New energy voltage reactive power management and control method based on novel power system and related equipment

Abstract

The invention belongs to the technical field of power distribution network voltage management and control, and particularly relates to a new energy voltage reactive power management and control method based on a novel power system and related equipment, and the method comprises the steps: building a novel power system source network load storage interaction model based on the interaction relation between each main body in the novel power system after new energy grid connection and a power distribution network; constructing a multi-target multi-constraint optimization control model according to the operation state data, the optimization target and the operation constraint conditions of the power distribution network; solving an optimal solution set of the multi-target multi-constraint optimal control model based on a preset optimal control algorithm, and determining a voltage reactive power regulation and control strategy according to the optimal solution set; and controlling the node access equipment to execute corresponding control actions according to the voltage reactive power regulation and control strategy. According to the invention, a more accurate voltage reactive power regulation and control strategy can be generated, the reactive power control efficiency and precision are improved, reactive power regulation is carried out by balancing multiple parties, voltage reactive power control is carried out on the power distribution network more effectively after distributed new energy is accessed to the power distribution network, and the operation safety of the power distribution network is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of voltage control in distribution networks, and in particular relates to a new energy voltage reactive power control method and related equipment based on a new power system. Background Art

[0002] With the rapid development of distributed renewable energy, the penetration rate of power grids is getting higher and higher. At the same time, the emergence of flexible resources such as adjustable flexible loads, electric vehicles and energy storage will bring huge challenges to the regulation of power grids. The large-scale access of renewable energy to the power grid will inevitably bring strong uncertainty. After the connection to the grid, the ability of the power grid to absorb renewable energy will be tested. At the same time, the access of a large number of flexible resources will inevitably lead to the complication of the operation mode of the power grid. Obviously, the traditional control methods under the deterministic conditions of the power grid and the mixed and unified control of various dispatchable resources are difficult to adapt to the control needs of complex power grids under the new situation.

[0003] In the case of distributed energy access to the power grid, the unpredictable photovoltaic output causes the loss of artificial reactive power control. For example, during the Spring Festival, most enterprises in a certain area stopped production or reduced production, and the demand for active and reactive power decreased significantly. In this regard, in order to prevent reactive power reverse transmission, it is mainly based on the grid and load side equipment, based on the traditional power system structure and operation mode, to strengthen the comprehensive reactive power control, and to optimize reactive power control based on the single target or multi-target weighted solution method. On the one hand, orderly arrange the withdrawal of capacitors at all levels, the input of reactors, and the setting of the inductive output of public transformer SVG. On the other hand, combined with the characteristics of large photovoltaic capacity in a certain area, the operation of the distributed photovoltaic inverter with surplus power is carried out. However, from the control results, due to the good weather during the holiday, the photovoltaic phase advance operation has a large output, resulting in an abnormally low power factor in the dispatch monitoring of a certain area. The main reason is that the one-size-fits-all operation method is still implemented, and there is a lack of intelligent control methods to stabilize the power factor as a whole within a reasonable range.

[0004] It can be seen that the existing technology for voltage and reactive power optimization control does not fully consider the characteristics and influence of multi-party interactions in the new power system, and there is a problem of low reactive power control efficiency; and the weighted solution-based method does not take into account the conflicts and coordination between multiple objectives, resulting in poor multi-party balancing capabilities and difficulty in meeting diverse operating scenarios and conditions. Summary of the invention

[0005] The purpose of the present invention is to address the problem that the prior art does not fully consider the characteristics and influence of multi-party interaction of the new power system for voltage and reactive power optimization control, resulting in low reactive power control efficiency, and the weighted solution method does not consider the conflict and coordination between multiple objectives, and there is a problem of poor multi-party balancing ability. A new energy voltage and reactive power control method and related equipment based on the new power system are proposed. The method constructs a source-grid-load-storage interaction model of the new power system based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, integrates the characteristics and influence of the source-grid-load-storage interaction of the new power system, and the constructed model is more in line with the scene, which is more conducive to improving the voltage and reactive power calculation accuracy, generating a more accurate voltage and reactive power regulation strategy, and finally providing High reactive power control efficiency and accuracy; at the same time, by determining multiple optimization objectives and multiple operating optimization conditions corresponding to reactive power optimization, the conflict and coordination between multiple optimization objectives can be taken into account, and then a more reasonable multi-objective and multi-constraint optimization control model can be constructed, which is more conducive to the reactive power regulation balance of all parties and adapts to diverse operating scenarios and conditions; by making full use of big data, cloud computing and other technologies, the model is solved by the particle swarm optimization algorithm to generate a voltage reactive power control strategy based on the optimal solution set, which not only improves the speed of the reactive power optimization control process, but also can formulate the optimal and most accurate voltage reactive power control strategy, more effectively solve the problem of voltage reactive power control of the distribution network after the distributed new energy is connected to the distribution network, and improve the operation safety of the distribution network.

[0006] In a first aspect, an embodiment of the present invention provides a new energy voltage reactive power control method based on a new power system, comprising the following steps: Based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, a new power system source-grid-load-storage interactive model is constructed, wherein the subject includes node access devices on multiple sides of the source-grid-load-storage; According to the operation status data, optimization objectives and operation constraints of the distribution network, a multi-objective and multi-constraint optimization control model of the new power system source-grid-load-storage interaction model is constructed; Solving the multi-objective multi-constraint optimization control model based on a preset optimization control algorithm to obtain an optimization solution set, and determining a voltage and reactive power control strategy for the source-grid-load-storage interaction model of the novel power system according to the optimization solution set; According to the voltage reactive power regulation strategy, reactive power control instructions are issued to corresponding node access devices in the source-grid-load-storage interaction model of the new power system, and the node access devices are controlled to perform corresponding control actions.

[0007] Furthermore, the node access devices on multiple sides of the source, grid, load and storage include distributed renewable energy, energy storage devices, energy conversion devices, loads and integrated energy systems. The source, grid, load and storage interaction model of the new power system is constructed based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, including: When new energy is connected to the grid, a source-grid-load-storage interaction model of the new power system is constructed based on the interaction relationship between distributed renewable energy, energy storage devices, energy conversion devices, loads, integrated energy systems and distribution networks in the new power system, wherein the interaction relationship includes the physical connection relationship and information interaction relationship between each subject and the distribution network.

[0008] Furthermore, the multi-objective and multi-constraint optimization control model includes an upper-level multi-objective and multi-constraint optimization control model and a lower-level multi-objective and multi-constraint optimization control model corresponding to the distribution network. The multi-objective and multi-constraint optimization control model for constructing a new power system source-grid-load-storage interaction model based on the operating status data, optimization objectives and operating constraints of the distribution network includes: obtaining the operating status data of each subject in the distribution network after connecting to new energy, determining the operating constraints based on the operating status data, taking minimizing the line loss of the distribution network, maximizing the system reliability and minimizing the environmental impact as the optimization objectives, taking the transformer tap adjustment and the capacitor group in the distribution network as the decision variables, and constructing an upper-level multi-objective and multi-constraint optimization control model of the new power system source-grid-load-storage interaction model.

[0009] Furthermore, the multi-objective and multi-constraint optimization control model corresponding to the novel power system source-grid-load-storage interaction model is constructed according to the operation status data, optimization objectives and operation constraints of the distribution network, and further includes: The operating status data of each entity in the distribution network after connecting to the new energy is obtained, and the operating constraints are determined according to the operating status data. The minimum power factor and the minimum voltage offset are taken as optimization objectives, and the reactive output of the user capacitor group and the photovoltaic inverter in the distribution network are taken as decision variables to construct the lower-level multi-objective and multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system.

[0010] Furthermore, the multi-objective multi-constraint optimization control model is solved based on a preset optimization control algorithm to obtain an optimization solution set, and a voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the optimization solution set, including: Solving the upper-layer multi-objective multi-constraint optimization control model by a particle swarm optimization algorithm based on uniform network theory to obtain a first optimization solution set; The upper-layer voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the first optimization solution set.

[0011] Further, the multi-objective multi-constraint optimization control model is solved based on a preset optimization control algorithm, and the voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the solution result, and it also includes: solving the lower-layer multi-objective multi-constraint optimization control model by the particle swarm optimization algorithm to obtain a second optimization solution set; The lower layer voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the second optimization solution set.

[0012] Further, the reactive power control instruction is sent to the corresponding node access device in the source-grid-load-storage interaction model of the new power system according to the voltage reactive power control strategy, and the node access device is controlled to perform corresponding control actions, including: determining the voltage reactive power control amount of the upper node access device and the upper node access device according to the upper voltage reactive power control strategy, and determining the voltage reactive power control amount of the lower node access device and the lower node access device according to the lower voltage reactive power control strategy, wherein the upper node access device and the lower node access device include voltage regulating equipment, reactive power compensation equipment and distributed energy; Generate an upper-layer reactive power control instruction based on the voltage reactive power regulation amount of the upper-layer node access device, and generate a lower-layer reactive power control instruction based on the voltage reactive power regulation amount of the lower-layer node access device; The upper layer reactive power control instruction is sent to the upper layer node access device to control the upper layer node access device to execute the upper layer reactive power control instruction, and the lower layer reactive power control instruction is sent to the lower layer node access device to control the lower layer node access device to execute the lower layer reactive power control instruction.

[0013] In a second aspect, an embodiment of the present invention further provides a new energy voltage reactive power control device based on a new power system, the device comprising: The first building module builds a source-grid-load-storage interaction model of a new power system based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid. The subject includes node access devices on multiple sides of the source-grid-load-storage. The second construction module is used to construct a multi-objective and multi-constraint optimization control model of a new power system source-grid-load-storage interaction model based on the operating status data of the distribution network, the optimization objectives and the operating constraints; A calculation module is used to solve the multi-objective and multi-constraint optimization control model based on a preset optimization control algorithm to obtain an optimization solution set, and determine the voltage and reactive power regulation strategy of the source-grid-load-storage interaction model of the new power system according to the optimization solution set; a control module is used to issue reactive power control instructions to corresponding node access devices in the source-grid-load-storage interaction model of the new power system according to the voltage and reactive power regulation strategy, and control the node access devices to perform corresponding control actions.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the new energy voltage reactive power control method based on the new power system as described in the first aspect are implemented.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the new energy voltage reactive power control method based on the new power system as described in the first aspect are implemented.

[0016] The beneficial effects achieved by the present invention are as follows: the method constructs a source-grid-load-storage interaction model of a new power system based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, integrates the characteristics and influences of the source-grid-load-storage interaction of the new power system, and the constructed model is more in line with the scene, which is more conducive to improving the voltage reactive power calculation accuracy, generating a more accurate voltage reactive power regulation strategy, and ultimately improving the reactive power control efficiency and accuracy; at the same time, by determining multiple optimization targets and multiple operation optimization conditions corresponding to reactive power optimization, it is possible to take into account the conflict and coordination between multiple optimization targets, and then construct a more reasonable multi-target multi-constraint optimization control model, which is more conducive to the reactive power regulation balance of all parties and adapts to diverse operation scenarios and conditions; by making full use of technologies such as big data and cloud computing, the model is solved by a particle swarm optimization algorithm to generate a voltage reactive power regulation strategy according to the optimal solution set, which not only improves the speed of the reactive power optimization control process, but also can formulate the optimal and most accurate voltage reactive power regulation strategy, more effectively solves the problem of voltage reactive power control of the distribution network after the distributed new energy is connected to the distribution network, and improves the operation safety of the distribution network.

[0017] The above invention content is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0019] Figure 1 It is a flow chart of a new energy voltage reactive power control method based on a new power system provided by an embodiment of the present invention.

[0020] Figure 2 It is a structural schematic diagram of a new energy voltage reactive power control device based on a new power system provided by an embodiment of the present invention.

[0021] Figure 3 A schematic diagram of the structure of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0024] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. It should also be understood that in various embodiments of the present invention, the size of the sequence number of each process does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0025] It should be understood that, in the present invention, "multiple" refers to two or more than two. "And / or" is merely a variable relationship that describes associated objects, indicating that three relationships may exist. "Including A, B and C" means that A, B and C are all included, "Including A, B or C" means that one of A, B and C is included, and "Including A, B and / or C" means that any one or any two or three of A, B and C are included. In the present invention, "B corresponding to A", "B corresponding to A", "A corresponds to B" or "B corresponds to A" means that B is associated with A, and B can be determined based on A. Determining B based on A does not mean that B is determined only based on A, but B can also be determined based on A and / or other information.

[0026] Embodiment 1 Please refer to Figure 1 , Figure 11 is a flow chart of a new energy voltage reactive power control method based on a new power system provided by an embodiment of the present invention. The new energy voltage reactive power control method based on a new power system specifically includes the following steps: S1. Based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, a source-grid-load-storage interactive model of the new power system is constructed, wherein the subject includes node access devices on multiple sides of the source-grid-load-storage.

[0027] In the present invention, the new energy voltage reactive power control method based on the new power system is applicable to the application scenario of distributed new energy access to the distribution network. The distribution network is at the end of the power system, with a long transmission distance and multiple voltage reduction levels. The operating state is greatly affected by the operating mode and load changes. These conditions cause the distribution network to be in a non-economic operating state in a certain area and time period, and it is necessary to coordinate and control indicators such as voltage and reactive power. By controlling the voltage reactive power of the distribution network connected to the distributed new energy, the voltage loss in the distribution network line is reduced. The electronic device running the new energy voltage reactive power control method based on the new power system can be an automated distribution master station. Among them, the electronic device can communicate with other electronic devices through wireless connection / wired connection. It should be pointed out that the above-mentioned wireless connection method includes but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB connection, and other wireless connection methods currently known or to be developed in the future.

[0028] Among them, new energy includes but is not limited to distributed access to solar energy, geothermal energy, wind energy, ocean energy, biomass energy and nuclear fusion energy, etc., and multiple power sources of the same or different types can be distributedly accessed in a distribution network. The above-mentioned new power system source-grid-load-storage interaction model is constructed by combining the power supply side, microgrid measurement, load side and energy storage measurement of the distribution network. The interaction mode between source-grid-load-storage includes source-source complementarity, source-grid coordination, source-storage interaction, grid-storage interaction, load-storage interaction, grid-load interaction, source-load interaction, etc. Among them, the node access equipment on each side of the source-grid-load-storage includes distributed renewable energy, energy storage devices, energy conversion devices, loads, integrated energy systems, etc. Loads can include asynchronous motors, synchronous motors, rectifiers, electrolysis devices, refrigeration and heating equipment, and power loads on the user side in the distribution network.

[0029] Specifically, after the new energy is connected to the grid, the source-grid-load-storage interaction model of the new power system is constructed according to the physical connection relationship and information interaction relationship between the distributed renewable energy, energy storage device, energy conversion device, load, integrated energy system and distribution network in the new power system. Among them, the physical connection relationship can refer to the connection between each subject and the distribution network based on physical characteristics, such as each subject is connected to the distribution network through wires / waves. The information interaction relationship can refer to the relationship between the influence and response characteristics of each subject on the voltage and reactive power of the distribution network after each subject is connected to the distribution network. For example, for photovoltaic power sources, the output characteristics of photovoltaic power sources and the relationship between photovoltaic output and the voltage and reactive power of the distribution network are analyzed according to the equipment performance parameters of the connected photovoltaic power sources and the state of the distribution network. By constructing a new power system source-grid-load-storage interaction model, and then analyzing it in combination with specific data, the voltage and reactive power of the distribution network are determined, and based on the interaction relationship between each subject and the distribution network, the subjects in each layer of the source-grid-load-storage are controlled to perform reactive adjustment according to the voltage and reactive power of the distribution network, so that the voltage and reactive power regulation of the distribution network remains balanced.

[0030] S2. Construct a multi-objective and multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system based on the operating status data, optimization objectives and operating constraints of the distribution network.

[0031] Among them, the operating status data of the distribution network after connecting to new energy can be collected in real time / periodic time, and a multi-objective and multi-constraint optimization control model corresponding to the source-grid-load-storage interaction model of the new power system can be constructed in combination with the optimization objectives and the operating constraints of the distribution network. Among them, the multi-objective and multi-constraint optimization control model refers to an optimization control model constructed under multiple optimization objectives and multiple constraints to solve the voltage and reactive power optimization control problem of the distribution network. The above-mentioned multiple optimization objectives may include but are not limited to minimizing losses, maximizing reliability, minimizing environmental impact, etc.; the above-mentioned multiple operating constraints include but are not limited to equipment capacity, voltage range, reactive power balance, etc.

[0032] Specifically, step S2 includes: The operating status data of each entity in the distribution network after the access to new energy is obtained, and the operating constraints are determined according to the operating status data. The optimization objectives are to minimize the line loss of the distribution network, maximize the system reliability and minimize the environmental impact. The transformer tap adjustment and capacitor bank in the distribution network are taken as decision variables to construct an upper-level multi-objective and multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system.

[0033] In the present application, the multi-objective multi-constraint optimization control model may include an upper-layer multi-objective multi-constraint optimization control model and a lower-layer multi-objective multi-constraint optimization control model corresponding to the distribution network, wherein the upper-layer multi-objective multi-constraint optimization control model is used to perform voltage and reactive power regulation on each node access device of the upper layer; the lower-layer multi-objective multi-constraint optimization control model is used to perform voltage and reactive power regulation on each node access device of the lower layer. The distribution network is divided into multiple levels. In the present embodiment, the distribution network includes an upper layer and a lower layer, and the upper layer and the lower layer respectively include various node access devices, for example: the upper layer is the main station distribution room of area A, and the lower layer is the distribution cabinet of each community in area A. The main station distribution room centrally controls the distribution cabinet of each community, including controlling the node voltage amplitude of the distribution cabinet of each community, and the distribution cabinet of each community feeds back data including user capacitors, photovoltaic reactive output, etc. to the main station distribution room.

[0034] More specifically, in this embodiment, the operation constraint conditions are determined based on the collected operation status data of the upper layer of the distribution network. Considering that the capacity of each device must meet the load demand and must not exceed the rated capacity of the device, and the voltage must be within a certain range to meet the user's needs and must not exceed the rated voltage range of the device, and at the same time, the reactive power must be kept within a reasonable range to achieve reactive balance, therefore, the equipment capacity, voltage range and reactive balance can be constrained by operation constraints, and the minimum line loss of the distribution network, the maximum system reliability and the minimum environmental impact are used as multiple optimization objectives, and the transformer tap adjustment and capacitor bank in the distribution network are used as decision variables. According to the multiple operation constraints, multiple optimization objectives and decision variables of the upper layer of the distribution network, the upper layer multi-objective multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system is constructed.

[0035] If there are n transformer taps, the transformer tap is expressed as a decision variable x = (x1, x2, ..., x n ), there are m capacitor banks, and the capacitor bank is represented as a decision variable y = (y1, y2, ..., y m ), then the upper-level multi-objective multi-constraint optimization control model is as follows: Objective function vector: F(x,y)=[P min(loss) (x,y),R max(t) (x,y),γ min (x,y)] (1) in: P min(loss) (x,y)=I 2 ×R; γ min (x,y)=w1×η+w2×β-w3×G; Where F(x,y) is the objective function vector, P min(loss) (x, y) is the minimum line loss, I is the current passing through the line, R is the resistance on the line; R max(t) (x, y) is the maximum reliability of the system (maximum system reliability), which means the probability that (x, y) operates normally within time t, λ is the failure rate of (x, y) (in 1 / hour or 1 / year); γ min (x, y) is the minimum environmental impact, which refers to the degree of impact of (x, y) on the environment. w1, w2 and w3 are the weights of the corresponding indicators, η represents the energy efficiency of (x, y), β represents the proportion of clean energy in (x, y), and G represents the carbon emissions of new energy in (x, y). The weight can be determined based on environmental policies, the use of environmental impact models, and other aspects.

[0036] Among them, each operation constraint condition is shown in the following formula (2): Among them, W i 、V i , P i are the equipment capacity, voltage and reactive power of equipment i, W mini 、V mini , P mini are the equipment capacity, voltage range and minimum reactive power of equipment i in the upper layer of the distribution network, respectively, W maxi 、V maxi , P maxi The equipment capacity, voltage range and maximum reactive power of equipment i in the upper layer of the distribution network are respectively.

[0037] More specifically, step S2 further includes: The operating status data of each entity in the distribution network after connecting to the new energy is obtained, and the operating constraints are determined according to the operating status data. The minimum power factor and the minimum voltage offset are taken as optimization objectives, and the reactive output of the user capacitor group and the photovoltaic inverter in the distribution network are taken as decision variables to construct the lower-level multi-objective and multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system.

[0038] Similarly, for the access node equipment in the lower layer of the distribution network, the corresponding operating constraints can be determined according to the operating status data of each subject in the lower layer of the distribution network after access to new energy. The operating constraints of the lower layer can also include equipment capacity, voltage range, reactive power balance, etc. And for the lower layer of the distribution network, in this embodiment, the minimum power factor and the minimum voltage offset are used as multiple optimization objectives, and the reactive output of the user capacitor group and the photovoltaic inverter in the distribution network are used as decision variables. Based on the multi-optimization determined by the lower layer of the distribution network, a lower-layer multi-objective multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system is constructed. The construction of the lower-layer multi-objective multi-constraint optimization control model can refer to the upper-layer multi-objective multi-constraint optimization control model for construction, which will not be repeated here.

[0039] In this embodiment, the characteristics and impacts of the interaction between the source, grid, load and storage of the new power system are fully considered, and the conflicts and coordination between multiple optimization objectives, multiple constraints and multiple optimization objectives are fully considered. A more reasonable multi-objective and multi-constraint optimization control model can be established to improve the efficiency and accuracy of reactive power control, balance the interests and needs of all parties, and adapt to diverse operating scenarios and conditions.

[0040] S3. Solve the multi-objective and multi-constraint optimization control model based on a preset optimization control algorithm to obtain an optimization solution set, and determine the voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system according to the optimization solution set.

[0041] Among them, after constructing a multi-objective multi-constraint optimization control model, the model can be solved through a preset optimization control algorithm to obtain an optimization solution set. According to the optimization solution set, a voltage and reactive power control strategy for the source-grid-load-storage interaction model of a new power system is formulated, wherein, for the upper and lower layers of the distribution network, the voltage and reactive power control strategy includes an upper-layer voltage and reactive power control strategy and a lower-layer voltage and reactive power control strategy. The above-mentioned preset optimization algorithms include but are not limited to particle swarm optimization algorithms, genetic algorithms, simulated annealing algorithms, ant colony algorithms, etc. In this embodiment, the particle swarm optimization algorithm is used for illustration.

[0042] Specifically, the above step S3 includes: S31, solving the upper-layer multi-objective multi-constraint optimization control model by a particle swarm optimization algorithm based on uniform network theory to obtain a first optimization solution set; S32. Determine the upper-layer voltage and reactive power control strategy of the source-grid-load-storage interaction model of the novel power system according to the first optimization solution set.

[0043] Among them, the particle swarm optimization algorithm has the advantages of fast convergence speed, few parameters, and simple and easy-to-implement algorithm. In view of the situation where there are many parameters involved in the source-grid-load-storage interaction model of the new power system in this application, the use of the particle swarm optimization algorithm can converge to the optimal solution faster. The above-mentioned homogenized network theory refers to a theoretical framework for describing and analyzing complex network structures. In the homogenized network theory, the nodes and edges in the network are regarded as individuals uniformly distributed in the network space, rather than nodes and connections at specific positions. Based on the homogenized network theory, the behavior and properties of complex networks can be studied through simplified mathematical models. Therefore, in this application, the homogenized network theory can be considered to solve the optimal solution in the process of solving the problem through the particle swarm optimization algorithm.

[0044] Specifically, the upper-level multi-objective and multi-constraint optimization control model is solved. For the particle swarm algorithm, the speed and position of each particle are first initialized, the fitness value of each particle is calculated, and then the individual optimal value of each particle and the global optimal value of the group are calculated. Then, the speed and position of the particle are updated according to the individual optimal value and the global optimal value until the operation constraints are met and the result is output as the first optimized subset.

[0045] In some embodiments, if the upper layer of the distribution network system includes node 1 with a transformer tap, node 2 is equipped with two groups of switchable parallel capacitors, and node 3 is equipped with four groups of switchable parallel capacitors, each with a capacity of 100kvar. Node 2 is connected to three 1000kW wind turbines with a total installed capacity of 2MW and a rated voltage of 650V. The equipment voltage amplitude is limited to Umin=1.85 and Umax=1.05. In the particle swarm optimization algorithm, the number of particles n=20 is selected, the inertia weight coefficient ω=0.8 decreases algebraically linearly between [0.4, 0.9], the acceleration coefficient c1=c2=2.0, the maximum number of iterations n is 50, the maximum particle velocity is Vmax=2, and the minimum is Vmin=-2. The first optimized subset is calculated based on the above known data. After calculating the first optimized subset, an upper-layer voltage reactive power control strategy is generated according to the first optimized subset. Based on the upper-layer voltage reactive power control strategy, the distribution network automation system issues and controls the voltage regulating equipment, reactive power compensation equipment, distributed energy, etc. in the distribution network in real time or offline, thereby realizing the distribution network voltage reactive power optimization operation.

[0046] Specifically, the above step S3 also includes: S33, solving the lower-layer multi-objective multi-constraint optimization control model by using the particle swarm optimization algorithm to obtain a second optimization solution set; S34. Determine the lower-layer voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system according to the second optimization solution set.

[0047] Specifically, for the lower-level multi-objective and multi-constraint optimization control model, the second optimization solution set can be solved by the particle swarm optimization algorithm in the same way, and the lower-level voltage reactive power control strategy of the source-grid-load-storage interaction model of the new power system can be determined based on the second optimization solution set. According to the lower-level voltage reactive power control strategy, the corresponding equipment in the distribution network is decentralized and adaptively adjusted. For example, when the connected new energy is photovoltaic, when the light intensity is low and the photovoltaic output active power is low, the photovoltaic sends reactive power to the distribution network system to support the node voltage of the distribution network system; when the light intensity is high, the photovoltaic output active power increases, and the distribution network system outputs reactive power to the photovoltaic to reduce the node voltage of the distribution network system.

[0048] In this embodiment, after calculating the first optimization subset and the second optimization subset, an upper-layer voltage reactive control strategy is generated according to the first optimization subset, and a lower-layer voltage reactive control strategy is generated according to the second optimization subset. The voltage reactive control is performed on the node access equipment at the upper layer of the distribution network system based on the upper-layer voltage reactive control strategy, and the voltage reactive control is performed on the node access equipment at the lower layer based on the lower-layer voltage reactive control strategy. That is, the distribution network automation system is used to issue and control real-time or offline instructions to the voltage regulating equipment, reactive compensation equipment, distributed energy, etc. in the distribution network, thereby realizing the voltage reactive optimization operation of the distribution network.

[0049] The above-mentioned voltage and reactive power control is carried out on the equipment at different levels by formulating a hierarchical control strategy, and the control accuracy is higher. Taking into full account the characteristics and influence of the interaction between the source, grid, load and storage of the new power system, and taking into full account the conflicts and coordination between multiple optimization objectives, multiple constraints and multiple optimization objectives, a more reasonable multi-objective and multi-constraint optimization control model can be established, which can improve the efficiency and accuracy of reactive power control, balance the interests and needs of all parties, and adapt to various operating scenarios and conditions; in addition, by making full use of big data, cloud computing and other technologies, the model is solved by the particle swarm optimization algorithm to generate a voltage and reactive power control strategy according to the optimal solution set, which not only improves the speed of the reactive power optimization control process, but also can formulate the optimal and most accurate voltage and reactive power control strategy, more effectively solve the problem of voltage and reactive power control of the distribution network after the distributed new energy is connected to the distribution network, and improve the safety of distribution network operation.

[0050] S4. According to the voltage reactive power regulation strategy, reactive power control instructions are issued to corresponding node access devices in the source-grid-load-storage interaction model of the new power system, and the node access devices are controlled to perform corresponding control actions.

[0051] Specifically, after generating the voltage reactive power control strategy, a reactive power control instruction corresponding to the voltage reactive power control strategy can be generated, and the reactive power control instruction is sent to the corresponding node access device in the source-grid-load-storage interaction model of the new power system. After receiving the reactive power control instruction, the node access device performs corresponding actions according to the reactive power control instruction, for example: controlling the voltage regulating equipment and the reactive power compensation equipment to send reactive power to the distribution network system to support the node voltage of the distribution network system, or controlling the voltage regulating equipment and the reactive power compensation equipment to receive reactive power from the distribution network system to support the reactive power output of the distribution network system to reduce the node voltage of the distribution network system.

[0052] Specifically, the above step S4 includes: S41, determining the voltage reactive power control amount of the upper node access device and the upper node access device according to the upper layer voltage reactive power control strategy, and determining the voltage reactive power control amount of the lower node access device and the lower node access device according to the lower layer voltage reactive power control strategy, wherein the upper node access device and the lower node access device include voltage regulating equipment, reactive power compensation equipment and distributed energy; S42, generating an upper-layer reactive power control instruction based on the voltage reactive power control amount of the upper-layer node access device, and generating a lower-layer reactive power control instruction based on the voltage reactive power control amount of the lower-layer node access device; S43, sending the upper-layer reactive power control instruction to the upper-layer node access device, controlling the upper-layer node access device to execute the upper-layer reactive power control instruction, and sending the lower-layer reactive power control instruction to the lower-layer node access device, controlling the lower-layer node access device to execute the lower-layer reactive power control instruction.

[0053] Among them, for strategy control, when generating the upper-layer voltage reactive control strategy and the lower-layer voltage reactive control strategy, the control strategy includes a specific control subject and the voltage reactive control amount of the control subject, that is, it includes the access node equipment that needs to be regulated and the voltage reactive control amount of the access node equipment that needs to be regulated. The access node equipment that needs to be regulated includes the upper-layer access node equipment and the lower-layer access node equipment. In this regard, for the upper layer of the distribution network, an upper-layer reactive control instruction can be generated and sent to the corresponding upper-layer node access equipment to perform reactive control actions; and for the lower layer of the distribution network, a lower-layer reactive control instruction can be generated and sent to the corresponding lower-layer node access equipment to perform reactive control actions, and finally realize the overall voltage reactive regulation of the distribution network connected to the distributed new energy, ensuring that the lines on the distribution network are in voltage reactive balance.

[0054] In an embodiment of the present invention, based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, the characteristics and influence of the source-grid-load-storage interaction of the new power system are considered, and a more practical new power system source-grid-load-storage interaction model is constructed, which is more conducive to accurate reactive power calculation and strategy generation, and ultimately improves reactive power control efficiency and accuracy; by determining multiple optimization targets corresponding to reactive power optimization, fully considering the conflicts and coordination between multiple optimization targets, establishing multiple operation optimization conditions, and constructing a more reasonable multi-objective and multi-constraint optimization control model, it is possible to balance the interests and needs of all parties and adapt to diverse operation scenarios and conditions; by making full use of big data, cloud computing and other technologies, the model is solved by a particle swarm optimization algorithm to generate a voltage reactive power control strategy according to the optimal solution set, which not only improves the speed of the reactive power optimization control process, but also can formulate the optimal and most accurate voltage reactive power control strategy, more effectively solve the problem of voltage reactive power control of the distribution network after the distributed new energy is connected to the distribution network, and improve the operation safety of the distribution network.

[0055] Embodiment 2 refer to Figure 2 As shown, Figure 2 The present invention provides a schematic diagram of a new energy voltage reactive power control device based on a new power system, wherein the device M20 includes: The first construction module M201 constructs a source-grid-load-storage interaction model of a new power system based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid. The subject includes node access devices on multiple sides of the source-grid-load-storage. The second construction module M202 is used to construct a multi-objective and multi-constraint optimization control model of a new power system source-grid-load-storage interaction model according to the operation status data, optimization objectives and operation constraints of the distribution network; The calculation module M203 is used to solve the multi-objective multi-constraint optimization control model based on a preset optimization control algorithm to obtain an optimization solution set, and determine the voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system according to the optimization solution set; The control module M204 is used to issue reactive power control instructions to corresponding node access devices in the source-grid-load-storage interaction model of the new power system according to the voltage reactive power regulation strategy, and control the node access devices to perform corresponding control actions.

[0056] The new energy voltage reactive power control device based on the new power system provided by the embodiment of the present invention can implement each process in the new energy voltage reactive power control method based on the new power system, and can achieve the same beneficial effects. To avoid repetition, it will not be described here.

[0057] The embodiment of the present invention also provides a computer device, please refer to Figure 3 , Figure 3: is a structural diagram of a computer device provided in an embodiment of the present invention, and the computer device D30 includes: a processor D301, a memory D302, and a computer program stored in the memory D302 and executable on the processor D301. The processor D301 calls the computer program stored in the memory D302 to execute each step of the voltage reactive power control method for new energy based on a new power system provided in an embodiment of the present invention, and can achieve the same technical effect, refer to the description in the above embodiment, and will not be repeated here.

[0058] It should be pointed out that those skilled in the art can understand that the electronic device in the embodiment of the present invention is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), digital signal processors (DSP), embedded devices, etc. The electronic device can be a computing device such as a desktop computer, a notebook, a handheld computer, and a cloud server. The electronic device can perform human-computer interaction through a keyboard, a mouse, a remote control, a touchpad, or a voice-controlled device.

[0059] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes and steps in the new energy voltage reactive power control method based on the new power system provided in the embodiment of the present invention are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0060] It should be noted that the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory may be an internal storage unit of an electronic device, such as a hard disk or memory of the electronic device. In other embodiments, the memory may also be an external storage device of an electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Of course, the memory may also include both the internal storage unit of the electronic device and its external storage device. In this embodiment, the memory is generally used to store operating devices and various application software installed in the electronic device, such as program codes of a new energy voltage reactive power control method based on a new power system, etc. In addition, the memory may also be used to temporarily store various types of data that have been output or are to be output.

[0061] A person of ordinary skill in the art can understand that the implementation of all or part of the processes in the above-mentioned embodiment of the method for voltage and reactive power control of renewable energy based on a new power system can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it may include the processes of the various embodiments of the above-mentioned method for voltage and reactive power control of renewable energy based on a new power system.

[0062] The specific implementation method described above is a preferred implementation method of the new energy voltage reactive power control method based on the new power system of the present invention, and it is not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation method. All equivalent changes made in accordance with the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A new energy voltage reactive power control method based on a new power system, characterized in that: The following steps are involved: Based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, a new power system source-grid-load-storage interactive model is constructed, wherein the subject includes node access devices on multiple sides of the source-grid-load-storage; According to the operation status data, optimization objectives and operation constraints of the distribution network, a multi-objective and multi-constraint optimization control model of the new power system source-grid-load-storage interaction model is constructed; Solving the multi-objective multi-constraint optimization control model based on a preset optimization control algorithm to obtain an optimization solution set, and determining a voltage and reactive power control strategy for the source-grid-load-storage interaction model of the novel power system according to the optimization solution set; According to the voltage reactive power regulation strategy, reactive power control instructions are issued to corresponding node access devices in the source-grid-load-storage interaction model of the new power system, and the node access devices are controlled to perform corresponding control actions.

2. The new energy voltage reactive power control method based on the new power system according to claim 1 is characterized in that: The node access equipment on multiple sides of the source, grid, load and storage includes distributed renewable energy, energy storage devices, energy conversion devices, loads, and integrated energy systems. The source, grid, load and storage interaction model of the new power system is constructed based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid, including: When new energy is connected to the grid, a source-grid-load-storage interaction model of the new power system is constructed based on the interaction relationship between distributed renewable energy, energy storage devices, energy conversion devices, loads, integrated energy systems and distribution networks in the new power system, wherein the interaction relationship includes the physical connection relationship and information interaction relationship between each subject and the distribution network.

3. The new energy voltage reactive power control method based on the new power system according to claim 1 is characterized in that: The multi-objective multi-constraint optimization control model includes an upper-layer multi-objective multi-constraint optimization control model and a lower-layer multi-objective multi-constraint optimization control model corresponding to the distribution network. The multi-objective multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system is constructed according to the operating status data, optimization objectives and operating constraints of the distribution network, including: The operating status data of each entity in the distribution network after the access to new energy is obtained, and the operating constraints are determined according to the operating status data. The optimization objectives are to minimize the line loss of the distribution network, maximize the system reliability and minimize the environmental impact. The transformer tap adjustment and capacitor bank in the distribution network are taken as decision variables to construct an upper-level multi-objective and multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system.

4. The new energy voltage reactive power control method based on the new power system according to claim 3 is characterized in that: The multi-objective and multi-constraint optimization control model corresponding to the source-grid-load-storage interaction model of the novel power system is constructed according to the operation status data of the distribution network, the optimization target and the operation constraint conditions, and further includes: The operating status data of each entity in the distribution network after connecting to the new energy is obtained, and the operating constraints are determined according to the operating status data. The minimum power factor and the minimum voltage offset are taken as optimization objectives, and the reactive output of the user capacitor group and the photovoltaic inverter in the distribution network are taken as decision variables to construct the lower-level multi-objective and multi-constraint optimization control model of the source-grid-load-storage interaction model of the new power system.

5. The new energy voltage reactive power control method based on the new power system according to claim 3 is characterized in that: The multi-objective multi-constraint optimization control model is solved based on a preset optimization control algorithm to obtain an optimization solution set, and a voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the optimization solution set, including: Solving the upper-layer multi-objective multi-constraint optimization control model by a particle swarm optimization algorithm based on uniform network theory to obtain a first optimization solution set; The upper-layer voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the first optimization solution set.

6. The new energy voltage reactive power control method based on the new power system according to claim 5 is characterized in that: The method further includes solving the multi-objective multi-constraint optimization control model based on a preset optimization control algorithm, and determining the voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system according to the solution result. Solving the lower-layer multi-objective multi-constraint optimization control model by using the particle swarm optimization algorithm to obtain a second optimization solution set; The lower layer voltage and reactive power control strategy of the source-grid-load-storage interaction model of the new power system is determined according to the second optimization solution set.

7. The new energy voltage reactive power control method based on the new power system according to claim 6 is characterized in that: The step of sending reactive power control instructions to corresponding node access devices in the source-grid-load-storage interaction model of the novel power system according to the voltage-reactive power control strategy, and controlling the node access devices to perform corresponding control actions, includes: Determine the voltage reactive power control amount of the upper node access device and the upper node access device according to the upper layer voltage reactive power control strategy, and determine the voltage reactive power control amount of the lower node access device and the lower node access device according to the lower layer voltage reactive power control strategy, wherein the upper node access device and the lower node access device include voltage regulating equipment, reactive power compensation equipment and distributed energy; Generate an upper-layer reactive power control instruction based on the voltage reactive power regulation amount of the upper-layer node access device, and generate a lower-layer reactive power control instruction based on the voltage reactive power regulation amount of the lower-layer node access device; The upper layer reactive power control instruction is sent to the upper layer node access device to control the upper layer node access device to execute the upper layer reactive power control instruction, and the lower layer reactive power control instruction is sent to the lower layer node access device to control the lower layer node access device to execute the lower layer reactive power control instruction.

8. A new energy voltage reactive power control device based on a new power system, characterized in that: The device comprises: The first building module builds a source-grid-load-storage interaction model of a new power system based on the interactive relationship between each subject and the distribution network in the new power system after the new energy is connected to the grid. The subject includes node access devices on multiple sides of the source-grid-load-storage. The second construction module is used to construct a multi-objective and multi-constraint optimization control model of a new power system source-grid-load-storage interaction model based on the operating status data of the distribution network, the optimization objectives and the operating constraints; A calculation module, used for solving the multi-objective multi-constraint optimization control model based on a preset optimization control algorithm to obtain an optimization solution set, and determining a voltage and reactive power control strategy of the source-grid-load-storage interaction model of the novel power system according to the optimization solution set; The control module is used to send reactive power control instructions to the corresponding node access devices in the source-grid-load-storage interaction model of the new power system according to the voltage-reactive power regulation strategy, and control the node access devices to perform corresponding control actions.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the new energy voltage reactive power control method based on a new power system are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the new energy voltage reactive power control method based on a new power system as described in any one of claims 1 to 7 are implemented.

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