Distributed energy coordinated operation method and system based on virtual power plant

Abstract

The present invention relates to the field of energy distribution coordination, and discloses a method and system for coordinated operation of distributed energy based on a virtual power plant, including the following steps: integrating and processing all distributed energy resources to obtain an energy network that can be uniformly scheduled, and building a virtual power plant in combination with a communication system; calculating the response speed of different devices in the energy network that can be uniformly scheduled to control instructions in the virtual power plant, thereby building a multi-objective scheduling decision model to generate different coordinated operation scheduling strategies for distributed energy, and finally screening the optimal solution for different coordinated operation scheduling strategies for distributed energy. The present invention can coordinate and analyze distributed energy resources in the form of a virtual power plant, generate the most appropriate distributed energy coordinated scheduling operation strategy output, and promote the rational use of distributed energy resources.

Description

Technical Field

[0001] The present invention relates to the field of energy distribution coordination, and in particular to a distributed energy coordinated operation method and system based on a virtual power plant. Background Art

[0002] A virtual power plant is a power coordination management system that uses advanced information and communication technologies and software systems to achieve the aggregation and coordinated optimization of distributed energy resources such as distributed generation, energy storage systems, controllable loads, electric vehicles, etc., so as to participate in the power market and power grid operation as a special power plant. Distributed energy resources are different small power generation units, such as solar power generation units, wind power generation units, energy storage systems, adjustable loads, etc. Since the installation locations of distributed energy resources may be scattered within a range, and the energy that a single distributed energy resource can provide to the power grid when working may be insufficient, it is necessary to coordinate the operation of multiple distributed energy resources and gather the energy of all distributed energy resources to provide power to users efficiently and with high quality. The coordinated operation of distributed energy through virtual power plants can take into account multiple goals such as economy, reliability, and low emissions to maximize the utilization of resources. At the same time, the coordinated management of virtual power plants can help users to intuitively see information such as the consumed or produced electricity and the corresponding costs. This helps to enhance users' awareness of energy conservation and promote the rational use of energy. Summary of the invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a distributed energy coordinated operation method and system based on a virtual power plant.

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

[0005] A first aspect of the present invention provides a distributed energy coordinated operation method based on a virtual power plant, comprising the following steps:

[0006] S102: Integrate all distributed energy resources to obtain a preliminary integrated dispatching energy network, and perform preliminary dispatching feasibility analysis and optimization on the preliminary integrated dispatching energy network to obtain an integrated dispatching energy network;

[0007] S104: integrating a communication system in the integrated dispatching energy network to construct a virtual power plant, and predicting the response speed of different energy network devices to control instructions under target operating environment parameters based on the virtual power plant, and finally ranking the response speeds of different energy network devices according to the response speeds;

[0008] S106: Construct a multi-objective scheduling decision model, generate different distributed energy coordinated operation scheduling strategies in the multi-objective scheduling decision model, and screen the optimal solutions for different distributed energy coordinated operation scheduling strategies.

[0009] Furthermore, in a preferred embodiment of the present invention, the step S102 is specifically:

[0010] Determine the integration scope of distributed energy resources, mark it as the target resource integration scope, and obtain all distributed energy resources within the target resource integration scope;

[0011] Acquire power grid system equipment within the target resource integration scope, wherein the power grid system equipment includes substations, transmission lines and energy storage equipment;

[0012] Acquire energy resource conversion equipment and a big data network, retrieve a solution for integrating power grid system equipment, energy resource conversion equipment, and all distributed energy resources in the big data network, and mark it as a type of integration solution;

[0013] Among them, the first type of integration solution is to connect all distributed energy resources through transmission lines, and connect energy resource conversion equipment to each distributed energy resource, so that the energy output from the distributed energy resources is converted into electrical energy, and the electrical energy is stored in the energy storage equipment. The energy storage equipment imports the stored electrical energy into the substation for substation processing, and outputs the electrical energy for users to use;

[0014] Output a type of integration plan among power grid system equipment, energy resource conversion equipment and all distributed energy resources to obtain a preliminary integrated scheduling energy network, conduct a preliminary scheduling feasibility analysis on the preliminary integrated scheduling energy network, and optimize the preliminary integrated scheduling energy network based on the results of the preliminary scheduling feasibility analysis to obtain an integrated scheduling energy network.

[0015] Furthermore, in a preferred embodiment of the present invention, the preliminary integrated scheduling energy network is subjected to a preliminary scheduling feasibility analysis, and the preliminary integrated scheduling energy network is optimized based on the preliminary scheduling feasibility analysis result to obtain an integrated scheduling energy network, specifically:

[0016] Running a preliminary integrated dispatching energy network, determining whether there is an abnormal integrated dispatching state in the preliminary integrated dispatching energy network, wherein the abnormal integrated dispatching state has different types, wherein the types of the abnormal integrated dispatching state include energy resource conversion equipment being unable to convert energy of distributed energy resources into electric energy, energy storage equipment being unable to store electric energy, and substation being unable to perform power transformation processing;

[0017] The power grid system equipment, energy resource conversion equipment and all distributed energy resources are collectively referred to as energy network equipment. If there is an abnormal integrated scheduling state in the preliminary integrated scheduling energy network, the Bayesian network algorithm is introduced to obtain the working parameters of the energy network equipment with the abnormal integrated scheduling state during operation based on the type of the abnormal integrated scheduling state. The working parameters of the energy network equipment with the abnormal integrated scheduling state during operation are analyzed based on the Bayesian network algorithm to determine the fault location of the energy network equipment with the abnormal integrated scheduling state and mark it as the abnormal integrated scheduling location.

[0018] Retrieve and output the maintenance plan of the abnormal integrated dispatching position in the big data network, and determine whether the abnormal integrated dispatching state still exists in the preliminary integrated dispatching energy network after the maintenance plan of the abnormal integrated dispatching position is output;

[0019] If not, the preliminary integrated dispatching energy network is marked as the integrated dispatching energy network;

[0020] If so, after the maintenance plan for locating and outputting the abnormal integrated dispatching position in the preliminary integrated dispatching energy network is output, the position where the abnormal integrated dispatching state still exists is marked as a Class I abnormal integrated dispatching position, and the equipment components of the energy network equipment with the Class I abnormal integrated dispatching position are replaced, so that there is no abnormal integrated dispatching state in the preliminary integrated dispatching energy network, and an integrated dispatching energy network is obtained.

[0021] Furthermore, in a preferred embodiment of the present invention, the step S104 is specifically:

[0022] Communication sensors are installed in different devices in the integrated dispatching energy network, and a target communication frequency band is preset. The communication frequency bands of all communication sensors are adjusted to the target communication frequency band to obtain a communication system of the integrated dispatching energy network, which is calibrated as a target communication system, wherein the target communication system can monitor the response speed of different energy network devices to control instructions in real time;

[0023] Combine the target communication system and the integrated dispatching energy network to build a virtual power plant, introduce a meteorological platform, determine the real-time environmental parameters of the target resource integration range based on the meteorological platform, and calibrate them as the target operating environment parameters;

[0024] Running the virtual power plant, and during the operation of the virtual power plant, monitoring in real time the response speed of different energy network devices to control instructions when operating in target operating environment parameters, and calibrating the response speed as real-time response speed;

[0025] The initial model of the long short-term memory network is introduced, and the working parameters of different energy network devices in the virtual power plant during operation, the target operating environment parameters, and the real-time response speed of different energy network devices under the target operating environment parameters are imported into the initial model of the long short-term memory network for model cross-validation training to obtain the long short-term memory network analysis model;

[0026] Running the long short-term memory network analysis model, and presetting the coordinated operation target time, predicting the response speed of different energy network devices to the control instructions when they are running after the coordinated operation target time based on the long short-term memory network analysis model, and calibrating it as the predicted response speed;

[0027] The predicted response speeds of different energy network devices are sorted in reverse order to obtain a predicted response speed sorting table.

[0028] Furthermore, in a preferred embodiment of the present invention, the step S106 is specifically as follows:

[0029] Obtain all coordinated operation targets of distributed energy resources that need to be met when the virtual power plant is running, and mark them as coordinated operation targets;

[0030] The coordinated operation objectives include maximizing the energy utilization efficiency of distributed energy resources, minimizing the operating costs of distributed energy resources, and reducing carbon emissions;

[0031] Obtaining the purpose of constructing the virtual power plant, and based on the purpose of constructing the virtual power plant, sorting all coordinated operation targets in descending order of importance to obtain a coordinated operation target importance ranking table;

[0032] Introduce a multi-objective scheduling decision algorithm, and use the multi-objective decision algorithm to build a multi-objective scheduling decision model with different time scales based on the coordination operation target importance ranking table and the predicted response speed ranking table;

[0033] Based on the coordinated operation target time, a multi-objective scheduling decision model corresponding to the time scale under the coordinated operation target time is determined, calibrated as a standard multi-objective scheduling decision model, and the standard multi-objective scheduling decision model is run to generate all distributed energy coordinated operation scheduling strategies;

[0034] Among them, in different distributed energy coordinated scheduling operation strategies, the scheduling order, scheduling degree and scheduling time of energy network equipment are different;

[0035] All distributed energy coordinated scheduling operation strategies are simulated and initially screened, and the distributed energy coordinated scheduling operation strategies after the initial screening are re-screened using the Pareto optimal solution set algorithm to obtain the target distributed energy coordinated scheduling operation strategy.

[0036] Furthermore, in a preferred embodiment of the present invention, the simulation operation and strategy initial screening of all distributed energy coordinated scheduling operation strategies are performed, and the distributed energy coordinated scheduling operation strategies after the initial strategy screening are rescreened by genetic algorithm to obtain the target distributed energy coordinated scheduling operation strategy, which is specifically:

[0037] Determine the maximum load that different distributed energy resources in the integrated dispatching energy network in the virtual power plant can bear during operation, calibrate it as the maximum load, introduce the simulation operation module, and build a simulated power plant identical to the virtual power plant in the simulation operation module;

[0038] Running different distributed energy coordinated scheduling operation strategies in the simulated power plant, and calculating in real time in the simulated power plant the loads borne by different distributed energy resources during the running of different distributed energy coordinated scheduling operation strategies, and marking them as loads to be analyzed;

[0039] The distributed energy coordinated scheduling operation strategy corresponding to the load to be analyzed of all distributed energy resources being less than the maximum load is marked as a qualified distributed energy coordinated scheduling operation strategy;

[0040] The standard prediction response speed threshold of the preset energy network equipment is introduced into the genetic algorithm, and all qualified distributed energy coordinated scheduling operation strategies are analyzed based on the genetic algorithm, and the qualified distributed energy coordinated scheduling operation strategies whose prediction response speed of distributed energy resources is maintained within the standard prediction response speed threshold are selected and calibrated as a type of qualified distributed energy coordinated scheduling operation strategy;

[0041] A qualified distributed energy coordinated scheduling operation strategy with the highest ranking in the coordinated operation target importance ranking table is selected and marked as the target distributed energy coordinated scheduling operation strategy, and the output value of the target distributed energy coordinated scheduling operation strategy is operated in a virtual power plant.

[0042] The second aspect of the present invention further provides a distributed energy coordinated operation system based on a virtual power plant, the distributed energy coordinated operation system comprising a memory and a processor, the memory storing a distributed energy coordinated operation method, and when the distributed energy coordinated operation method is executed by the processor, the following steps are implemented:

[0043] Integrate all distributed energy resources to obtain a preliminary integrated dispatching energy network, and perform preliminary feasibility analysis and optimization on the preliminary integrated dispatching energy network to obtain an integrated dispatching energy network;

[0044] Integrate a communication system in the integrated dispatching energy network to build a virtual power plant, and predict the response speed of different energy network devices to control instructions under target operating environment parameters based on the virtual power plant, and finally sort the response speed of different energy network devices according to the response speed;

[0045] Construct a multi-objective scheduling decision model, generate different distributed energy coordinated operation scheduling strategies in the multi-objective scheduling decision model, and screen the optimal solutions for different distributed energy coordinated operation scheduling strategies.

[0046] The present invention solves the technical defects existing in the background technology, and the present invention has the following beneficial effects: integrating and processing all distributed energy resources to obtain an energy network that can be uniformly scheduled, and building a virtual power plant in combination with a communication system; calculating the response speed of different devices in the energy network that can be uniformly scheduled to control instructions in the virtual power plant, thereby building a multi-objective scheduling decision model to generate different distributed energy coordinated operation scheduling strategies, and finally screening the optimal solution for different distributed energy coordinated operation scheduling strategies. The present invention can coordinate the operation analysis of distributed energy resources in the form of a virtual power plant, generate the most appropriate distributed energy coordinated scheduling operation strategy output, and promote the rational use of distributed energy resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0048] Figure 1 A flow chart showing a method for coordinated operation of distributed energy based on a virtual power plant is provided;

[0049] Figure 2 A flow chart of a method for formulating a target distributed energy coordinated operation scheduling strategy is shown;

[0050] Figure 3 The program view of the distributed energy coordinated operation system based on the virtual power plant is shown. DETAILED DESCRIPTION

[0051] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0052] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0053] Figure 1 A flow chart of a distributed energy coordinated operation method based on a virtual power plant is shown, comprising the following steps:

[0054] S102: Integrate all distributed energy resources to obtain a preliminary integrated dispatching energy network, and perform preliminary dispatching feasibility analysis and optimization on the preliminary integrated dispatching energy network to obtain an integrated dispatching energy network;

[0055] S104: integrating a communication system in the integrated dispatching energy network to construct a virtual power plant, and predicting the response speed of different energy network devices to control instructions under target operating environment parameters based on the virtual power plant, and finally ranking the response speeds of different energy network devices according to the response speeds;

[0056] S106: Construct a multi-objective scheduling decision model, generate different distributed energy coordinated operation scheduling strategies in the multi-objective scheduling decision model, and screen the optimal solutions for different distributed energy coordinated operation scheduling strategies.

[0057] Furthermore, in a preferred embodiment of the present invention, the step S102 is specifically:

[0058] Determine the integration scope of distributed energy resources, mark it as the target resource integration scope, and obtain all distributed energy resources within the target resource integration scope;

[0059] Acquire power grid system equipment within the target resource integration scope, wherein the power grid system equipment includes substations, transmission lines and energy storage equipment;

[0060] Acquire energy resource conversion equipment and a big data network, retrieve a solution for integrating power grid system equipment, energy resource conversion equipment, and all distributed energy resources in the big data network, and mark it as a type of integration solution;

[0061] Among them, the first type of integration solution is to connect all distributed energy resources through transmission lines, and connect energy resource conversion equipment to each distributed energy resource, so that the energy output from the distributed energy resources is converted into electrical energy, and the electrical energy is stored in the energy storage equipment. The energy storage equipment imports the stored electrical energy into the substation for substation processing, and outputs the electrical energy for users to use;

[0062] Output a type of integration plan among power grid system equipment, energy resource conversion equipment and all distributed energy resources to obtain a preliminary integrated scheduling energy network.

[0063] It should be noted that distributed energy resources include solar photovoltaic power generation units, wind power generation units, energy storage charges, adjustable charges, etc. There may be multiple distributed energy resources within a specific range. Integrating all distributed energy resources to form a uniformly dispatchable energy network can achieve information sharing between different resources and achieve the purpose of original control. Therefore, it is necessary to build an integrated dispatching energy network to achieve unified dispatching of all distributed energy resources. After the distributed energy resources are integrated, the energy resources are converted into electric energy output, so it is necessary to connect the distributed energy resources with the power grid system equipment and the energy resource conversion equipment to facilitate the conversion of energy in the distributed energy resources into electric energy and supply it to the power grid system equipment for transformation, so as to supply it to users. A type of integration solution can be retrieved in a big data network, which is a database that brings together multiple solutions. After all devices are connected through a type of integration solution, a preliminary integrated dispatching energy network can be obtained.

[0064] Furthermore, in a preferred embodiment of the present invention, the preliminary integrated scheduling energy network is subjected to a preliminary scheduling feasibility analysis, and the preliminary integrated scheduling energy network is optimized based on the preliminary scheduling feasibility analysis result to obtain an integrated scheduling energy network, specifically:

[0065] Running a preliminary integrated dispatching energy network, determining whether there is an abnormal integrated dispatching state in the preliminary integrated dispatching energy network, wherein the abnormal integrated dispatching state has different types, wherein the types of the abnormal integrated dispatching state include energy resource conversion equipment being unable to convert energy of distributed energy resources into electric energy, energy storage equipment being unable to store electric energy, and substation being unable to perform power transformation processing;

[0066] The power grid system equipment, energy resource conversion equipment and all distributed energy resources are collectively referred to as energy network equipment. If there is an abnormal integrated scheduling state in the preliminary integrated scheduling energy network, the Bayesian network algorithm is introduced to obtain the working parameters of the energy network equipment with the abnormal integrated scheduling state during operation based on the type of the abnormal integrated scheduling state. The working parameters of the energy network equipment with the abnormal integrated scheduling state during operation are analyzed based on the Bayesian network algorithm to determine the fault location of the energy network equipment with the abnormal integrated scheduling state and mark it as the abnormal integrated scheduling location.

[0067] Retrieve and output the maintenance plan of the abnormal integrated dispatching position in the big data network, and determine whether the abnormal integrated dispatching state still exists in the preliminary integrated dispatching energy network after the maintenance plan of the abnormal integrated dispatching position is output;

[0068] If not, the preliminary integrated dispatching energy network is marked as the integrated dispatching energy network;

[0069] If so, after the maintenance plan for locating and outputting the abnormal integrated dispatching position in the preliminary integrated dispatching energy network is output, the position where the abnormal integrated dispatching state still exists is marked as a Class I abnormal integrated dispatching position, and the equipment components of the energy network equipment with the Class I abnormal integrated dispatching position are replaced, so that there is no abnormal integrated dispatching state in the preliminary integrated dispatching energy network, and an integrated dispatching energy network is obtained.

[0070] It should be noted that the preliminary integrated dispatching energy network is only to connect all devices, but whether the preliminary integrated dispatching energy network can operate normally requires further judgment and analysis. If the preliminary integrated dispatching energy network cannot operate normally, it is judged that it has an abnormal integrated dispatching state. When the preliminary integrated dispatching energy network has an abnormal integrated dispatching state, it is necessary to locate the abnormal position of the preliminary integrated dispatching energy network and determine the position of the energy network equipment where the abnormal integrated dispatching state occurs. The Bayesian network can locate the fault of the energy network equipment according to the working parameters of the energy network equipment during operation, thereby obtaining the abnormal integrated dispatching position. After the abnormal integrated dispatching position is overhauled, if the abnormal integrated dispatching state still exists in the preliminary integrated dispatching energy network, it is judged that the abnormal integrated dispatching state cannot be achieved after the preliminary integrated dispatching energy network is overhauled, and the corresponding equipment components of a type of abnormal integrated dispatching position need to be replaced to obtain an integrated dispatching energy network.

[0071] Furthermore, in a preferred embodiment of the present invention, the step S104 is specifically:

[0072] Communication sensors are installed in different devices in the integrated dispatching energy network, and a target communication frequency band is preset. The communication frequency bands of all communication sensors are adjusted to the target communication frequency band, and a communication system of the integrated dispatching energy network is obtained, which is calibrated as a target communication system, wherein the target communication system can monitor the response speed of different energy network devices to control instructions in real time;

[0073] Combine the target communication system and the integrated dispatching energy network to build a virtual power plant, introduce a meteorological platform, determine the real-time environmental parameters of the target resource integration range based on the meteorological platform, and calibrate them as the target operating environment parameters;

[0074] Running the virtual power plant, and during the operation of the virtual power plant, monitoring in real time the response speed of different energy network devices to control instructions when operating in target operating environment parameters, and calibrating the response speed as real-time response speed;

[0075] The initial model of the long short-term memory network is introduced, and the working parameters of different energy network devices in the virtual power plant during operation, the target operating environment parameters, and the real-time response speed of different energy network devices under the target operating environment parameters are imported into the initial model of the long short-term memory network for model cross-validation training to obtain the long short-term memory network analysis model;

[0076] Running the long short-term memory network analysis model, and presetting the coordinated operation target time, predicting the response speed of different energy network devices to the control instructions when they are running after the coordinated operation target time based on the long short-term memory network analysis model, and calibrating it as the predicted response speed;

[0077] The predicted response speeds of different energy network devices are sorted in reverse order to obtain a predicted response speed sorting table.

[0078] It should be noted that after the communication sensors are installed, different communication sensors can be connected to realize the communication processing of different energy network devices. The content of the communication is to share the state parameter information between different energy network devices, so as to realize the coordinated operation of different distributed energy resources in the integrated dispatching energy network system. The communication sensors are connected to build a communication system. To build a communication system, the frequency band of the communication sensors needs to be adjusted to the same frequency band to ensure that the communication sensors can transmit information within the agreed frequency band. In the target communication system, the response speed of different energy network devices to the control instructions can be monitored. The response speed reflects the sensitivity of the energy network equipment to receive instructions. The virtual power plant is a power coordination management system that realizes the aggregation and coordinated optimization of distributed energy resources through advanced information communication technology and software systems, so as to participate in the power market and power grid operation as a special power plant. The virtual power plant consists of a communication system and an integrated dispatching energy network. When the virtual power plant is operated, the energy network equipment has a response speed to the control instructions under the current target operating environment parameters, and a real-time response speed. According to the real-time response speed and the target operating environment parameters, the long short-term memory network initial model can predict the predicted response speed of the energy network equipment in the virtual power plant after continuing to operate to the target time under the current real-time response speed and the target operating environment parameters. The purpose of obtaining the predicted response speed is to determine the order of coordination and the output size when coordinating the operation of distributed energy resources according to their corresponding response speed. Therefore, it is also necessary to sort the predicted response speeds of different energy network devices in reverse order to obtain a predicted response speed sorting table.

[0079] Figure 2 A flow chart of a method for formulating a target distributed energy coordinated operation scheduling strategy is shown, including the following steps:

[0080] S202: Determine the importance ranking table of coordination operation objectives;

[0081] S204: construct a standard multi-objective scheduling decision model, and generate different distributed energy coordinated scheduling operation strategies based on the standard multi-objective scheduling decision model;

[0082] S206: Simulate and preliminarily screen all distributed energy coordinated scheduling operation strategies, and re-screen the distributed energy coordinated scheduling operation strategies after the preliminarily screened strategies through a genetic algorithm to obtain a target distributed energy coordinated scheduling operation strategy.

[0083] Furthermore, in a preferred embodiment of the present invention, the step S202 is specifically:

[0084] Obtain all coordinated operation targets of distributed energy resources that need to be met when the virtual power plant is running, and mark them as coordinated operation targets;

[0085] The coordinated operation objectives include maximizing the energy utilization efficiency of distributed energy resources, minimizing the operating costs of distributed energy resources, and reducing carbon emissions;

[0086] The purpose of constructing the virtual power plant is obtained, and based on the purpose of constructing the virtual power plant, all coordinated operation targets are sorted in descending order of importance to obtain a coordinated operation target importance ranking table.

[0087] It should be noted that the purpose of obtaining coordinated operation goals is to ensure that distributed energy resources can achieve coordinated operation according to user needs, such as maximizing the energy utilization efficiency of distributed energy resources, minimizing the operating costs of distributed energy resources, and reducing carbon emissions. The purpose of constructing virtual electromagnetics is one of the above three. Different purposes have different importance to users, so it is necessary to sort the importance and obtain a ranking table of the importance of coordinated operation goals.

[0088] Furthermore, in a preferred embodiment of the present invention, the step S204 is specifically:

[0089] Introduce a multi-objective scheduling decision algorithm, and use the multi-objective decision algorithm to build a multi-objective scheduling decision model with different time scales based on the coordination operation target importance ranking table and the predicted response speed ranking table;

[0090] Based on the coordinated operation target time, a multi-objective scheduling decision model corresponding to the time scale under the coordinated operation target time is determined, calibrated as a standard multi-objective scheduling decision model, and the standard multi-objective scheduling decision model is run to generate all distributed energy coordinated operation scheduling strategies;

[0091] Among them, in different distributed energy coordinated scheduling operation strategies, the scheduling order, scheduling degree and scheduling time of energy network equipment are different.

[0092] It should be noted that the multi-objective scheduling decision algorithm can construct multi-objective scheduling decision models of different time scales based on the coordinated operation target importance ranking table and the predicted response speed ranking table. Among them, the time scale includes the hour-level day-ahead optimization scheduling model and the minute-level intraday optimization scheduling model. After the multi-objective scheduling decision algorithm analyzes the coordinated operation target importance ranking table and the predicted response speed ranking table, all the decisions obtained are related to the coordinated operation target importance ranking table and the predicted response speed ranking table. In different decisions, the scheduling order, scheduling degree and scheduling time of different energy network equipment are different. Based on the target time, the multi-objective scheduling decision model of the corresponding time scale is determined, and different distributed energy coordinated scheduling operation strategies are obtained.

[0093] Furthermore, in a preferred embodiment of the present invention, the step S206 is specifically:

[0094] Determine the maximum load that different distributed energy resources in the integrated dispatching energy network in the virtual power plant can bear during operation, calibrate it as the maximum load, introduce the simulation operation module, and build a simulated power plant identical to the virtual power plant in the simulation operation module;

[0095] Running different distributed energy coordinated scheduling operation strategies in the simulated power plant, and calculating in real time in the simulated power plant the loads borne by different distributed energy resources during the running of different distributed energy coordinated scheduling operation strategies, and marking them as loads to be analyzed;

[0096] The distributed energy coordinated scheduling operation strategy corresponding to the load to be analyzed of all distributed energy resources being less than the maximum load is marked as a qualified distributed energy coordinated scheduling operation strategy;

[0097] The standard prediction response speed threshold of the preset energy network equipment is introduced into the genetic algorithm, and all qualified distributed energy coordinated scheduling operation strategies are analyzed based on the genetic algorithm, and the qualified distributed energy coordinated scheduling operation strategies whose prediction response speed of distributed energy resources is maintained within the standard prediction response speed threshold are selected and calibrated as a type of qualified distributed energy coordinated scheduling operation strategy;

[0098] A qualified distributed energy coordinated scheduling operation strategy with the highest ranking in the coordinated operation target importance ranking table is selected and marked as the target distributed energy coordinated scheduling operation strategy, and the output value of the target distributed energy coordinated scheduling operation strategy is operated in a virtual power plant.

[0099] It should be noted that the purpose of constructing a simulation power plant is to simulate and analyze the virtual power plant, so as to more intuitively judge the state existing in the operation process of the virtual power plant. During the operation of the simulation power plant, the load of its distributed energy resources cannot exceed the maximum load that can be borne, otherwise there will be safety hazards in the operation of the distributed energy resources. Select the corresponding distributed energy coordination and scheduling operation strategy output whose load to be analyzed is less than the maximum load, that is, output the qualified distributed energy coordination and scheduling operation strategy. There may be multiple qualified distributed energy coordination and scheduling operation strategies, which need to be screened further. All qualified distributed energy coordination and scheduling operation strategies are calculated by genetic algorithm, and the corresponding strategy output whose predicted response speed of distributed energy resources is maintained within the standard value is selected. The purpose is to maximize the response speed of different distributed energy resources and achieve timeliness and efficiency in the coordinated operation of distributed energy resources. At the same time, it is necessary to select the highest-ranked qualified distributed energy coordination and scheduling operation strategy in the coordination operation target importance ranking table, so that the strategy is most in line with the construction purpose of the virtual power plant, that is, to select the target distributed energy coordination and scheduling operation strategy.

[0100] In addition, the distributed energy coordinated operation method based on the virtual power plant also includes the following steps:

[0101] Preset standard response speed ranges for different energy network devices, and analyze the predicted response speeds of different energy network devices to determine whether there is an energy network device whose predicted response speed is not within the standard response speed range;

[0102] If not, directly generate a predicted response speed ranking table based on the predicted response speeds of different energy network devices in reverse order;

[0103] If yes, the corresponding energy network device is marked as the energy network device to be analyzed, and the electromagnetic induction intensity of the energy network device to be analyzed is monitored to obtain the electromagnetic induction intensity of the energy network device to be analyzed, and at the same time, the maximum electromagnetic induction intensity that can be tolerated by the energy network device to be analyzed is retrieved based on the big data network;

[0104] When the electromagnetic induction intensity of the energy network device to be analyzed is greater than the maximum electromagnetic induction intensity that can be tolerated, a filter is installed on the corresponding energy network device to be analyzed, and the filter is allowed to make the electromagnetic induction intensity of the corresponding energy network device to be analyzed less than the maximum electromagnetic induction intensity that can be tolerated;

[0105] If the electromagnetic induction intensity of all energy network devices to be analyzed is less than the maximum tolerable electromagnetic induction intensity, but there are still energy network devices to be analyzed, the predicted response speed of the energy network devices to be analyzed will be obtained, and the operating process working parameters of other energy network devices that are not energy network devices to be analyzed will be adjusted to make the predicted response speed of other energy network devices that are not energy network devices to be analyzed greater than the predicted response speed of the energy network devices to be analyzed.

[0106] It should be noted that when there are energy network devices to be analyzed, that is, there are energy network devices whose predicted response speed is not within the standard response speed range, if a virtual power plant is operated at this time, different response speeds may cause the working time of each device to be out of sync, and there is a risk of hidden dangers. It is necessary to monitor and optimize the energy network devices to be analyzed. Since communication sensors can analyze the response speed of energy network devices, and the electromagnetic intensity will affect the normal operation of communication sensors, it is necessary to determine whether the electromagnetic interference intensity of the energy network devices to be analyzed is greater than the standard value. If so, a filter is required to be used for filtering to ensure that the electromagnetic interference intensity is less than the standard value. When the electromagnetic interference intensity of all energy network devices to be analyzed is less than the standard value, but there are still abnormal predicted response speeds of energy network devices, that is, there are still energy network devices to be analyzed, it is necessary to synchronize the response speeds of all energy network devices, and the working parameters of other devices other than the energy network devices to be analyzed can be adjusted to synchronize the predicted response speeds of all devices to avoid safety hazards.

[0107] like Figure 3 As shown, the second aspect of the present invention further provides a distributed energy coordinated operation system based on a virtual power plant, the distributed energy coordinated operation system includes a memory 31 and a processor 32, the memory 31 stores a distributed energy coordinated operation method, and when the distributed energy coordinated operation method is executed by the processor 32, the following steps are implemented:

[0108] Integrate all distributed energy resources to obtain a preliminary integrated dispatching energy network, and perform preliminary feasibility analysis and optimization on the preliminary integrated dispatching energy network to obtain an integrated dispatching energy network;

[0109] Integrate a communication system in the integrated dispatching energy network to build a virtual power plant, and predict the response speed of different energy network devices to control instructions under target operating environment parameters based on the virtual power plant, and finally sort the response speed of different energy network devices according to the response speed;

[0110] Construct a multi-objective scheduling decision model, generate different distributed energy coordinated operation scheduling strategies in the multi-objective scheduling decision model, and screen the optimal solutions for different distributed energy coordinated operation scheduling strategies.

[0111] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A distributed energy coordinated operation method based on a virtual power plant, characterized in that: The following steps are involved: S102: Integrate all distributed energy resources to obtain a preliminary integrated dispatching energy network, and perform preliminary dispatching feasibility analysis and optimization on the preliminary integrated dispatching energy network to obtain an integrated dispatching energy network; S104: integrating a communication system in the integrated dispatching energy network to construct a virtual power plant, and predicting the response speed of different energy network devices to control instructions under target operating environment parameters based on the virtual power plant, and finally ranking the response speeds of different energy network devices according to the response speeds; S106: construct a multi-objective scheduling decision model, generate different distributed energy coordinated operation scheduling strategies in the multi-objective scheduling decision model, and screen the optimal solutions of the different distributed energy coordinated operation scheduling strategies; Wherein, the S106 is specifically: Obtain all coordinated operation targets of distributed energy resources that need to be met when the virtual power plant is running, and mark them as coordinated operation targets; The coordinated operation objectives include maximizing the energy utilization efficiency of distributed energy resources, minimizing the operating costs of distributed energy resources, and reducing carbon emissions; Obtaining the purpose of constructing the virtual power plant, and based on the purpose of constructing the virtual power plant, sorting all coordinated operation targets in descending order of importance to obtain a coordinated operation target importance ranking table; Introduce a multi-objective scheduling decision algorithm, and use the multi-objective decision algorithm to build a multi-objective scheduling decision model with different time scales based on the coordination operation target importance ranking table and the predicted response speed ranking table; Based on the coordinated operation target time, a multi-objective scheduling decision model corresponding to the time scale under the coordinated operation target time is determined, calibrated as a standard multi-objective scheduling decision model, and the standard multi-objective scheduling decision model is run to generate all distributed energy coordinated operation scheduling strategies; Among them, in different distributed energy coordinated scheduling operation strategies, the scheduling order, scheduling degree and scheduling time of energy network equipment are different; All distributed energy coordination and dispatching operation strategies are simulated and preliminarily screened, and the distributed energy coordination and dispatching operation strategies after the preliminary screening are rescreened through the Pareto optimal solution set algorithm to obtain the target distributed energy coordination and dispatching operation strategy; Among them, the simulation operation and strategy initial screening of all distributed energy coordinated scheduling operation strategies are performed, and the distributed energy coordinated scheduling operation strategies after the initial strategy screening are re-screened by genetic algorithm to obtain the target distributed energy coordinated scheduling operation strategy, which is specifically: Determine the maximum load that different distributed energy resources in the integrated dispatching energy network in the virtual power plant can bear during operation, calibrate it as the maximum load, introduce the simulation operation module, and build a simulated power plant identical to the virtual power plant in the simulation operation module; Running different distributed energy coordinated scheduling operation strategies in the simulated power plant, and calculating in real time in the simulated power plant the loads borne by different distributed energy resources during the running of different distributed energy coordinated scheduling operation strategies, and marking them as loads to be analyzed; The distributed energy coordinated scheduling operation strategy corresponding to the load to be analyzed of all distributed energy resources being less than the maximum load is marked as a qualified distributed energy coordinated scheduling operation strategy; The standard prediction response speed threshold of the preset energy network equipment is introduced into the genetic algorithm, and all qualified distributed energy coordinated scheduling operation strategies are analyzed based on the genetic algorithm, and the qualified distributed energy coordinated scheduling operation strategies whose prediction response speed of distributed energy resources is maintained within the standard prediction response speed threshold are selected and calibrated as a type of qualified distributed energy coordinated scheduling operation strategy; A qualified distributed energy coordinated scheduling operation strategy with the highest ranking in the coordinated operation target importance ranking table is selected and marked as the target distributed energy coordinated scheduling operation strategy, and the output value of the target distributed energy coordinated scheduling operation strategy is operated in a virtual power plant.

2. The method for coordinated operation of distributed energy based on a virtual power plant according to claim 1, characterized in that: The S102 is specifically: Determine the integration scope of distributed energy resources, mark it as the target resource integration scope, and obtain all distributed energy resources within the target resource integration scope; Acquire power grid system equipment within the target resource integration scope, wherein the power grid system equipment includes substations, transmission lines and energy storage equipment; Acquire energy resource conversion equipment and a big data network, retrieve a solution for integrating power grid system equipment, energy resource conversion equipment, and all distributed energy resources in the big data network, and mark it as a type of integration solution; Among them, the first type of integration solution is to connect all distributed energy resources through transmission lines, and connect energy resource conversion equipment to each distributed energy resource, so that the energy output from the distributed energy resources is converted into electrical energy, and the electrical energy is stored in the energy storage equipment. The energy storage equipment imports the stored electrical energy into the substation for substation processing, and outputs the electrical energy for users to use; Output a type of integration plan among power grid system equipment, energy resource conversion equipment and all distributed energy resources to obtain a preliminary integrated scheduling energy network, conduct a preliminary scheduling feasibility analysis on the preliminary integrated scheduling energy network, and optimize the preliminary integrated scheduling energy network based on the results of the preliminary scheduling feasibility analysis to obtain an integrated scheduling energy network.

3. The method for coordinated operation of distributed energy based on virtual power plants according to claim 2, characterized in that: The preliminary feasibility analysis of scheduling of the preliminary integrated scheduling energy network is performed, and the preliminary integrated scheduling energy network is optimized based on the results of the preliminary scheduling feasibility analysis to obtain an integrated scheduling energy network, which is specifically: Running a preliminary integrated dispatching energy network, determining whether there is an abnormal integrated dispatching state in the preliminary integrated dispatching energy network, wherein the abnormal integrated dispatching state has different types, wherein the types of the abnormal integrated dispatching state include energy resource conversion equipment being unable to convert energy of distributed energy resources into electric energy, energy storage equipment being unable to store electric energy, and substation being unable to perform power transformation processing; The power grid system equipment, energy resource conversion equipment and all distributed energy resources are collectively referred to as energy network equipment. If there is an abnormal integrated scheduling state in the preliminary integrated scheduling energy network, the Bayesian network algorithm is introduced to obtain the working parameters of the energy network equipment with the abnormal integrated scheduling state during operation based on the type of the abnormal integrated scheduling state. The working parameters of the energy network equipment with the abnormal integrated scheduling state during operation are analyzed based on the Bayesian network algorithm to determine the fault location of the energy network equipment with the abnormal integrated scheduling state and mark it as the abnormal integrated scheduling location. Retrieve and output the maintenance plan of the abnormal integrated dispatching position in the big data network, and determine whether the abnormal integrated dispatching state still exists in the preliminary integrated dispatching energy network after the maintenance plan of the abnormal integrated dispatching position is output; If not, the preliminary integrated dispatching energy network is marked as the integrated dispatching energy network; If so, after the maintenance plan for locating and outputting the abnormal integrated dispatching position in the preliminary integrated dispatching energy network is output, the position where the abnormal integrated dispatching state still exists is marked as a Class I abnormal integrated dispatching position, and the equipment components of the energy network equipment with the Class I abnormal integrated dispatching position are replaced, so that there is no abnormal integrated dispatching state in the preliminary integrated dispatching energy network, and an integrated dispatching energy network is obtained.

4. The method for coordinated operation of distributed energy based on a virtual power plant according to claim 1, characterized in that: The S104 is specifically: Communication sensors are installed in different devices in the integrated dispatching energy network, and a target communication frequency band is preset. The communication frequency bands of all communication sensors are adjusted to the target communication frequency band, and a communication system of the integrated dispatching energy network is obtained, which is calibrated as a target communication system, wherein the target communication system can monitor the response speed of different energy network devices to control instructions in real time; Combine the target communication system and the integrated dispatching energy network to build a virtual power plant, introduce a meteorological platform, determine the real-time environmental parameters of the target resource integration range based on the meteorological platform, and calibrate them as the target operating environment parameters; Running the virtual power plant, and during the operation of the virtual power plant, monitoring in real time the response speed of different energy network devices to control instructions when operating in target operating environment parameters, and calibrating the response speed as real-time response speed; The initial model of the long short-term memory network is introduced, and the working parameters of different energy network devices in the virtual power plant during operation, the target operating environment parameters, and the real-time response speed of different energy network devices under the target operating environment parameters are imported into the initial model of the long short-term memory network for model cross-validation training to obtain the long short-term memory network analysis model; Running the long short-term memory network analysis model, and presetting the coordinated operation target time, predicting the response speed of different energy network devices to the control instructions when they are running after the coordinated operation target time based on the long short-term memory network analysis model, and calibrating it as the predicted response speed; The predicted response speeds of different energy network devices are sorted in reverse order to obtain a predicted response speed sorting table.

5. The distributed energy coordinated operation system based on virtual power plant is characterized by: The distributed energy coordinated operation system includes a memory and a processor, wherein the memory stores a distributed energy coordinated operation method program, and when the distributed energy coordinated operation method program is executed by the processor, the distributed energy coordinated operation method steps as described in any one of claims 1 to 4 are implemented: S102: Integrate all distributed energy resources to obtain a preliminary integrated dispatching energy network, and perform preliminary dispatching feasibility analysis and optimization on the preliminary integrated dispatching energy network to obtain an integrated dispatching energy network; S104: integrating a communication system in the integrated dispatching energy network to construct a virtual power plant, and predicting the response speed of different energy network devices to control instructions under target operating environment parameters based on the virtual power plant, and finally ranking the response speeds of different energy network devices according to the response speeds; S106: construct a multi-objective scheduling decision model, generate different distributed energy coordinated operation scheduling strategies in the multi-objective scheduling decision model, and screen the optimal solutions of the different distributed energy coordinated operation scheduling strategies; Wherein, the S106 is specifically: Obtain all coordinated operation targets of distributed energy resources that need to be met when the virtual power plant is running, and mark them as coordinated operation targets; The coordinated operation objectives include maximizing the energy utilization efficiency of distributed energy resources, minimizing the operating costs of distributed energy resources, and reducing carbon emissions; Obtaining the purpose of constructing the virtual power plant, and based on the purpose of constructing the virtual power plant, sorting all coordinated operation targets in descending order of importance to obtain a coordinated operation target importance ranking table; Introduce a multi-objective scheduling decision algorithm, and use the multi-objective decision algorithm to build a multi-objective scheduling decision model with different time scales based on the coordination operation target importance ranking table and the predicted response speed ranking table; Based on the coordinated operation target time, a multi-objective scheduling decision model corresponding to the time scale under the coordinated operation target time is determined, calibrated as a standard multi-objective scheduling decision model, and the standard multi-objective scheduling decision model is run to generate all distributed energy coordinated operation scheduling strategies; Among them, in different distributed energy coordinated scheduling operation strategies, the scheduling order, scheduling degree and scheduling time of energy network equipment are different; All distributed energy coordination and dispatching operation strategies are simulated and preliminarily screened, and the distributed energy coordination and dispatching operation strategies after the preliminary screening are rescreened through the Pareto optimal solution set algorithm to obtain the target distributed energy coordination and dispatching operation strategy; Among them, the simulation operation and strategy initial screening of all distributed energy coordinated scheduling operation strategies are performed, and the distributed energy coordinated scheduling operation strategies after the initial strategy screening are re-screened by genetic algorithm to obtain the target distributed energy coordinated scheduling operation strategy, which is specifically: Determine the maximum load that different distributed energy resources in the integrated dispatching energy network in the virtual power plant can bear during operation, calibrate it as the maximum load, introduce the simulation operation module, and build a simulated power plant identical to the virtual power plant in the simulation operation module; Running different distributed energy coordinated scheduling operation strategies in the simulated power plant, and calculating in real time in the simulated power plant the loads borne by different distributed energy resources during the running of different distributed energy coordinated scheduling operation strategies, and marking them as loads to be analyzed; The distributed energy coordinated scheduling operation strategy corresponding to the load to be analyzed of all distributed energy resources being less than the maximum load is marked as a qualified distributed energy coordinated scheduling operation strategy; The standard prediction response speed threshold of the preset energy network equipment is introduced into the genetic algorithm, and all qualified distributed energy coordinated scheduling operation strategies are analyzed based on the genetic algorithm, and the qualified distributed energy coordinated scheduling operation strategies whose prediction response speed of distributed energy resources is maintained within the standard prediction response speed threshold are selected and calibrated as a type of qualified distributed energy coordinated scheduling operation strategy; A qualified distributed energy coordinated scheduling operation strategy with the highest ranking in the coordinated operation target importance ranking table is selected and marked as the target distributed energy coordinated scheduling operation strategy, and the output value of the target distributed energy coordinated scheduling operation strategy is operated in a virtual power plant.

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