig optimization algorithm, and comprises the following steps: determining a target function of a power distribution network voltage reduction and load reduction operation multi-objective optimization problem and system operation constraint conditions; adopting the Guan Hao pig optimization algorithm to simulate visual intimidation, sound intimidation, smell attack and physical defense behaviors of the Guan Hao pig, and iteratively optimizing a population under the premise of meeting the system operation constraint conditions to minimize the target function of the multi-objective optimization problem, so as to determine optimal on-load voltage regulating transformer (OLTC) adjustment gears, operation output of distributed power generation resources (DGs) and network structure states and issue an execution. The application aims at a multi-objective optimization problem of effectively reducing the operation cost of a power grid, reducing loss and guaranteeing voltage quality during a load peak period, improves the solution accuracy of the multi-objective optimization problem, and reduces additional investment cost and improves the economy of power grid operation.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network voltage optimization and regulation, and in particular to a distribution network voltage reduction and load reduction operation method and system based on a crested porcupine optimization algorithm. Background Art

[0002] With the development of society and the growth of energy demand, distribution networks, as a vital component of the power system, are tasked with transmitting electricity from the high-voltage grid to end users. In modern distribution networks, distributed power sources, such as solar photovoltaics and wind power generation, provide a clean and flexible energy supplement to the grid, but also bring new challenges. Traditional distribution network design and operation methods are mainly targeted at centralized power supply models. However, with the widespread access of distributed power sources, the operation and management of the grid has become more complex. How to effectively reduce grid operating costs, minimize losses, and ensure voltage quality, especially during peak load periods, has become a pressing issue. Currently, optimization methods for distribution network operation mainly focus on network reconstruction, load scheduling, and power supply configuration. In addition, with the increasing severity of environmental problems, voltage reduction and energy-saving measures are also being increasingly emphasized. The goal is to operate within a lower voltage range and reduce energy consumption while meeting the supply voltage deviation and preventing damage to electrical equipment. Currently, some scholars have considered using on-load tap-changing transformers, substation capacitor banks, and line capacitor banks for reactive power compensation to achieve voltage reduction and energy conservation in the context of high-penetration photovoltaic access distribution systems. Other researchers have proposed a voltage reduction and energy conservation technology that integrates voltage and reactive power optimization control, distribution system control, and the active participation of distributed power sources. However, these methods are less economical and may suffer from poor adaptability and insufficient solution accuracy when solving multi-objective optimization problems. Summary of the Invention

[0003] The technical problem to be solved by the present invention is as follows: In response to the above-mentioned problems in the prior art, a method and system for reducing voltage and load in a distribution network based on the crown porcupine optimization algorithm are provided. The present invention aims to solve the multi-objective optimization problem of effectively reducing the operating cost of the power grid, reducing losses, and ensuring voltage quality during peak load periods, and to improve the accuracy of solving the multi-objective optimization problem, so as to reduce additional investment costs and improve the economy of power grid operation.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A method for reducing voltage and load in a distribution network based on a crown porcupine optimization algorithm comprises the following steps:

[0006] S1, determine the objective function of the multi-objective optimization problem of voltage reduction and load reduction operation of the distribution network and its system operation constraints;

[0007] S2, taking the distribution network's on-load tap-changing transformer (OLTC) adjustment gear, the operating output of the distributed generation resource set (DGs), and the network structure status as the control objects, uses the crested porcupine optimization algorithm to simulate the crested porcupine's visual intimidation, sound intimidation, odor attack, and physical defense behaviors. Under the premise of meeting the system operation constraints, iteratively optimizes the population to minimize the objective function of the multi-objective optimization problem to determine the optimal on-load tap-changing transformer (OLTC) adjustment gear, the operating output of the distributed generation resource set (DGs), and the network structure status, and issues them for execution.

[0008] Optionally, the objective functions of the multi-objective optimization problem of voltage reduction and load reduction operation of the distribution network in step S1 include an objective function of minimizing network loss, an objective function of minimizing load energy consumption, and an objective function of minimizing voltage deviation.

[0009] Optionally, the function expression of the objective function of minimizing the network loss is:

[0010] ,

[0011] in, is the objective function of minimizing network loss, is the network loss, is the network branch set; For branch The switch state, 1 represents closed, 0 represents open; For branch The resistance, For branch The current amplitude of the load; the function expression of the objective function of minimizing the load energy consumption is:

[0012] ,

[0013] in, is the objective function of minimizing load energy consumption, is the load energy consumption, is the set of network nodes, For nodes The load active power; the function expression of the objective function of minimizing the voltage deviation is:

[0014] ,

[0015] in, is the objective function of minimizing voltage deviation, is the voltage deviation, is the set of network nodes, For nodes The actual voltage, is the rated voltage of the distribution network.

[0016] Optionally, the system operation constraint in step S1 includes an operation equation constraint, which is a forward-backward power flow equation of the distribution network and an on-load tap-changing transformer OLTC regulation constraint as shown in the following equation:

[0017] ,

[0018] in, Node is the network branch set at the head end, For branch The first section active power, For nodes The load active power, Node is the network branch set at the end, For branch The first section active power, For branch The resistance, For branch The first section of reactive power, For nodes The actual voltage, For nodes The active power generated by the distributed generation resources DG; For branch The first section of reactive power, For nodes The reactive power of the load, For branch The reactance, For nodes The reactive power generated by the distributed generation resources DG, For nodes The actual voltage, The substation voltage after adjustment by the on-load tap-changing transformer OLTC, The substation voltage before OLTC regulation, It is the adjustment gear of the on-load tap-changing transformer OLTC. Adjust the voltage for each gear of the on-load tap changing transformer OLTC.

[0019] Optionally, the system operation constraints in step S1 include operation inequality constraints, which include node voltage constraints, branch current constraints, single distributed generation resource DG output constraints, on-load tap-changing transformer OLTC gear constraints, and network topology branch switch state constraints shown in the following formula:

[0020] ,

[0021] in, For the The voltage of each node, and Respectively The lower and upper voltage limits of each node, For branch The current between and Branch The current lower and upper limits between For the The active power generated by the distributed generation resources DG, and Respectively The lower and upper limits of the active power generated by the distributed generation resources DG, For the The reactive power generated by the distributed generation resources DG, and Respectively The lower and upper limits of reactive power generated by distributed generation resources DG, It is the OLTC gear position of the on-load tap-changing transformer. and They are the lower and upper limits of the OLTC gear of the on-load tap-changing transformer respectively; For branch The switch state, 1 represents closed, 0 represents open; is the network branch set; The number of disconnectable branches.

[0022] Optionally, step S2 includes:

[0023] S2.1, initialize and generate a crested porcupine population. The attributes of the crested porcupine individuals in the crested porcupine population include the OLTC adjustment gear, the operating output of the distributed generation resource set DGs, and the network structure state. The iteration variable t is 0, and the number of iterations is T.

[0024] S2.2, calculate the power flow of the power grid based on the OLTC adjustment gear of the individual crested porcupines in the crested porcupine population, the operating output of the distributed generation resource set DGs, and the network structure state, and calculate the function value of the objective function as the fitness of the crested porcupines;

[0025] S2.3, generate five random numbers, including: random number r1 to random number r5;

[0026] S2.4, determine whether the random number r1 is greater than the random number r2. If not, jump to step S2.5; otherwise, jump to step S2.6;

[0027] S2.5, determine whether the random number r3 is greater than the random number r4. If not, enter the visual intimidation phase of the crested porcupine population and update the crested porcupine individuals. Otherwise, enter the sound intimidation phase of the crested porcupine population and update the crested porcupine individuals, then jump to step S2.7;

[0028] S2.6, determine whether the random number r5 is greater than the preset weight percentage T f Is it true? If not, then enter the scent intimidation phase of the crested porcupine population and update the crested porcupine individuals. Otherwise, enter the physical defense phase of the crested porcupine population and update the crested porcupine individuals, and jump to step S2.7.

[0029] S2.7, determining whether the crested porcupine individuals in the crested porcupine population meet the system operation constraints, eliminating invalid crested porcupine individuals that do not meet the system operation constraints, and obtaining a new crested porcupine population;

[0030] S2.8, save the value of the optimal objective function in the new crested porcupine population obtained in this round;

[0031] S2.9, determine whether the iteration variable t is equal to the number of iterations T. If so, the on-load tap-changing transformer OLTC adjustment gear of the crown porcupine individual corresponding to the optimal value of the objective function, the operating output of the distributed generation resource set DGs and the network structure state are used as the optimal on-load tap-changing transformer OLTC adjustment gear, the operating output of the distributed generation resource set DGs and the network structure state and sent down for execution, end and exit; otherwise, add 1 to the iteration variable t and jump to step S2.2.

[0032] Optionally, the function expression for updating the individual crested porcupines in the visual intimidation stage of the crested porcupine population is:

[0033] ,

[0034] ,

[0035] in, for and The average value of is the current solution represented by the current crested porcupine individual, is the random solution represented by a random crested porcupine individual other than the current crested porcupine individual in the crested porcupine population, is a random number, is the global optimal solution represented by the best crested porcupine individual in the crested porcupine population;

[0036] The function expression for updating the crested porcupine individuals in the voice intimidation stage of the crested porcupine population is:

[0037] ,

[0038] in, is a random matrix between 0 and 1, 、 is a random solution represented by a random crested porcupine individual other than the current crested porcupine individual in the crested porcupine population;

[0039] The function expression for updating the crested porcupine individuals in the odor intimidation stage of the crested porcupine population is:

[0040] ,

[0041] ,

[0042] ,

[0043] in, for The fitness of To avoid division by zero errors, is the strategic factor in the odor intimidation stage, is the time decay factor, is the search intensity;

[0044] The function expression for updating the crested porcupine individuals in the physical defense phase of the crested porcupine population is:

[0045] ,

[0046] ,

[0047] ,

[0048] ,

[0049] in, is the strategy factor of the physical defense phase, is the search direction, To control the search intensity parameter, is a random matrix between 0 and 1.

[0050] In addition, the present invention also provides a distribution network voltage reduction and load reduction operation system based on the crown porcupine optimization algorithm, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm.

[0051] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program or instruction, and the computer program or instruction is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm through a processor.

[0052] In addition, the present invention also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm through a processor.

[0053] Compared with existing technologies, the present invention offers the following key advantages: The present invention's distribution network voltage reduction and load reduction optimization operation method, based on the crested porcupine optimization algorithm, simulates the crested porcupine's visual intimidation, acoustic intimidation, odor attack, and physical defense behaviors to establish a corresponding optimization search mechanism. This method, while satisfying constraints, determines the optimal on-load tap-changing transformer (OLTC) adjustment position, distributed generation (DG) operating output, and network structure. This minimizes network losses, load energy consumption, and voltage deviation, effectively maintaining terminal bus voltage quality and further improving the economic efficiency and reliability of the distribution network. This invention uses the crested porcupine optimization algorithm to search for the optimal solution for the multi-objective optimization problem of effectively reducing grid operating costs, minimizing losses, and ensuring voltage quality during peak load periods, effectively improving the algorithm's accuracy, reducing additional investment costs, and improving the economic efficiency of grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 Schematic diagram of the basic process of the method of the embodiment of the present invention.

[0055] Figure 2 Schematic diagram of the solution process of the crested porcupine optimization algorithm in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0057] In modern distribution networks, distributed power sources (DGs), such as solar photovoltaics and wind power, provide a clean and flexible energy source, but they also present new challenges. Traditional distribution network design and operation methods primarily target centralized power supply models. However, with the widespread integration of DGs, grid operation and management become increasingly complex. Effectively reducing grid operating costs, minimizing losses, and ensuring voltage quality, particularly during peak load periods, poses a pressing challenge. Currently, optimization methods for distribution network operation primarily focus on network reconfiguration, load scheduling, and power supply configuration. With the increasing severity of environmental issues, voltage reduction and energy conservation measures are gaining increasing attention. While meeting supply voltage tolerances and preventing damage to electrical equipment, energy consumption can be reduced by operating within a lower voltage range. Currently, some researchers have considered voltage reduction and energy conservation through reactive power compensation using on-load tap-changing transformers, substation capacitor banks, and line capacitor banks in the context of high-penetration PV access distribution systems. Other researchers have proposed a voltage reduction and energy conservation technology that integrates voltage and reactive power optimization control, distribution system control, and the active participation of DGs. However, these approaches are less economical and can suffer from poor adaptability and inaccuracy when solving multi-objective optimization problems. Therefore, the present invention provides a distribution network voltage reduction and load reduction optimization operation method based on the crown porcupine optimization algorithm, which uses the crown porcupine optimization algorithm to search for the optimal solution, effectively improving the accuracy of the algorithm. This method can reduce additional investment costs and improve the economic efficiency of power grid operation. Figure 1 As shown, the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm in this embodiment includes the following steps:

[0058] S1, determine the objective function of the multi-objective optimization problem of voltage reduction and load reduction operation of the distribution network and its system operation constraints;

[0059] S2, taking the distribution network's on-load tap-changing transformer (OLTC) adjustment gear, the operating output of the distributed generation resource set (DGs), and the network structure status as the control objects, uses the crested porcupine optimization algorithm to simulate the crested porcupine's visual intimidation, sound intimidation, odor attack, and physical defense behaviors. Under the premise of meeting the system operation constraints, iteratively optimizes the population to minimize the objective function of the multi-objective optimization problem to determine the optimal on-load tap-changing transformer (OLTC) adjustment gear, the operating output of the distributed generation resource set (DGs), and the network structure status, and issues them for execution.

[0060] In step S1 of this embodiment, the objective functions of the multi-objective optimization problem of voltage reduction and load reduction operation of the distribution network include an objective function of minimizing network loss, an objective function of minimizing load energy consumption, and an objective function of minimizing voltage deviation.

[0061] The functional expression of the objective function for minimizing network loss in this embodiment is:

[0062] ,

[0063] in, is the objective function of minimizing network loss, is the network loss, is the network branch set; For branch The switch state, 1 represents closed, 0 represents open; For branch The resistance, For branch The current amplitude of the load; the function expression of the objective function of minimizing the load energy consumption is:

[0064] ,

[0065] in, is the objective function of minimizing load energy consumption, is the load energy consumption, is the set of network nodes, For nodes The load active power; the function expression of the objective function of minimizing the voltage deviation is:

[0066] ,

[0067] in, is the objective function of minimizing voltage deviation, is the voltage deviation, is the set of network nodes, For nodes The actual voltage, is the rated voltage of the distribution network.

[0068] In step S1 of this embodiment, the system operation constraint condition includes an operation equation constraint, which is a forward-backward power flow equation of the distribution network and an on-load tap-changing transformer (OLTC) regulation constraint as shown in the following equation:

[0069] ,

[0070] in, Node is the network branch set at the head end, For branch The first section active power, For nodes The load active power, Node is the network branch set at the end, For branch The first section active power, For branch The resistance, For branch The first section of reactive power, For nodes The actual voltage, For nodes The active power generated by the distributed generation resources DG; For branch The first section of reactive power, For nodes The reactive power of the load, For branch The reactance, For nodes The reactive power generated by the distributed generation resources DG, For nodes The actual voltage, The substation voltage after adjustment by the on-load tap-changing transformer OLTC, The substation voltage before OLTC regulation, It is the adjustment gear of the on-load tap-changing transformer OLTC. The voltage is adjusted for each gear of the OLTC. The forward-backward substitution power flow equation of the above distribution network and the OLTC regulation constraint of the OLTC contain four equations. The first equation represents the outflow j The active power of the node is j The sum of the active power of the loads at the node is equal to the power flowing into j The active power of the point j The sum of the active power output of the node DG, the second formula represents the outflow j The reactive power of the node is j The sum of the reactive power of the loads at the node is equal to the power flowing into j The reactive power of the point j The sum of the reactive power output of the node DG, the third equation is the voltage distribution equation, and the fourth equation is the OLTC regulation constraint.

[0071] In step S1 of this embodiment, the system operation constraint conditions include operation inequality constraints, which include node voltage constraints, branch current constraints, single distributed generation resource DG output constraints, on-load tap-changing transformer OLTC gear constraints, and network topology branch switch state constraints as shown in the following formula:

[0072] ,

[0073] in, For the The voltage of each node, and Respectively The lower and upper voltage limits of each node, For branch The current between and Branch The current lower and upper limits between For the The active power generated by the distributed generation resources DG, and Respectively The lower and upper limits of the active power generated by the distributed generation resources DG, For the The reactive power generated by the distributed generation resources DG, and Respectively The lower and upper limits of reactive power generated by distributed generation resources DG, It is the OLTC gear position of the on-load tap-changing transformer. and They are the lower and upper limits of the OLTC gear of the on-load tap-changing transformer respectively; For branch The switch state, 1 represents closed, 0 represents open; is the network branch set; The number of disconnectable branches.

[0074] The crested porcupine optimization algorithm simulates four defense strategies of crested porcupines when facing predators: visual intimidation, sound intimidation, odor attack, and physical defense. Each strategy corresponds to a set of specific search or movement rules used to update the positions of candidate solutions and ultimately determine the optimal solution. Figure 2 As shown, step S2 of this embodiment includes:

[0075] S2.1, initialize and generate a crested porcupine population. The attributes of the crested porcupine individuals in the crested porcupine population include the OLTC adjustment gear, the operating output of the distributed generation resource set DGs, and the network structure state. The iteration variable t is 0, and the number of iterations is T.

[0076] S2.2, calculate the power flow of the power grid based on the OLTC adjustment gear of the individual crested porcupines in the crested porcupine population, the operating output of the distributed generation resource set DGs, and the network structure state, and calculate the function value of the objective function as the fitness of the crested porcupines;

[0077] S2.3, generate five random numbers, including: random number r1 to random number r5;

[0078] S2.4, determine whether the random number r1 is greater than the random number r2. If not, jump to step S2.5; otherwise, jump to step S2.6;

[0079] S2.5, determine whether the random number r3 is greater than the random number r4. If not, enter the visual intimidation phase of the crested porcupine population and update the crested porcupine individuals. Otherwise, enter the sound intimidation phase of the crested porcupine population and update the crested porcupine individuals, then jump to step S2.7;

[0080] S2.6, determine whether the random number r5 is greater than the preset weight percentage T f Is it true? If not, then enter the scent intimidation phase of the crested porcupine population and update the crested porcupine individuals. Otherwise, enter the physical defense phase of the crested porcupine population and update the crested porcupine individuals, and jump to step S2.7.

[0081] S2.7, determining whether the crested porcupine individuals in the crested porcupine population meet the system operation constraints, eliminating invalid crested porcupine individuals that do not meet the system operation constraints, and obtaining a new crested porcupine population;

[0082] S2.8, save the value of the optimal objective function in the new crested porcupine population obtained in this round;

[0083] S2.9, determine whether the iteration variable t is equal to the number of iterations T. If so, the on-load tap-changing transformer OLTC adjustment gear of the crown porcupine individual corresponding to the optimal value of the objective function, the operating output of the distributed generation resource set DGs and the network structure state are used as the optimal on-load tap-changing transformer OLTC adjustment gear, the operating output of the distributed generation resource set DGs and the network structure state and sent down for execution, end and exit; otherwise, add 1 to the iteration variable t and jump to step S2.2.

[0084] Visual intimidation is when crested porcupines display their bright colors and quills to scare away predators. In the algorithm, this can be understood as individuals moving significantly toward the optimal solution, and increasing population diversity by randomly perturbing candidate solutions. In this embodiment, the function expression for updating crested porcupine individuals during the visual intimidation phase of the crested porcupine population is:

[0085] ,

[0086] ,

[0087] in, for and The average value of is the current solution represented by the current crested porcupine individual, is the random solution represented by a random crested porcupine individual other than the current crested porcupine individual in the crested porcupine population, is a random number, The global optimal solution represented by the best crested porcupine individual in the crested porcupine population.

[0088] Sound intimidation is a warning sound made by crested porcupines to scare away potential dangers. In the algorithm, it can be regarded as a small adjustment of the individual position to maintain the stability of the population and avoid falling into a local optimum. In this embodiment, the function expression for updating the crested porcupine individuals during the sound intimidation phase of the crested porcupine population is:

[0089] ,

[0090] in, is a random matrix between 0 and 1, 、 The random solution represented by a random crested porcupine individual other than the current one in the crested porcupine population.

[0091] Odor attack is a defense mechanism released by crested porcupines. In optimization, it can be considered as information exchange between individuals to explore new areas of the solution space. In this embodiment, the function expression for updating crested porcupine individuals during the odor intimidation phase of the crested porcupine population is:

[0092] ,

[0093] ,

[0094] ,

[0095] in, for The fitness of To avoid division by zero errors, is the strategic factor in the odor intimidation stage, is the time decay factor, is the search intensity.

[0096] Physical defense is the use of quills by crested porcupines as a last resort. In the optimization algorithm, this can represent strict protection of the current best solution while exploring other solutions. In this embodiment, the function expression for updating crested porcupine individuals in the physical defense phase of the crested porcupine population is:

[0097] ,

[0098] ,

[0099] ,

[0100] ,

[0101] in, is the strategy factor of the physical defense phase, is the search direction, To control the search intensity parameter, is a random matrix between 0 and 1.

[0102] In summary, the core of this embodiment's distribution network voltage reduction and load reduction method, based on the crested porcupine optimization algorithm, simulates the crested porcupine's four defensive strategies against predators and transforms the mathematical models of these strategies into an optimization search process. By simulating the crested porcupine's visual intimidation, acoustic intimidation, odor attack, and physical defense behaviors, the algorithm constructs a corresponding optimization search mechanism. This algorithm then determines the optimal OLTC adjustment position, operating output of distributed generation resources (DGs), and network structure, while satisfying constraints. This optimizes the objective function that minimizes network losses, load energy consumption, and voltage deviation. This application of the present invention effectively maintains terminal bus voltage quality during peak load periods, while simultaneously achieving optimized distribution network operation, minimizing total energy consumption, and improving the grid's economy and reliability.

[0103] In addition, this embodiment also provides a distribution network voltage reduction and load reduction operation system based on the crown porcupine optimization algorithm, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm.

[0104] In addition, this embodiment also provides a computer-readable storage medium, which stores a computer program or instruction, and the computer program or instruction is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm through a processor.

[0105] In addition, this embodiment also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crown porcupine optimization algorithm through a processor.

[0106] Those skilled in the art should understand that the technical solutions provided by the embodiments of the present application may be in the form of methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including the instruction device, which implements the function specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0107] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for reducing voltage and load in a distribution network based on a crown porcupine optimization algorithm, characterized in that: The steps include: S1, determine the objective function of the multi-objective optimization problem of voltage reduction and load reduction operation of the distribution network and its system operation constraints; S2, taking the distribution network's on-load tap-changing transformer (OLTC) adjustment gear, the operating output of the distributed generation resource (DGs), and the network structure as the control objects, uses the crested porcupine optimization algorithm to simulate the crested porcupine's visual intimidation, sound intimidation, odor attack, and physical defense behaviors. Under the premise of meeting the system's operating constraints, iteratively optimizes the population to minimize the objective function of the multi-objective optimization problem to determine the optimal on-load tap-changing transformer (OLTC) adjustment gear, the operating output of the distributed generation resource (DGs), and the network structure, and issues them for execution; The objective functions of the multi-objective optimization problem of voltage reduction and load reduction operation of the distribution network in step S1 include an objective function of minimizing network loss, an objective function of minimizing load energy consumption, and an objective function of minimizing voltage deviation; Step S2 includes: S2.1, initialize and generate a crested porcupine population. The attributes of the crested porcupine individuals in the crested porcupine population include the OLTC adjustment gear, the operating output of the distributed generation resource set DGs, and the network structure state. The iteration variable t is 0, and the number of iterations is T. S2.2, calculate the power flow of the power grid based on the OLTC adjustment gear of the individual crested porcupines in the crested porcupine population, the operating output of the distributed generation resource set DGs, and the network structure state, and calculate the function value of the objective function as the fitness of the crested porcupines; S2.3, generate five random numbers, including: random number r1 to random number r5; S2.4, determine whether the random number r1 is greater than the random number r2. If not, jump to step S2.5; otherwise, jump to step S2.6; S2.5, determine whether the random number r3 is greater than the random number r4. If not, enter the visual intimidation phase of the crested porcupine population and update the crested porcupine individuals. Otherwise, enter the sound intimidation phase of the crested porcupine population and update the crested porcupine individuals, then jump to step S2.7; S2.6, determine whether the random number r5 is greater than the preset weight percentage T f Is it true? If not, then enter the scent intimidation phase of the crested porcupine population and update the crested porcupine individuals. Otherwise, enter the physical defense phase of the crested porcupine population and update the crested porcupine individuals, and jump to step S2.

7. S2.7, determining whether the crested porcupine individuals in the crested porcupine population meet the system operation constraints, eliminating invalid crested porcupine individuals that do not meet the system operation constraints, and obtaining a new crested porcupine population; S2.8, save the value of the optimal objective function in the new crested porcupine population obtained in this round; S2.9, determine whether the iteration variable t is equal to the number of iterations T. If so, the on-load tap-changing transformer OLTC adjustment gear of the crown porcupine individual corresponding to the optimal value of the objective function, the operating output of the distributed generation resource set DGs and the network structure state are used as the optimal on-load tap-changing transformer OLTC adjustment gear, the operating output of the distributed generation resource set DGs and the network structure state and sent down for execution, end and exit; otherwise, add 1 to the iteration variable t and jump to step S2.

2.

2. The method for reducing voltage and load of a distribution network based on the crown porcupine optimization algorithm according to claim 1, characterized in that: The functional expression of the objective function of minimizing the network loss is: ， in, is the objective function of minimizing network loss, is the network loss, is the network branch set; For branch The switch state, 1 represents closed, 0 represents open; For branch The resistance, For branch The current amplitude of the load; the function expression of the objective function of minimizing the load energy consumption is: ， in, is the objective function of minimizing load energy consumption, is the load energy consumption, is the set of network nodes, For nodes The load active power; the function expression of the objective function of minimizing the voltage deviation is: ， in, is the objective function of minimizing voltage deviation, is the voltage deviation, is the set of network nodes, For nodes The actual voltage, is the rated voltage of the distribution network.

3. The method for reducing voltage and load of a distribution network based on the crown porcupine optimization algorithm according to claim 2, characterized in that: The system operation constraints in step S1 include operation equation constraints, which are the forward and backward power flow equations of the distribution network and the OLTC regulation constraints shown in the following equations: ， in, Node is the network branch set at the head end, For branch The first section active power, For nodes The load active power, Node is the network branch set at the end, For branch The first section active power, For branch The resistance, For branch The first section of reactive power, For nodes The actual voltage, For nodes The active power generated by the distributed generation resources DG; For branch The first section of reactive power, For nodes The reactive power of the load, For branch The reactance, For nodes The reactive power generated by the distributed generation resources DG, For nodes The actual voltage, The substation voltage after adjustment by the on-load tap-changing transformer OLTC, The substation voltage before OLTC regulation, It is the adjustment gear of the on-load tap-changing transformer OLTC. Adjust the voltage for each gear of the on-load tap changing transformer OLTC.

4. The method for reducing voltage and load of a distribution network based on the crown porcupine optimization algorithm according to claim 2, characterized in that: The system operation constraints in step S1 include operation inequality constraints, which include node voltage constraints, branch current constraints, single distributed generation resource DG output constraints, on-load tap-changing transformer OLTC gear constraints, and network topology branch switch state constraints as shown in the following formula: ， in, For the The voltage of each node, and Respectively The lower and upper voltage limits of each node, For branch The current between and Branch The current lower and upper limits between For the The active power generated by the distributed generation resources DG, and Respectively The lower and upper limits of the active power generated by the distributed generation resources DG, For the The reactive power generated by the distributed generation resources DG, and Respectively The lower and upper limits of reactive power generated by distributed generation resources DG, It is the OLTC gear position of the on-load tap-changing transformer. and They are the lower and upper limits of the OLTC gear of the on-load tap-changing transformer respectively; For branch The switch state, 1 represents closed, 0 represents open; is the network branch set; The number of disconnectable branches.

5. The method for reducing voltage and load of a distribution network based on the crown porcupine optimization algorithm according to claim 1, characterized in that: The function expression for updating the crested porcupine individuals in the visual intimidation stage of the crested porcupine population is: ， ， in, for and The average value of is the current solution represented by the current crested porcupine individual, is the random solution represented by a random crested porcupine individual other than the current crested porcupine individual in the crested porcupine population, is a random number, is the global optimal solution represented by the best crested porcupine individual in the crested porcupine population; The function expression for updating the crested porcupine individuals in the voice intimidation stage of the crested porcupine population is: ， in, is a random matrix between 0 and 1, 、 is a random solution represented by a random crested porcupine individual other than the current crested porcupine individual in the crested porcupine population; The function expression for updating the crested porcupine individuals in the odor intimidation stage of the crested porcupine population is: ， ， ， in, for The fitness of To avoid division by zero errors, is the strategic factor in the odor intimidation stage, is the time decay factor, is the search intensity; The function expression for updating the crested porcupine individuals in the physical defense phase of the crested porcupine population is: ， ， ， ， in, is the strategy factor of the physical defense phase, is the search direction, To control the search intensity parameter, is a random matrix between 0 and 1.

6. A distribution network voltage reduction and load reduction operation system based on the crown porcupine optimization algorithm, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crested porcupine optimization algorithm as described in any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crested porcupine optimization algorithm as described in any one of claims 1 to 5 through a processor.

8. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the distribution network voltage reduction and load reduction operation method based on the crested porcupine optimization algorithm as described in any one of claims 1 to 5 through a processor.

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