Power grid voltage reduction and energy saving method based on swarm intelligence algorithm

Abstract

The invention provides a power grid step-down energy-saving method based on a swarm intelligence algorithm, relates to the technical field of power grid planning and energy management, and solves the problem of how to guarantee the operation efficiency and stability of a power system while realizing an overall energy-saving target by optimizing load power and reducing power loss of a power transmission line in the step-down energy-saving process. The method comprises the following steps: determining a power grid structure accessed to a user load, determining a user side load model, and constructing different types of load cluster models; establishing a mathematical optimization model of a power grid voltage regulation and energy conservation problem, wherein the mathematical optimization model corresponds to all the established load cluster models; a swarm intelligence algorithm is adopted in the mathematical optimization model, and the power grid voltage regulation and energy saving problem is solved in an iterative updating mode; an iteration termination condition in the solving process is preset, and a power grid voltage regulation scheme under the corresponding condition is obtained after iteration calculation is terminated; according to the invention, the load power consumption can be reduced, and the power loss of the power transmission line can be reduced, so that the comprehensive effect of overall energy conservation is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid planning and energy management, and can be applied to the optimization process of load power and transmission line loss, and specifically relates to a power grid voltage reduction and energy saving method based on a swarm intelligence algorithm. Background Art

[0002] With the rapid development of China's economy and the acceleration of urbanization, energy consumption has shown a trend of increasing year by year. This phenomenon has not only led to the problem of tight energy supply, but also triggered a series of challenges such as increased environmental pollution. Especially in the power sector, the rapid growth of user electricity demand has significantly increased the load on the power grid, which not only increases the pressure on the transmission network, but also may lead to the risk of reduced power quality and reduced power supply stability.

[0003] In order to meet these challenges and achieve long-term sustainable development goals, the Chinese government has been committed to promoting energy conservation and emission reduction policies and actively promoting various energy-saving technologies. Among the many energy-saving measures, voltage reduction has received widespread attention because it can effectively reduce overall energy consumption. By reasonably adjusting the supply voltage, while ensuring normal power consumption for users, the load power of the entire system can be effectively reduced. Doing so will help ease the pressure on the power grid, reduce unnecessary power loss, and thus improve the economic benefits of the power system.

[0004] However, implementing the voltage reduction energy-saving strategy is not without obstacles. Since different types of loads show different sensitivities to voltage changes, certain difficulties are encountered in the actual operation process. For example, for constant impedance loads, when the supply voltage drops, its power consumption will also decrease accordingly; but for equipment such as air conditioning systems and industrial motors, the voltage reduction may cause their working efficiency to decrease or even cause failures. In addition, when faced with a voltage drop, constant power loads will increase current to maintain the original power output, which will directly lead to overheating of the equipment and shorten its service life.

[0005] In addition, it is worth noting that when considering the voltage reduction energy-saving scheme, the relationship between the load type and the energy loss of the transmission line must also be taken into account. Although appropriately reducing the voltage can reduce the power consumption of some resistive loads, for some constant power loads, the voltage reduction may lead to an increase in current, thereby increasing the energy loss on the transmission line. Therefore, the implementation of the voltage reduction energy-saving scheme should be comprehensively evaluated based on the load characteristics and system operating conditions to ensure that it can achieve the purpose of energy saving and minimize the additional loss problem.

[0006] In summary, although voltage reduction and energy saving provide a potential and effective way to solve some key energy problems currently facing the country, it is still necessary to comprehensively consider the influence of various factors in the specific implementation process in order to achieve the best results. Summary of the invention

[0007] Based on the current status of the background technology, the purpose of the present invention is to solve the problem of how to achieve the overall energy-saving goal while ensuring the operating efficiency and stability of the power system by reducing the user load power and line power loss during the voltage reduction and energy saving process. Therefore, a power grid voltage reduction and energy saving method based on a swarm intelligence algorithm is proposed. The present invention utilizes the powerful optimization ability of the swarm intelligence algorithm, combines the characteristics of different loads, and proposes a feasible voltage regulation scheme, which can reduce load power consumption and reduce transmission line losses, thereby achieving a comprehensive effect of overall energy saving.

[0008] The present invention adopts the following technical solutions to achieve the purpose:

[0009] A power grid voltage reduction and energy saving method based on a swarm intelligence algorithm, the method comprising the following steps:

[0010] S1. Collect grid data and determine the grid structure connected to user loads;

[0011] S2. Determine the user-side load model based on the grid structure;

[0012] S3. Based on the user-side load model, build different types of load cluster models;

[0013] S4, establishing a mathematical optimization model for the problem of power grid voltage regulation and energy saving, the mathematical optimization model corresponding to all the load cluster models that have been constructed;

[0014] S5. Use swarm intelligence algorithm in mathematical optimization model to solve the problem of grid voltage regulation and energy saving in an iterative update manner;

[0015] S6. Preset the iterative termination condition in the solution process, and obtain the grid voltage regulation plan under the corresponding condition after the iterative calculation is terminated.

[0016] Specifically, in step S1, the grid structure data of the load cluster connected to the substation is collected and organized according to the grid manual and grid operation monitoring data; based on the determined grid structure, the safe operation range of each power equipment in the grid and the maximum load carrying power at the access location of each substation load cluster are further determined.

[0017] Furthermore, in step S2, by analyzing the relationship between the voltage and power changes of the user-side load, the load characteristics corresponding to the user-side load are determined, and then the user-side load model is determined; the types of user-side loads include constant impedance loads, constant power loads and temperature-controlled loads.

[0018] Specifically, when analyzing constant impedance loads, based on the theoretical basis that the power decreases accordingly when the voltage decreases, the proportional relationship between the power of this type of load and the square of the voltage drop is verified; when analyzing constant power loads, the linear correlation between the power change and voltage change of this type of load is determined; when analyzing temperature-controlled loads, based on the change in power when the voltage is reduced, the association between this type of load and the corresponding equipment type and control method is determined.

[0019] Preferably, in step S3, the user-side load model has a plurality of different types of user-side loads; when constructing a load cluster, first determine the access ratio range of each type of user-side load in the substation; then, within the access ratio range, randomly generate specific access ratios of each type of user-side load to complete the construction of the load cluster model.

[0020] Furthermore, in step S4, the mathematical optimization model includes an optimization objective and a system constraint; the optimization objective is to optimize the load power and line loss of the substation power grid through the mathematical optimization model; and the system constraint is used to ensure the normal operating conditions of the power grid during the optimization process.

[0021] Specifically, when optimizing the load power and line power loss of the power grid, the minimum sum of the load power and the line power loss is used as the quantitative indicator of the optimization target; when the mathematical optimization model optimizes the operating state of the power grid by adjusting the voltage, the user-side load power and line power loss are comprehensively considered to achieve the determination of the optimization target.

[0022] Specifically, system constraints include equality constraints and inequality constraints; equality constraints are used to ensure the active power balance and reactive power balance of the power grid, thereby ensuring the stable operation of the power grid; inequality constraints are used to ensure that various parameters in the power system operate within a preset safe and reasonable range, and maintain the stability of the power system during the optimization process of voltage reduction and energy saving.

[0023] Preferably, in step S5, after adopting the swarm intelligence algorithm, the swarm intelligence algorithm is improved according to the nonlinear and non-convex characteristics of the grid voltage regulation and energy-saving problem; the improvement strategy includes dynamic adjustment of parameters and introduction of weight coefficients; in step S6, the setting of the iteration termination condition is based on the scale of the grid; the number of iterations in the iteration termination condition increases with the increase of the scale of the grid.

[0024] Preferably, after obtaining multiple grid voltage regulation schemes through step S6, the method further includes:

[0025] S7. During the iterative calculation process, Newton-Raphson power flow calculation is performed on each voltage regulation scheme on the power grid connected to the substation load cluster, and the constraint violation value, substation load power value and line loss value corresponding to each power grid voltage regulation scheme are obtained, and the feasibility and advantages and disadvantages of each power grid voltage regulation scheme are comprehensively evaluated;

[0026] S8. Delete the grid voltage regulation schemes with non-zero constraint violation values; among the remaining grid voltage regulation schemes, analyze the dynamic relationship between the voltage regulation rate and the load cluster power curve, and select the optimal voltage regulation scheme as a dispatch reference scheme for power decision makers.

[0027] In summary, due to the adoption of this technical solution, the beneficial effects of the present invention are as follows:

[0028] The present invention can adapt to diverse load conditions and fully consider the characteristics of different types of loads. Therefore, it is not only suitable for power systems with different structures, but also can well cope with actual scenarios with variable user loads, showing high flexibility and wide applicability.

[0029] In addition, in the process of designing voltage regulation schemes using swarm intelligence algorithms, the present invention gradually selects feasible schemes that meet various constraints of the power system through iteration, effectively avoiding the existence of unsafe or unstable factors, thereby ensuring the safe and stable operation of the power system. The elimination mechanism in this process effectively improves the reliability of the entire system.

[0030] The swarm intelligence algorithm itself has a powerful parallel search capability, which enables the present invention to provide high-quality and efficient voltage regulation suggestions to power decision makers in a relatively short time. This means that even in the face of complex power grid conditions, the best voltage regulation solution can be found quickly, greatly reducing time costs and improving decision-making efficiency.

[0031] The present invention is very suitable for solving multi-objective optimization problems in the field of power grid planning. It not only focuses on reducing the load power consumption of users, but also pays attention to reducing the energy loss in the transmission line, and determines the optimal voltage regulation strategy by comprehensively considering these key factors. Such a processing method helps to improve the operational stability and economic benefits of the power system at the same time, and provides strong support for achieving a more efficient and environmentally friendly power supply. It can be seen that the present invention has shown obvious advantages in promoting energy conservation and emission reduction, ensuring power supply quality, and enhancing the economy of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Detailed flow chart of the method of the present invention;

[0033] Figure 2 A schematic diagram of the structure of an electric power system according to an example of the present invention;

[0034] Figure 3 The following is a schematic diagram of load power and line loss of an exemplary power system under different voltage regulation levels after applying the method of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0036] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Example 1

[0038] A power grid voltage reduction and energy saving method based on swarm intelligence algorithm. Figure 1 The flow of the method and the key points of each part are shown, which can be viewed simultaneously; the steps of the method can be summarized as follows:

[0039] S1. Collect grid data and determine the grid structure connected to user loads;

[0040] S2. Determine the user-side load model based on the grid structure;

[0041] S3. Based on the user-side load model, build different types of load cluster models;

[0042] S4, establishing a mathematical optimization model for the problem of power grid voltage regulation and energy saving, the mathematical optimization model corresponding to all the load cluster models that have been constructed;

[0043] S5. Use swarm intelligence algorithm in mathematical optimization model to solve the problem of grid voltage regulation and energy saving in an iterative update manner;

[0044] S6. Preset the iterative termination condition in the solution process, and obtain the grid voltage regulation plan under the corresponding condition after the iterative calculation is terminated.

[0045] This embodiment will introduce the details of each step in detail according to the above step sequence.

[0046] Step S1: Collection and preparation of power grid data

[0047] According to the power grid manual and power grid operation monitoring data, collect and organize the power grid structure data of the load cluster connected to the substation; based on the determined power grid structure, further determine the safe operation range of each power equipment in the power grid, as well as the maximum load-bearing power at the access location of each substation load cluster.

[0048] It can be briefly explained here that the power grid manual can be a matpower manual. MATPOWER is a software toolbox for power system analysis and optimization, which can perform industrial applications for power system related tasks. The term "substation" here refers to the area powered by a transformer, which is a basic unit in a distribution network. The data collected at this step in this embodiment includes key information such as safe operating parameters of power equipment and the maximum load carrying capacity of the access location of the substation load cluster.

[0049] Step S2: Load characteristics analysis

[0050] By analyzing the relationship between the voltage and power changes of the user-side load, the load characteristics corresponding to the user-side load are determined, and then the user-side load model is determined. In this embodiment, the types of user-side loads include constant impedance loads, constant power loads, and temperature control loads.

[0051] When analyzing constant impedance loads, based on the theoretical basis that power decreases accordingly when voltage decreases, the proportional relationship between the power of this type of load and the square of the voltage drop is verified.

[0052] When analyzing constant power loads, determine the linear correlation between the power change and voltage change of this type of load.

[0053] When analyzing temperature-controlled loads, determine the relationship between this type of load and the corresponding equipment type and control method based on the change in power when the voltage is reduced.

[0054] Step S3: Building a load cluster model

[0055] According to the data obtained in the above steps, the user-side load model will have a variety of different types of user-side loads. When constructing a load cluster, this embodiment first determines the access ratio range of each type of user-side load in the substation; then uses Monte Carlo and other similar methods to randomly generate specific access ratios of each type of user-side load within the access ratio range, thereby completing the construction of the load cluster model. The Monte Carlo method is a computational algorithm based on random sampling and statistical experiments. It is based on probability theory and solves various problems by generating a large number of random samples. It is suitable for application in this step of this embodiment.

[0056] Step S4: Mathematical modeling and constraint setting

[0057] The mathematical optimization model established in this step includes optimization objectives and system constraints; the optimization objective is to optimize the load power and line loss of the substation power grid through the mathematical optimization model; the system constraints are used to ensure the normal operating conditions of the power grid during the optimization process.

[0058] In this embodiment, when optimizing the load power and line loss of the power grid, the minimum sum of the load power and the line power loss is used as the quantitative indicator of the optimization target; when the mathematical optimization model optimizes the operating state of the power grid by adjusting the voltage, the user-side load power and line power loss are comprehensively considered, so that the economic benefits and power supply stability can be more comprehensively taken into account, thereby improving the overall benefits of the power system.

[0059] The determined optimization objective Obj is as follows:

[0060] Obj=min(P load +P loss )

[0061] Where P load Represents load power, P loss Represents the line power loss; the specific formula is as follows:

[0062]

[0063] In the formula, α+β+γ=1, α, β, and γ represent the corresponding proportions of constant impedance load, constant power load, and temperature control load in the substation respectively; Respectively represent the corresponding load power of constant impedance load, constant power load and temperature control load; N L Represents the number of branches in the power grid, c k represents the conductance of the kth transmission branch connecting the i-th node and the j-th node; V i 、V j Represent the corresponding voltage amplitudes of the i-th node and the j-th node, δ ij Represents the phase angle difference between the i-th node and the j-th node.

[0064] In this embodiment, the system constraints include equality constraints and inequality constraints; the equality constraints are used to ensure the active power balance and reactive power balance of the power grid, thereby ensuring the stable operation of the power grid, as shown in the following formula:

[0065]

[0066] Where P Gi represents the active power of the i-th generator, P Di represents the active power of the i-th load node; Q Gi represents the reactive power of the i-th generator, Q Di represents the reactive power of the i-th load node; G ij , B ij represent the mutual conductance and mutual susceptance between the ith node and the jth node respectively; N represents the number of nodes in the power grid except the balancing node, N i Represents the number of nodes connected to the i-th node, NPQ Represents the total number of load nodes;

[0067] Inequality constraints are used to ensure that various parameters in the power system operate within a preset safe and reasonable range, and play a key role in maintaining the stability and reliability of the power system during the optimization process of voltage reduction and energy saving. They include the following:

[0068]

[0069]

[0070] In the above formulas, V Gi represents the voltage of the i-th generator, N G Represents the number of generators in the power grid; V Li represents the voltage of the ith load node, T i represents the transformation ratio of the i-th transformer, N T Represents the number of transformers in the power grid; Q Ci represents the switching of the i-th reactive power compensation device, N C Represents the number of reactive power compensation devices; S l represents the apparent power of the lth line, N L Indicates the number of lines; superscript (...) min Represents the lower limit of the corresponding parameter, and the superscript (…) max Represents the upper limit value of the corresponding parameter; Represents the sum of load power, P access Represents the maximum load power that the corresponding node in the power grid can bear.

[0071] Step S5: Improvement and application of swarm intelligence algorithm

[0072] Swarm intelligence is a computational method inspired by the collective behavior of simple individuals in nature through local interactions. These individuals can be groups of organisms such as ants, bees, and bird flocks that follow simple rules but can complete complex tasks or exhibit advanced behavioral patterns as a whole. Swarm intelligence algorithms mimic this natural phenomenon to solve optimization problems, search problems, and other challenges in complex systems.

[0073] In this embodiment, a swarm intelligence algorithm with wide applicability can be selected to solve the problem of power grid voltage regulation and energy saving. Moreover, after adopting the swarm intelligence algorithm, the swarm intelligence algorithm can be improved according to the nonlinear and non-convex characteristics of the power grid voltage regulation and energy saving problem. The improvement strategy includes dynamic parameter adjustment and introduction of weight coefficients, so that the final set of methods is formed into a voltage reduction and energy saving method that can comprehensively optimize the load power and the power loss of the transmission line.

[0074] Step S6: Setting of iteration termination conditions

[0075] The setting of the iteration termination condition is based on the scale of the power grid. The number of iterations in the iteration termination condition increases with the scale of the power grid; for example, in a larger-scale power grid, appropriately increasing the number of iterations can ensure convergence when exploring the power grid voltage regulation scheme with the smallest sum of the load power and the line power loss.

[0076] As a preferred part of this embodiment, after multiple grid voltage regulation schemes are obtained through step S6, the entire grid voltage reduction and energy saving method may also include two parts, steps S7 and S8.

[0077] Step S7: Power flow calculation and scheme evaluation

[0078] During the iterative calculation process, Newton-Raphson power flow calculation is performed on each voltage regulation scheme on the power grid connected to the substation load cluster to obtain the constraint violation value, substation load power value and line loss value corresponding to each power grid voltage regulation scheme, and comprehensively evaluate the feasibility and advantages and disadvantages of each power grid voltage regulation scheme.

[0079] Step S8: Screening and optimization of solutions

[0080] The grid voltage regulation schemes with non-zero constraint violation values ​​are deleted to ensure the safe and stable operation of the grid. Among the remaining grid voltage regulation schemes, the dynamic relationship between the voltage regulation rate and the load cluster power curve is deeply studied, and the optimal grid voltage regulation scheme is selected accordingly, that is, the scheme that minimizes the sum of the load power and line loss in the substation area, which can be used as a dispatch reference scheme for power decision makers.

[0081] Example 2

[0082] Based on the method of Example 1, this example uses an exemplary power system grid structure to demonstrate the application of the method of the present invention.

[0083] The power system of the example is as follows Figure 2 The IEEE 30-bus power system shown in the figure provides a standardized platform for power system analysis, planning, control and optimization. The IEEE 30-bus power system is an important benchmark model in power grid planning and energy management research, and has a key reference value for voltage regulation and energy saving research.

[0084] In this embodiment, a cluster of stations including constant impedance load, constant power load and temperature control load is connected at the 20th node of the IEEE 30-node power system. The access ratios of the above three load types are randomly generated. In this embodiment, the access ratio of constant impedance load is 24.0%, the access ratio of constant power load is 43.9%, and the access ratio of temperature control load is 32.1%.

[0085] The maximum load power of the 20th node in the IEEE 30-node power system is 2.2 MW. In this embodiment, the power margin factor of the node is 0.8 to cope with load fluctuations.

[0086] In this embodiment, the voltage adjustment gears are 5 gears, and adjusting 1 gear means adjusting the voltage by 1.25%. The situations where the voltage drops by 2.50% and rises by 2.50% are analyzed respectively.

[0087] In this embodiment, the swarm intelligence algorithm selected is the bat algorithm, and the grid voltage regulation scheme determined by the bat algorithm is used to comprehensively optimize the load power of the substation and the power loss of the line. As a heuristic search method, the bat algorithm is inspired by the behavior of bats in nature using echolocation to find prey. It has good global search capabilities and fast convergence speed, fewer parameters and is easy to implement, and can effectively avoid falling into the local optimal solution.

[0088] The following is a display of the results of the application example. In this embodiment, the grid voltage reduction energy saving method after the bat algorithm is used. The user load power, the line loss of the IEEE30-node transmission network and the sum of the two are respectively achieved under 5 voltage levels. Figure 3 shown.

[0089] When only optimizing user load power is considered, the load power change caused by voltage regulation is basically positively correlated with the voltage change. When the regulated voltage drops by 2.50%, the load power of the substation drops by up to 1.7862%. When considering the user load power and the power loss of the transmission line, the change of the sum of the two no longer shows a simple positive correlation with the voltage change. When the regulated voltage drops by 1.25%, the load power and line loss of the substation drop by up to 1.4979%.

[0090] This example demonstrates the effectiveness of the grid voltage reduction and energy-saving method of the present invention in optimizing load power and transmission line losses.

Claims

1. A power grid voltage reduction and energy saving method based on swarm intelligence algorithm, characterized in that: The method comprises the following steps: S1. Collect grid data and determine the grid structure connected to user loads; S2. Determine the user-side load model based on the grid structure; S3. Based on the user-side load model, build different types of load cluster models; S4, establishing a mathematical optimization model for the problem of power grid voltage regulation and energy saving, the mathematical optimization model corresponding to all the load cluster models that have been constructed; S5. Use swarm intelligence algorithm in mathematical optimization model to solve the problem of grid voltage regulation and energy saving in an iterative update manner; S6. Preset the iterative termination condition in the solution process, and obtain the grid voltage regulation plan under the corresponding condition after the iterative calculation is terminated.

2. The method for reducing voltage and saving energy in a power grid according to claim 1, characterized in that: In step S1, the grid structure data of the load cluster connected to the substation is collected and organized according to the grid manual and grid operation monitoring data; based on the determined grid structure, the safe operation range of each power equipment in the grid and the maximum load carrying power at the access location of each substation load cluster are further determined.

3. The power grid voltage reduction and energy saving method according to claim 1, characterized in that: In step S2, by analyzing the relationship between the voltage and power changes of the user-side load, the load characteristics corresponding to the user-side load are determined, and then the user-side load model is determined; the types of user-side loads include constant impedance loads, constant power loads and temperature-controlled loads.

4. The power grid voltage reduction and energy saving method according to claim 3 is characterized in that: When analyzing constant impedance loads, the proportional relationship between the power of this type of load and the square of the voltage drop is verified based on the theoretical basis that the power decreases accordingly when the voltage decreases; when analyzing constant power loads, the linear correlation between the power change and the voltage change of this type of load is determined; When analyzing temperature-controlled loads, determine the relationship between this type of load and the corresponding equipment type and control method based on the change in power when the voltage is reduced.

5. The power grid voltage reduction and energy saving method according to claim 1, characterized in that: In step S3, the user-side load model has a variety of different types of user-side loads; when constructing a load cluster, first determine the access ratio range of each type of user-side load in the substation; then, within the access ratio range, randomly generate the specific access ratio of each type of user-side load to complete the construction of the load cluster model.

6. The power grid voltage reduction and energy saving method according to claim 1, characterized in that: In step S4, the mathematical optimization model includes an optimization objective and a system constraint; the optimization objective is to optimize the substation load power and line power loss of the power grid through the mathematical optimization model; the system constraint is used to ensure the feasibility of the voltage regulation scheme, that is, the voltage regulation scheme does not affect the safe and stable operation of the power grid.

7. The method for reducing voltage and saving energy in a power grid according to claim 6, characterized in that: When optimizing the load power and line power loss of the power grid, the minimum sum of the load power and the line power loss is used as the quantitative indicator of the optimization target; when the mathematical optimization model optimizes the operation state of the power grid by adjusting the voltage, after comprehensively considering the user side load power and line power loss, the determined optimization target Obj is as follows: Obj=min(P load +P loss ) Where P load Represents load power, P loss Represents the line power loss; the specific formula is as follows: In the formula, α+β+γ=1, α, β, and γ represent the corresponding proportions of constant impedance load, constant power load, and temperature control load in the substation respectively; Respectively represent the corresponding load power of constant impedance load, constant power load and temperature control load; N L Represents the number of branches in the power grid, c k represents the conductance of the kth transmission branch connecting the i-th node and the j-th node; V i 、V j Represent the corresponding voltage amplitudes of the i-th node and the j-th node, δ ij Represents the phase angle difference between the i-th node and the j-th node.

8. The method for reducing voltage and saving energy in a power grid according to claim 7, characterized in that: System constraints include equality constraints and inequality constraints; equality constraints are used to ensure the active power balance and reactive power balance of the power grid, thereby ensuring the stable operation of the power grid, as shown in the following formula: Where P Gi represents the active power of the i-th generator, P Di represents the active power of the i-th load node; Q Gi represents the reactive power of the i-th generator, Q Di represents the reactive power of the i-th load node; G ij , B ij Represent the mutual conductance and mutual susceptance between the i-th node and the j-th node respectively; N represents the number of nodes in the power grid except the balancing nodes. i Represents the number of nodes connected to the i-th node, N PQ Represents the total number of load nodes; Inequality constraints are used to ensure that all parameters in the power system operate within a preset safe and reasonable range, and to maintain the stability of the power system during the optimization process of voltage reduction and energy saving, including the following: In the above formulas, V Gi represents the voltage of the i-th generator, N G Represents the number of generators in the power grid; V Li represents the voltage of the ith load node, T i represents the transformation ratio of the i-th transformer, N T Represents the number of transformers in the power grid; Q Ci represents the switching of the i-th reactive power compensation device, N C Represents the number of reactive power compensation devices; S l represents the apparent power of the lth line, N L Indicates the number of lines; superscript (...) min Represents the lower limit of the corresponding parameter, and the superscript (…) max Represents the upper limit value of the corresponding parameter; Represents the sum of load power, P access Represents the maximum load power that the corresponding node in the power grid can bear.

9. The method for reducing voltage and saving energy in a power grid according to claim 1, characterized in that: In step S5, after adopting the swarm intelligence algorithm, the swarm intelligence algorithm is improved according to the nonlinear and non-convex characteristics of the power grid voltage regulation and energy-saving problem; the improvement strategy includes dynamic adjustment of parameters and introduction of weight coefficients; in step S6, the setting of the iteration termination condition is based on the scale of the power grid; the number of iterations in the iteration termination condition increases with the increase of the scale of the power grid.

10. The power grid voltage reduction and energy saving method according to claim 1, characterized in that: After multiple grid voltage regulation schemes are obtained through step S6, the method further includes: S7. During the iterative calculation process, Newton-Raphson power flow calculation is performed on each voltage regulation scheme on the power grid connected to the substation load cluster, and the constraint violation value, substation load power value and line loss value corresponding to each power grid voltage regulation scheme are obtained, and the feasibility and advantages and disadvantages of each power grid voltage regulation scheme are comprehensively evaluated; S8. Delete the grid voltage regulation schemes with non-zero constraint violation values; among the remaining grid voltage regulation schemes, analyze the dynamic relationship between the voltage regulation rate and the load cluster power curve, and select the optimal voltage regulation scheme as a dispatch reference scheme for power decision makers.

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