A virtual power plant operation control method and system

Abstract

The present application provides a virtual power plant operation control method and system, which first obtains a backup strategy based on the actual situation of the virtual power plant at the current stage, and then performs simulation and evaluation of basic operation control and collaborative operation control respectively. The first operation control cost of the basic strategy is generated through actual operation control, and the simulated operation test is used to generate the simulated operation test results of multiple enabled control strategies under the collaborative strategy, and then the collaborative operation test results and the corresponding second operation control cost are obtained through collaborative integration. Finally, by comparing the costs of the two strategies, the optimal target operation control strategy is determined. In this way, the operation strategy can be dynamically adjusted according to actual needs and changes in the external environment, effectively reducing the operation cost. At the same time, the introduction of the collaborative operation control strategy enhances the interaction ability of the virtual power plant with the surrounding power grid or other virtual power plants, promotes the optimal configuration and sharing of regional energy, and improves the overall energy utilization efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of virtual power plants, and more specifically, to a method and system for controlling the operation of a virtual power plant. Background Art

[0002] With the transformation of the global energy structure and the rapid development of smart grid technology, virtual power plants, as an innovative energy management method, have shown great potential in improving the flexibility of power systems, optimizing resource allocation, and promoting the consumption of renewable energy. However, virtual power plants face many challenges in actual operation, such as how to flexibly adjust operation strategies according to real-time load demand and energy output to maximize economic and environmental benefits; how to effectively interact with surrounding power grids or other virtual power plants to improve regional energy efficiency; and how to accurately evaluate the costs and benefits of different operation control strategies to provide a scientific basis for decision-making.

[0003] Traditional virtual power plant operation control methods often rely on empirical judgment or fixed operation rules, which are difficult to adapt to the complex and changing operation environment and energy market changes. At the same time, most existing methods focus on the internal optimization of a single virtual power plant, ignoring the coordinated interaction with surrounding power grids or other virtual power plants, limiting the improvement of overall energy efficiency.

[0004] In order to overcome the above problems, the field urgently needs a virtual power plant operation control method that can comprehensively consider multiple factors, flexibly adjust operation strategies, and achieve cross-regional collaborative interaction. Summary of the invention

[0005] In order to at least overcome the above-mentioned deficiencies in the prior art, the purpose of the present application is to provide a virtual power plant operation control method and system.

[0006] In a first aspect, the present application provides a virtual power plant operation control method, the method comprising:

[0007] Obtaining a standby operation control strategy corresponding to the virtual power plant at this stage; the standby operation control strategy includes a basic operation control strategy and a coordinated operation control strategy;

[0008] According to the basic operation control strategy, the operation of the virtual power plant in this stage is regulated and controlled to generate a first operation regulation cost corresponding to the basic operation control strategy;

[0009] Acquire multiple enabled operation control strategies corresponding to the collaborative operation control strategy, simulate the operation of the virtual power plant in this stage according to each enabled operation control strategy, generate simulated operation test results corresponding to each enabled operation control strategy, coordinately integrate each simulated operation test result to generate a collaborative operation test result, and generate a second operation regulation cost corresponding to the collaborative operation control strategy according to the collaborative operation test result;

[0010] Determining the target operation control strategy corresponding to the virtual power plant in this stage from the basic operation control strategy and the collaborative operation control strategy according to the first operation regulation cost and the second operation regulation cost;

[0011] For example, in a possible implementation of the first aspect, the step of determining, based on the first operation regulation cost and the second operation regulation cost, the target operation control strategy corresponding to the virtual power plant at this stage from the basic operation control strategy and the collaborative operation control strategy includes:

[0012] Calculating a cost difference between a first operation regulation cost of the basic operation control strategy and a second operation regulation cost of the coordinated operation control strategy;

[0013] If the cost difference is a positive number, and the difference between the cost difference and 0 is greater than a first threshold, selecting the basic operation control strategy as the target operation control strategy;

[0014] If the cost difference is a negative number, and the difference between the cost difference and 0 is greater than a second threshold, the coordinated operation control strategy is used as the target operation control strategy;

[0015] If the cost difference is a positive number and the difference between the cost difference and 0 is not greater than a first threshold, and / or if the cost difference is a negative number and the difference between the cost difference and 0 is not greater than a second threshold, performing a cost-benefit analysis on the collaborative operation control strategy to evaluate the additional benefit parameter value of the collaborative operation control strategy, and calculating the difference between the cost difference and the additional benefit parameter value to generate a total cost difference;

[0016] If the total cost difference is less than 0, the collaborative operation control strategy is selected as the target operation control strategy, and if the total cost difference is greater than 0, the basic operation control strategy is selected as the target operation control strategy.

[0017] In a second aspect, an embodiment of the present application further provides a virtual power plant operation and control system, which includes a processor and a machine-readable storage medium, in which a computer program is stored. The computer program is loaded and executed in conjunction with the processor to implement the virtual power plant operation and control method of the first aspect above.

[0018] By adopting the technical solutions of any of the above aspects, the embodiment of the present application realizes efficient optimization and intelligent decision-making of the operation of the virtual power plant by integrating the backup operation control strategy (including the basic operation control strategy and the collaborative operation control strategy). Specifically, the backup strategy is first obtained according to the actual situation of the virtual power plant at the current stage, and then the simulation and evaluation of the basic operation control and the collaborative operation control are performed respectively. The first operation control cost of the basic strategy is generated by actual operation control, and the simulated operation test results of multiple enabled control strategies under the collaborative strategy are generated by simulated operation test, and then the collaborative operation test results and the corresponding second operation control cost are obtained through collaborative integration. Finally, by comparing the costs of the two strategies, the optimal target operation control strategy is determined. As a result, the flexibility and economy of the operation of the virtual power plant are significantly improved, and the operation strategy can be dynamically adjusted according to actual needs and changes in the external environment, effectively reducing the operation cost. At the same time, the introduction of the collaborative operation control strategy enhances the interaction ability of the virtual power plant with the surrounding power grid or other virtual power plants, promotes the optimal configuration and sharing of regional energy, and improves the overall energy utilization efficiency. In addition, by combining simulated operation tests with cost evaluation, a scientific basis is provided for decision-making, ensuring the effectiveness and rationality of the operation strategy, and providing a strong guarantee for the stable and efficient operation of the virtual power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained by combining these drawings without paying creative work.

[0020] Figure 1 A flowchart of a virtual power plant operation control method provided in an embodiment of the present application;

[0021] Figure 2 A block diagram showing the functional structure of a virtual power plant operation control system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The following description is intended to enable one of ordinary skill in the art to implement and combine the present application, and the description is provided in the context of a specific application scenario and its requirements. It will be apparent to one of ordinary skill in the art that various changes may be made to the disclosed embodiments, and that the general principles defined in the present application may be applied to other embodiments and application scenarios without departing from the principles and scope of the present application. Therefore, the present application is not limited to the described embodiments, but should be given the broadest scope consistent with the claims.

[0023] See also Figure 1 As shown, the present application provides a virtual power plant operation control method, including the following steps.

[0024] Step S110, obtaining the standby operation control strategy corresponding to the virtual power plant in this stage. The standby operation control strategy includes a basic operation control strategy and a coordinated operation control strategy.

[0025] In detail, the standby operation control strategy refers to a series of control strategies pre-formulated to cope with various situations that may be encountered by virtual power plants under different operating conditions, aiming to ensure that virtual power plants can maintain efficient, stable and economical operation in various operating scenarios. For example, the standby operation control strategy usually includes a basic operation control strategy and a collaborative operation control strategy. The former is the basic framework for the daily operation of the virtual power plant, and the latter is a special strategy for collaborative operation with surrounding power grids or other virtual power plants. Among them, the basic operation control strategy is the basic control strategy for the daily operation of the virtual power plant, which defines how to reasonably dispatch various energy resources (such as wind power, solar energy, hydropower, gas turbines, etc.) to meet power demand under different load demands and energy output conditions. The collaborative operation control strategy refers to the control strategy when the virtual power plant conducts energy transactions and mutual assistance with surrounding power grids or other virtual power plants, aiming to optimize energy distribution, improve energy utilization efficiency, and reduce overall operating costs through regional collaboration.

[0026] In this embodiment, it is assumed that there is a large virtual power plant that integrates multiple energy resources, including but not limited to wind farms, solar farms, hydroelectric power stations, gas turbines, energy storage systems, and controllable loads. This virtual power plant serves a wide area, covering cities, industrial parks, and rural areas.

[0027] At the current stage, the server needs to obtain a suitable backup operation control strategy for this complex virtual power plant. First, the server deeply analyzes various data and information of the virtual power plant. For example, the historical operation data is first obtained, including the output of various energy resources in different seasons and time periods in the past, the change trend of load demand, and the charge and discharge cycle records of the energy storage system. At the same time, the server also collects current real-time data, such as current weather conditions (affecting the output of solar and wind energy), immediate load demand in various regions, and the remaining capacity of the energy storage system.

[0028] Based on this rich data, the server begins to filter from a large number of pre-set template operation control strategies. These template operation control strategies cover a variety of possible operation scenarios and response methods.

[0029] To determine the basic operation control strategy, the server first evaluates the performance of each template operation control strategy in meeting the basic load demand and ensuring the stability of power supply. For example, template operation control strategy A may focus on giving priority to the use of renewable energy (such as wind and solar energy), meeting the load demand when its output is sufficient, and storing the excess electricity in the energy storage system; while template operation control strategy B may pay more attention to the stable output of gas turbines and hydropower stations to cope with the intermittent nature of renewable energy.

[0030] For example, the server analyzes the energy output, consumption, and distribution of each template operation control strategy in different scenarios through simulation and calculation. It takes into account various cost factors, such as wear and aging of equipment, efficiency loss of energy conversion, and maintenance requirements of the system. Suppose that it is found in the simulation that in the long-term operation of template operation control strategy A, due to the uncertainty of frequent reliance on renewable energy, the energy storage system is overcharged and discharged, thereby increasing the aging rate and maintenance cost of the battery; while template operation control strategy B can provide stable output, but the fuel consumption of the gas turbine is high, and the water resource utilization efficiency of the hydropower station needs to be improved.

[0031] After comprehensive evaluation and comparison, the server finally determined the template operation control strategy C as the basic operation control strategy for the virtual power plant in this phase. Strategy C adopts a balanced approach to flexibly adjust the output of gas turbines and hydropower plants according to the predicted output of renewable energy and changes in load demand, while optimizing the use of energy storage systems to minimize the overall operating cost.

[0032] When determining the collaborative operation control strategy, the server takes into account the interactive relationship between the virtual power plant and other virtual power plants or energy networks in the vicinity. Assuming that there is another virtual power plant in the vicinity that mainly uses traditional energy, they can trade and help each other with energy. The server obtains template operation control strategies that can promote such collaborative cooperation. For example, collaborative strategy D proposes to sell excess electricity to surrounding virtual power plants when the renewable energy output of this virtual power plant is in excess, and to purchase from the other party when its own energy is insufficient; collaborative strategy E recommends that both parties jointly plan power generation plans to cope with major load fluctuations in the region.

[0033] The server simulates different coordination scenarios to evaluate the impact of each coordination strategy on the virtual power plant. It takes into account factors such as the cost of energy transactions, transmission losses, and the communication and coordination costs of coordinated planning. Assume that after analysis, it is found that coordination strategy D may be risky when energy prices fluctuate greatly, while coordination strategy E requires more preliminary communication and coordination work, but in the long run it can more effectively reduce the overall operating cost.

[0034] Finally, the server determines that collaborative strategy E is the collaborative operation control strategy of the virtual power plant in this stage, and together with the basic operation control strategy C, it constitutes the backup operation control strategy.

[0035] Step S120: performing operation regulation and control on the virtual power plant in this stage according to the basic operation control strategy, and generating a first operation regulation and control cost corresponding to the basic operation control strategy.

[0036] In detail, the first operation and control cost refers to the cost incurred by actually operating and controlling the virtual power plant according to the basic operation and control strategy, including equipment operation cost, energy conversion efficiency loss, energy storage system maintenance cost, etc. For example, various costs under the basic operation and control strategy can be calculated by recording and analyzing various data and parameters in the actual operation process in detail, and the first operation and control cost can be summarized.

[0037] In this embodiment, the server starts to perform actual operation control of the virtual power plant according to the selected basic operation control strategy C. In this process, the server sends precise control instructions to each energy production and storage device.

[0038] For example, in the morning, solar energy output gradually increases. The server controls the solar farm to gradually increase the output power according to strategy C, while monitoring the status of the energy storage system. If the remaining capacity of the energy storage system is low, the server will reduce the output of the solar farm to avoid damage to the battery caused by overcharging. During the noon period, the load demand reaches its peak and the solar energy output is also at its maximum. The server will coordinate the gas turbine and hydroelectric power station to reduce the output, give priority to using solar power generation to meet the load, and store the excess solar power in the energy storage system.

[0039] During the entire operation and control process, the server will record various operating parameters and data in detail. For example, the operating time of each device, the change in output power, the number and depth of charge and discharge of the energy storage system, etc. These data will be used to calculate the operation and control costs later.

[0040] When calculating the first operation and control cost, the server considers multiple cost factors. The first is the operation and maintenance cost of the equipment. Since the server frequently adjusts the output power of the gas turbine and the hydroelectric power station according to strategy C, this may cause the key components of these equipment to wear out faster, requiring more frequent repairs and replacements, increasing maintenance costs. Assume that the maintenance cost of the gas turbine increases by 20 units and the maintenance cost of the hydroelectric power station increases by 15 units.

[0041] The second is the efficiency loss of energy conversion and transmission. In the process of transmission and conversion of electric energy, there will always be a certain amount of energy loss. According to the operation mode of strategy C, in order to quickly respond to load changes, electric energy needs to be converted and transmitted multiple times, resulting in increased efficiency loss. For example, due to frequent electric energy conversion, the energy waste caused by efficiency loss is equivalent to a cost of 10 units.

[0042] In addition, the use of energy storage systems also brings certain costs. Excessive charging and discharging will shorten the service life of the battery, and the battery needs to be replaced in advance. This part of the cost also needs to be calculated. Assume that due to the regulation of strategy C, the life of the energy storage system is shortened and the cost of replacing the battery increases by 18 units.

[0043] The server also considers some other indirect costs, such as the cost of upgrading and optimizing the control system in order to achieve precise control of strategy C, and the cost of governance due to increased environmental impact caused by changes in the operating status of the equipment. Assume that these indirect costs total 8 units.

[0044] After comprehensive calculation and summary, the server concluded that the first operation control cost corresponding to the basic operation control strategy C is 71 units.

[0045] Step S130, obtain multiple enabled operation control strategies corresponding to the collaborative operation control strategy, simulate the operation of the virtual power plant in this stage according to each enabled operation control strategy, generate simulated operation test results corresponding to each enabled operation control strategy, coordinately integrate each simulated operation test result to generate a collaborative operation test result, and generate a second operation control cost corresponding to the collaborative operation control strategy based on the collaborative operation test result.

[0046] In detail, the enabling operation control strategy refers to multiple control strategies specifically implemented under the collaborative operation control strategy. These enabling operation control strategies are tested for different collaborative scenarios and requirements through simulation operations to support the formulation of collaborative operation control strategies. For example, an enabling operation control strategy that matches the collaborative operation control strategy is selected from multiple template operation control strategies, and its effect is tested through simulation operations to evaluate its applicability and cost-effectiveness in different scenarios.

[0047] The simulation operation test results refer to a series of predicted data on the operation status and cost of the virtual power plant obtained by simulating the operation of different operation control strategies. For example, simulation software or algorithms can be used to simulate the operation status of the virtual power plant under different operation control strategies, record and analyze various operation parameters and cost data, and generate simulation operation test results.

[0048] Synergistic integration refers to the comprehensive analysis and processing of the simulation test results of each enabled operation control strategy to obtain the overall operation effect and cost under the coordinated operation control strategy. For example, the performance of different enabled operation control strategies in different aspects (such as economy, stability, environmental impact, etc.) can be comprehensively considered, and the simulation test results can be integrated through weighted average, optimization algorithm and other methods to obtain the coordinated operation test results.

[0049] The second operation and control cost refers to the cost incurred by operating and controlling the virtual power plant according to the collaborative operation control strategy, including energy transaction costs, collaborative planning costs, transmission losses, etc. For example, based on the collaborative operation test results, the various costs under the collaborative operation control strategy can be calculated and summarized to obtain the second operation and control cost.

[0050] In this embodiment, the server obtains multiple enabled operation control strategies related to the collaborative operation control strategy E. For example, the enabled operation control strategy F focuses on taking a more active pricing strategy in energy trading to obtain more economic benefits; the enabled operation control strategy G focuses more on long-term cooperation with surrounding virtual power plants to reduce common operating costs by sharing resources and technologies.

[0051] The server first simulates the operation of the virtual power plant in this phase according to the enabled operation control strategy F. During the simulation, the server assumes that under specific market conditions, the virtual power plant conducts energy transactions with surrounding virtual power plants. Due to the adoption of a more aggressive pricing strategy, the virtual power plant has obtained higher profits in the short term, but it may also cause dissatisfaction among surrounding partners and increase the uncertainty of future cooperation. The simulation test results show that although 15 units of economic benefits were obtained in this transaction, due to potential cooperation risks, an additional 8 units of cost may be required in the future to repair the relationship.

[0052] Next, the server simulated the operation based on the enabled operation control strategy G. Under this strategy, the virtual power plant established a deep cooperation mechanism with the surrounding virtual power plants, jointly invested in the construction of an efficient energy transmission line, and reduced transmission losses. The simulation results show that by sharing resources and technologies, the virtual power plant saves 12 units of cost in the long run, but the initial investment also reaches 6 units.

[0053] The server synergizes the simulation test results of each enabled operation control strategy. In this process, the server comprehensively considers the impact of different strategies in multiple aspects such as economy, technology, society and environment. For strategy F, although it has gained benefits in the short term, the long-term cooperation risks need to be carefully evaluated; for strategy G, although there is an initial investment, the long-term cost savings are significant. By weighing various factors, the server generates synergistic operation test results.

[0054] Based on the collaborative operation test results, the server starts to calculate the second operation control cost corresponding to the collaborative operation control strategy E. The server considers multiple aspects such as the direct costs and benefits of energy trading, the allocation of cooperative investment, and the quantification of potential risks. Assume that after detailed calculation, the second operation control cost corresponding to the collaborative operation control strategy E is 45 units.

[0055] Step S140: determining a target operation control strategy corresponding to the virtual power plant in this stage from the basic operation control strategy and the collaborative operation control strategy based on the first operation control cost and the second operation control cost.

[0056] The target operation control strategy refers to the control strategy that is most suitable for the operation of the virtual power plant at the current stage, selected based on the comparison result of the first operation control cost and the second operation control cost. For example, by comparing the cost difference and additional benefits of the basic operation control strategy and the collaborative operation control strategy, a strategy with lower cost or higher benefit is selected as the target operation control strategy.

[0057] In detail, in this embodiment, the server calculates that the first operation regulation cost corresponding to the basic operation control strategy C is 71 units, and the second operation regulation cost corresponding to the coordinated operation control strategy E is 45 units.

[0058] First, calculate the cost difference: 71-45=26 units.

[0059] Since the cost difference is a positive number, and assuming that the first threshold is 20 units, 26 is greater than 20, the server selects collaborative operation control strategy E as the target operation control strategy corresponding to the virtual power plant in this stage.

[0060] Assume another situation, the first operation control cost is 58 units, the second operation control cost is 50 units, and the cost difference is 8 units. Since 8 is less than the first threshold 20 units, the server needs to perform a cost-benefit analysis on the collaborative operation control strategy E to evaluate its additional benefit parameter value.

[0061] Through further analysis and calculation, the server evaluates the additional benefits of collaborative operation control strategy E in terms of improving energy supply reliability, strengthening cooperation with surrounding virtual power plants, and promoting regional energy balance. It is assumed that the additional benefit parameter value of collaborative operation control strategy E is 12 units.

[0062] The difference between the cost difference (8 units) and the additional benefit parameter value (12 units) is calculated, and the total cost difference is -4 units. Since the total cost difference is less than 0, the server selects the collaborative operation control strategy E as the target operation control strategy.

[0063] Therefore, the target operation control strategy that best suits the virtual power plant at this stage can be determined from the basic operation control strategy and the collaborative operation control strategy to achieve efficient, stable and economical operation of the virtual power plant.

[0064] Based on the above steps, the embodiment of the present application realizes efficient optimization and intelligent decision-making of the operation of the virtual power plant by integrating the backup operation control strategy (including the basic operation control strategy and the collaborative operation control strategy). Specifically, the backup strategy is first obtained according to the actual situation of the virtual power plant at the current stage, and then the simulation and evaluation of the basic operation control and the collaborative operation control are performed respectively. The first operation control cost of the basic strategy is generated by actual operation control, and the simulated operation test results of multiple enabled control strategies under the collaborative strategy are generated by simulated operation test, and then the collaborative operation test results and the corresponding second operation control cost are obtained through collaborative integration. Finally, by comparing the costs of the two strategies, the optimal target operation control strategy is determined. As a result, the flexibility and economy of the operation of the virtual power plant are significantly improved, and the operation strategy can be dynamically adjusted according to actual needs and changes in the external environment, effectively reducing the operation cost. At the same time, the introduction of the collaborative operation control strategy enhances the interaction ability of the virtual power plant with the surrounding power grid or other virtual power plants, promotes the optimal configuration and sharing of regional energy, and improves the overall energy utilization efficiency. In addition, by combining simulated operation tests with cost evaluation, a scientific basis is provided for decision-making, ensuring the effectiveness and rationality of the operation strategy, and providing a strong guarantee for the stable and efficient operation of the virtual power plant.

[0065] For example, in a possible implementation, step S140 includes:

[0066] Step S141, calculating the cost difference between the first operation regulation cost of the basic operation control strategy and the second operation regulation cost of the coordinated operation control strategy.

[0067] Step S142: If the cost difference is a positive number, and the difference between the cost difference and 0 is greater than a first threshold, the basic operation control strategy is selected as the target operation control strategy.

[0068] Step S143: if the cost difference is a negative number, and the difference between the cost difference and 0 is greater than a second threshold, the coordinated operation control strategy is used as the target operation control strategy.

[0069] Step S144, if the cost difference is a positive number, and the difference between the cost difference and 0 is not greater than a first threshold, and / or if the cost difference is a negative number, and the difference between the cost difference and 0 is not greater than a second threshold, then a cost-benefit analysis is performed on the collaborative operation control strategy to evaluate the additional benefit parameter value of the collaborative operation control strategy, and the difference between the cost difference and the additional benefit parameter value is calculated to generate a total cost difference.

[0070] Step S145: if the total cost difference is less than 0, the collaborative operation control strategy is selected as the target operation control strategy; if the total cost difference is greater than 0, the basic operation control strategy is selected as the target operation control strategy.

[0071] For example, in one example, a virtual power plant covers a variety of energy facilities, including wind power generation, solar power generation, hydropower generation, energy storage systems, and controllable loads. At the current stage, the server has calculated that the first operation control cost of the basic operation control strategy is 80 units, and the second operation control cost of the collaborative operation control strategy is 60 units.

[0072] The server first calculates the cost difference, which is 80-60=20 units. Since the cost difference is a positive number, the server then needs to determine the relationship between this difference and the first threshold. Assuming the first threshold is 15 units, since 20 is greater than 15, the server selects the basic operation control strategy as the target operation control strategy for the virtual power plant at this stage.

[0073] At another stage, the server calculates that the first operation control cost of the basic operation control strategy is 70 units, and the second operation control cost of the collaborative operation control strategy is 75 units. The cost difference is -5 units, which is a negative number. At this time, the server needs to determine the relationship between this difference and the second threshold. Assume that the second threshold is -8 units. Because -5 is greater than -8, the server uses the collaborative operation control strategy as the target operation control strategy.

[0074] In another case, the server obtains the first operation control cost of the basic operation control strategy as 78 units, and the second operation control cost of the collaborative operation control strategy as 72 units. The cost difference is 6 units, which is a positive number. Assuming that the first threshold is 10 units, because 6 is less than 10, the server cannot directly select the basic operation control strategy.

[0075] Therefore, the server conducts a cost-benefit analysis on the collaborative operation control strategy to evaluate its additional benefit parameter value. Assume that after detailed analysis and calculation, the server evaluates that the additional benefit parameter value brought by the collaborative operation control strategy in improving energy supply stability, promoting renewable energy consumption, and enhancing the synergy with surrounding power grids is 8 units.

[0076] Then, the server calculates the difference between the cost difference and the additional benefit parameter value, which is 6-8=-2 units. Since the total cost difference is -2 units, which is less than 0, the server selects the collaborative operation control strategy as the target operation control strategy.

[0077] For another example, the server calculates that the first operation control cost of the basic operation control strategy is 65 units, and the second operation control cost of the collaborative operation control strategy is 58 units. The cost difference is 7 units, which is a positive number. Assuming that the first threshold is 8 units, because 7 is less than 8, the server performs a cost-benefit analysis on the collaborative operation control strategy.

[0078] Assume that the additional benefit parameter value of the collaborative operation control strategy is evaluated to be 5 units, and the difference between the cost difference and the additional benefit parameter value is 7-5=2 units, which is greater than 0. Therefore, the server selects the basic operation control strategy as the target operation control strategy.

[0079] In actual situations, the server will continuously collect and analyze the operation data of the virtual power plant, including the output of different energy facilities, changes in load demand, fluctuations in market energy prices, etc. For example, in a certain period of time, due to good weather conditions, the output of wind and solar power generation exceeded expectations, and the load demand was relatively low. At this time, the basic operation control strategy may focus on storing excess electricity, but its storage cost is high. The collaborative operation control strategy may be to trade electricity with surrounding virtual power plants to obtain better economic benefits.

[0080] When calculating the operation control cost, the server will take into account various detailed factors such as the loss of storage devices, the loss of power transmission, and the handling fees during the transaction process. Assume that in this case, the first operation control cost of the basic operation control strategy is 90 units, and the second operation control cost of the collaborative operation control strategy is 80 units, with a cost difference of 10 units.

[0081] If the first threshold is set to 12 units, the server will evaluate the additional benefits of the collaborative operation control strategy because 10 is less than 12. Assume that the evaluation finds that the use of collaborative operation control strategy for power trading can not only obtain economic benefits at the current stage, but also strengthen the cooperative relationship with surrounding virtual power plants. This cooperative relationship may bring more preferential treatment and resource sharing in the future. The additional benefit parameter value is estimated to be 8 units.

[0082] The difference between the calculated cost difference and the additional benefit parameter value is 10-8=2 units, which is greater than 0, so the server finally selects the basic operation control strategy as the target operation control strategy.

[0083] In addition, assuming that during another special period, such as a major event held locally, the load demand increases sharply, the basic operation control strategy may need to start some spare high-cost power generation equipment to meet the demand. At this time, the first operation control cost of the basic operation control strategy may be as high as 120 units, while the collaborative operation control strategy coordinates resources through cooperation with multiple surrounding virtual power plants, and its second operation control cost is 100 units.

[0084] The cost difference is 20 units, and assuming that the first threshold is 18 units, because 20 is greater than 18, the server selects the basic operation control strategy as the target operation control strategy.

[0085] In short, the server will accurately calculate and compare the cost differences of different operation control strategies based on the real-time operation of the virtual power plant and various complex factors, and conduct in-depth cost-benefit analysis when necessary to determine the target operation control strategy that best suits the current stage, thereby achieving efficient, stable and economical operation of the virtual power plant.

[0086] In a possible implementation, step S110 includes:

[0087] From multiple template operation control strategies, a template operation control strategy with the lowest operation and regulation cost for the virtual power plant in the current stage is obtained as the basic operation control strategy corresponding to the virtual power plant in the current stage.

[0088] In this embodiment, the virtual power plant includes a variety of different types of energy facilities, such as large-scale land wind farms, rooftop solar power generation devices, small hydroelectric power stations, gas turbines, advanced energy storage systems, and a variety of controllable loads. This virtual power plant needs to provide electricity services for a wide area including cities, suburbs, and towns, while also responding to complex and changing energy environments and policy requirements.

[0089] The server first obtains multiple preset template operation control strategies.

[0090] Template operation control strategy A focuses on giving priority to wind and solar power generation, fully meeting load demand when their output is sufficient, and storing excess electricity in the energy storage system. However, due to the instability of wind and solar power, the energy storage system may be frequently activated, increasing the loss cost of the energy storage system. At the same time, when renewable energy is insufficient, it may cause instability in power supply, increasing the risk cost of power supply interruption.

[0091] Template operation control strategy B mainly relies on gas turbines and hydroelectric power stations to ensure stable power output, and the energy storage system is used as an auxiliary regulation. However, this method may increase the fuel consumption of gas turbines and bring higher fuel procurement costs. Moreover, the water resource utilization efficiency of hydroelectric power stations may not be high, resulting in the cost of wasting water resources.

[0092] Template operation control strategy C takes a balanced approach. It flexibly adjusts the operating status of various energy facilities based on the predicted output of renewable energy, real-time load demand changes, and the dynamic situation of the energy market. For example, when the output of renewable energy is high and the load demand is low, it appropriately stores electricity and reasonably controls the output of gas turbines and hydroelectric power stations; when the load is peak and renewable energy is insufficient, it optimizes the startup of gas turbines and hydroelectric power stations, while ensuring the efficient charging and discharging of the energy storage system to minimize the overall operation and regulation cost.

[0093] The server starts to calculate the operation and control cost of each template operation control strategy for the virtual power plant in this stage.

[0094] For Strategy A, server analysis found that due to the intermittent nature of wind and solar power, the energy storage system frequently performs deep charging and discharging, which increases the maintenance and replacement costs of the energy storage system. In addition, the instability of power supply may cause dissatisfaction among some users who have high requirements for power quality, resulting in the cost of reduced user satisfaction. Comprehensively evaluating these costs, Strategy A has a higher cost of operation and regulation.

[0095] For Strategy B, although it can provide relatively stable power output, the high fuel consumption of gas turbines brings high costs, and the waste of water resources also increases the cost of environment and resources. Overall, the operation and control cost of Strategy B is not optimistic.

[0096] For Strategy C, the server fully considered various factors through sophisticated simulation and calculation. In terms of energy output forecasting, it combined advanced meteorological data and energy forecasting models to improve forecast accuracy and reduce the cost of scheduling errors caused by forecast deviations. In terms of load demand response, detailed power consumption data of each region is obtained in real time, and precise regulation is carried out to reduce the cost of overpowering or insufficient power supply. At the same time, in terms of equipment operation management, the start and stop strategies of various types of equipment are optimized to reduce the risk cost of equipment wear and failure. After comprehensive consideration, the operation and regulation cost of Strategy C is relatively minimal.

[0097] After comprehensive, in-depth and detailed evaluation and comparison, the server determines that template operation control strategy C is the basic operation control strategy corresponding to the virtual power plant in this stage, in order to guide the subsequent operation and regulation of the virtual power plant and achieve the operation goals of efficiency, stability and minimum cost.

[0098] In a possible implementation, step S130 may include:

[0099] Step S131, from each template operation control strategy, according to the linkage operation control strategy corresponding to the linkage virtual power plant of the virtual power plant in the current stage, obtain the template operation control strategy associated with the basic operation control strategy as the first related operation control strategy. The linkage operation control strategy is a template operation control strategy with the minimum operation and regulation cost for the linkage virtual power plant.

[0100] Step S132, obtaining the focus operation control strategy of the preset dimension as the second relevant operation control strategy, and generating the relevant operation control strategy sequence corresponding to the virtual power plant in this stage according to the second relevant operation control strategy and each first relevant operation control strategy.

[0101] Step S133 , obtaining a plurality of related operation control strategies from the related operation control strategy sequence in descending order of relevance to the basic operation control strategy as the enabled operation control strategies corresponding to the coordinated operation control strategy.

[0102] In this embodiment, it is assumed that a virtual power plant VP1 is linked to another virtual power plant VP2. VP1 includes a variety of energy facilities, such as large wind power generation facilities, solar panel arrays, energy storage systems, and controllable loads.

[0103] The server first determines the linkage operation control strategy of VP2. VP2 also has multiple energy combinations and operation modes. After a series of analysis and calculations, the linkage operation control strategy with the lowest operation and regulation cost for VP2 is determined.

[0104] Based on the linkage operation control policy of VP2, the server obtains the template operation control policy associated with the basic operation control policy of VP1 from various preset template operation control policies, and uses it as the first related operation control policy.

[0105] For example, the basic operation control strategy is to give priority to the use of wind energy when there is sufficient wind energy, and to reasonably allocate the energy storage system. Then the first related operation control strategy associated with it may be to output a certain amount of electricity to VP2 when there is surplus wind energy output; or when VP2 is short of electricity, to allocate electricity from VP1's energy storage system to VP2 first.

[0106] The server also obtains the preset dimension of the focus operation control strategy as the second related operation control strategy. These preset dimensions may include maximizing energy utilization efficiency, minimizing environmental impact, etc. For example, a preset dimension of the focus operation control strategy is to minimize the use of the energy storage system to extend its life under the premise of meeting the power supply.

[0107] Next, the server generates a sequence of relevant operation control strategies corresponding to VP1 based on the second relevant operation control strategy and each of the first relevant operation control strategies. This sequence will comprehensively consider various factors, such as the complementarity and synergy between different strategies.

[0108] After the relevant operation control strategy sequence is generated, the server obtains multiple relevant operation control strategies from the sequence according to the descending order of relevance to the basic operation control strategy, and respectively serves as the enabled operation control strategies corresponding to the collaborative operation control strategy.

[0109] For example, an enabled operation control strategy that is highly correlated with the basic operation control strategy may be to dynamically adjust the transmission volume and price of electric energy according to the load demand of VP2 and the energy output of VP1 during a specific time period; an enabled operation control strategy with a slightly lower correlation may be to jointly formulate emergency plans with VP2 during special periods such as holidays to ensure the stability of power supply.

[0110] In this way, the server obtains a series of targeted and coordinated activation and operation control strategies for VP1, providing strong support for the efficient collaborative operation between virtual power plants.

[0111] In a possible implementation, step S130 further includes:

[0112] Step S134, obtaining the reconstruction operation test result corresponding to the linked virtual power plant of the virtual power plant in this stage.

[0113] Step S135, generating a simulation operation test result corresponding to the operation control strategy enabled in this stage from the reconstructed operation test result according to the reconstructed operation node state parameter corresponding to the operation node matching the simulation operation task corresponding to the operation control strategy enabled in this stage.

[0114] In this embodiment, it is continued to be assumed that the virtual power plant VP1 has a linkage relationship with another virtual power plant VP2.

[0115] The server first obtains the reconstruction operation test results corresponding to VP2. The reconstruction operation test results of VP2 contain a series of detailed data and information, such as energy output, load demand, power transmission, equipment operation status, etc. in different time periods.

[0116] Next, the server generates simulation operation test results according to the operation control strategy enabled in the current stage.

[0117] Assume that the currently enabled operation control strategy is to transfer the excess power of VP1 to VP2 at a specific price when the energy output of VP1 is at its peak and the load demand of VP2 is at its low point. The server extracts the reconstructed operation node state parameters corresponding to the operation node matching this simulation operation task from the reconstructed operation test results of VP2.

[0118] These parameters may include the original load demand data of VP2 during the time period, the state of electric energy storage, the equipment operation efficiency, etc. By analyzing and calculating these parameters, the server generates the simulation operation test results corresponding to the currently enabled operation control strategy.

[0119] For example, the server found that VP2's original load demand in this time period was 800 MW, the power storage had reached 80%, and the equipment operating efficiency was 85%. After executing the enabled operation control strategy, it is expected that VP2's power storage will rise to 90%, and the equipment operating efficiency will remain unchanged, but due to receiving the power from VP1, its subsequent power supply stability during peak loads will be improved.

[0120] For example, another operation control strategy is that when VP2 has equipment failure and causes a significant drop in energy output, VP1 increases the power transmission to VP2 and adjusts its own load distribution. The server obtains the specific operating parameters of VP2's equipment failure from the reconstruction operation test results of VP2, such as the type of faulty equipment, the scope of impact, and the estimated repair time, and then generates the simulation operation test results corresponding to this operation control strategy based on the current status of VP1. The results show that after the adjustment of VP1's operation, although its own energy storage consumption increased by a certain percentage, it successfully guaranteed the basic power demand of VP2, and the stability of the overall system was not significantly affected.

[0121] In this way, accurate and practical simulation operation test results can be generated for each enabled operation control strategy, providing strong support for subsequent operation control strategy selection and optimization.

[0122] In a possible implementation, step S130 may further include:

[0123] Step S136, based on the state parameter deviation between the virtual power plant in this stage and the associated operation nodes in the collaborative operation test result, generate the operation cost corresponding to each group of associated operation nodes. The operation cost and the corresponding state parameter deviation are positively correlated.

[0124] Step S137, accumulating various operation costs to generate a global operation cost corresponding to the collaborative operation control strategy.

[0125] Step S138: generating a second operation regulation cost corresponding to the collaborative operation control strategy according to the global operation cost.

[0126] In this embodiment, the server obtains the collaborative operation test result, which includes the state parameters of multiple associated operation nodes between VP1 and VP2.

[0127] For example, one of the associated operation nodes is the transmission efficiency of power transmission from VP1 to VP2. Under ideal conditions, the expected transmission efficiency should be 95%, but the collaborative operation test results show that the actual transmission efficiency is 90%. This state parameter deviation will result in a certain operation cost. Since the transmission efficiency is lower than expected, it may lead to increased loss of power during transmission, increased frequency of repair and maintenance of transmission lines, etc. The server calculates the operation cost corresponding to this group of associated operation nodes based on this deviation.

[0128] Another related operation node is the saturation of the energy storage system after VP2 receives the power from VP1. Ideally, the saturation of the energy storage system should be controlled within 80% to ensure safety and efficiency, but the test results show that it reached 85%. This deviation may increase the safety risk of the energy storage system and require more monitoring and protection measures. The server calculates the corresponding operation cost based on this.

[0129] In this way, the server analyzes the state parameter deviations between the associated running nodes and calculates the corresponding running costs for each group of associated running nodes. These running costs are positively correlated with the state parameter deviations. The larger the deviation, the higher the running cost.

[0130] Then, the server accumulates the various operating costs. Assume that the operating cost corresponding to the above transmission efficiency deviation is 10 units, the operating cost corresponding to the energy storage system saturation deviation is 8 units, and the operating costs of several other related operating nodes are 5 units, 12 units, and 6 units respectively. Adding up these operating costs, we get the global operating cost corresponding to the collaborative operation control strategy, which is 10+8+5+12+6=41 units.

[0131] Finally, the server generates the second operation control cost corresponding to the collaborative operation control strategy based on the global operation cost. For example, the server may add a certain management and coordination cost to the global operation cost. Assuming that the management and coordination cost is 5 units, the second operation control cost is 41+5=46 units.

[0132] This design can accurately obtain the second operation control cost corresponding to the collaborative operation control strategy, providing an important basis for selecting the optimal operation control strategy.

[0133] In a possible implementation, the method further includes:

[0134] Step A110, controlling and operating the virtual power plant at this stage according to the target operation control strategy, and generating basic operation plan data corresponding to the virtual power plant at this stage.

[0135] Step A120, when the target operation control strategy is the basic operation control strategy, and the basic operation control strategy is the focus operation control strategy of a preset dimension, the target operation plan data corresponding to the virtual power plant in this stage is generated based on the first target feature label and the basic operation plan data.

[0136] Step A130, when the target operation control strategy is not the focus operation control strategy of the preset dimension, obtain a strategy label set, and generate the target operation plan data corresponding to the virtual power plant in this stage based on the second target feature label, the strategy label set and the basic operation plan data.

[0137] The first target feature tag represents that the basic operation control strategy is a focus operation control strategy of a preset dimension, the second target feature tag represents that the basic operation control strategy is not a focus operation control strategy of a preset dimension, and the strategy tag set includes a related strategy tag representing that a related operation control strategy in a related operation control strategy sequence is adopted, and a collaborative strategy tag representing that a collaborative operation control strategy is adopted. The related operation control strategy sequence is used to determine the multiple enabled operation control strategies.

[0138] In this embodiment, assuming a virtual power plant VP, the server determines the target operation control strategy.

[0139] The server regulates the operation of the virtual power plant in this stage according to the target operation control strategy. For example, if the target operation control strategy requires the priority use of wind power generation in a specific time period and reasonable allocation according to the status of the energy storage system, the server will send corresponding instructions to each device to control the output power of the wind power generation equipment, the charging and discharging of the energy storage system, and other operations. In this process, the server will collect and record a large amount of operation data, such as the operating time of each device, the change of output power, the status of the energy storage system, etc., so as to generate the basic operation plan data corresponding to the virtual power plant in this stage.

[0140] If the target operation control strategy is the basic operation control strategy, and this basic operation control strategy is a focus operation control strategy of the preset dimension, for example, this strategy pays special attention to the efficient use of energy and energy conservation and emission reduction. The server will further generate the target operation plan data based on the first target feature tag and the generated basic operation plan data. For example, the first target feature tag indicates that the focus of this strategy is to reduce carbon emissions. The server will further optimize the plan based on the data on various energy usage and emissions in the basic operation plan data, which may increase the proportion of clean energy use, or adjust the equipment operation time to reduce carbon emissions during peak hours.

[0141] If the target operation control strategy is not the focus operation control strategy of the preset dimension, the server will obtain a set of policy tags. Assume that the policy tag set contains relevant policy tags that characterize the adoption of a strategy in the relevant operation control strategy sequence, and collaborative policy tags that characterize the adoption of collaborative operation control strategies. The server generates target operation plan data based on the second target feature tag, the policy tag set, and the basic operation plan data. For example, the second target feature tag indicates that the current strategy focuses on reducing costs. The server will adjust the plan based on the details of each cost in the basic operation plan data and the cost optimization information involved in the relevant strategies in the policy tag set. This may reduce the use time of some high-cost equipment, or increase energy transactions with other virtual power plants to reduce overall costs.

[0142] In this way, the target operation plan data that best suits the current virtual power plant operation can be generated according to different situations to achieve efficient, economical and sustainable operation.

[0143] In a possible implementation, step A130 includes:

[0144] Step A131, when the target operation control strategy is the collaborative operation control strategy, obtain the collaborative strategy label from the strategy label set, and generate the target operation plan data corresponding to the virtual power plant in this stage based on the second target feature label, the collaborative strategy label and the basic operation plan data.

[0145] Step A132, when the target operation control strategy is the basic operation control strategy, if the basic operation control strategy belongs to the related operation control strategy sequence, then obtain the related strategy label matching the basic operation control strategy from the strategy label set as the first strategy feature label, and generate the target operation plan data corresponding to the virtual power plant in this stage based on the second target feature label, the first strategy feature label and the basic operation plan data.

[0146] Step A133, when the target operation control strategy is the basic operation control strategy, if the basic operation control strategy does not belong to the relevant operation control strategy sequence, the other operation control strategies except the relevant operation control strategy sequence and the focus operation control strategy of the preset dimension are rearranged according to the strategy coding serial number, and the second strategy feature label is determined according to the strategy coding serial number obtained after the rearrangement of the basic operation control strategy, and the target operation plan data corresponding to the virtual power plant in this stage is generated according to the second target feature label, the second strategy feature label and the basic operation plan data.

[0147] In this embodiment, first, the server has determined the target operation control strategy of the virtual power plant in this phase. Assume that the target operation control strategy is a collaborative operation control strategy.

[0148] The server obtains the collaborative strategy tag from the strategy tag set. For example, the collaborative strategy tag may be "Regional Energy Collaborative Optimization-001". At the same time, the server has obtained the second target feature tag, such as "Peak load period-energy supply stability priority", as well as the basic operation plan data, which includes the basic operating parameters of various equipment, historical data of energy output and consumption, load forecasts for different regions, etc.

[0149] The server generates target operation plan data based on this information. For example, during peak load periods, in order to ensure the stability of energy supply, the collaborative strategy may require the virtual power plant to strengthen energy transactions with other virtual power plants in the vicinity. When the energy output of the power plant is insufficient, a certain amount of electricity is purchased from adjacent power plants. At the same time, according to the energy surplus of other power plants, the operating status of some equipment in the power plant is reasonably adjusted, such as reducing the output power of gas turbines, to reduce energy consumption and costs.

[0150] It is assumed that the target operation control strategy is a basic operation control strategy, and the basic operation control strategy belongs to a related operation control strategy sequence.

[0151] The server obtains the relevant policy tags matching the basic operation control strategy from the policy tag set as the first policy feature tag. For example, the first policy feature tag is "Renewable energy priority allocation-002". The second target feature tag is "Off-peak load period-cost saving priority". The basic operation plan data includes the conventional operating parameters of various equipment during the off-peak load period, the remaining capacity of the energy storage system, etc.

[0152] The server generates target operation plan data based on these data. During off-peak load periods, due to the low load demand, in order to save costs, the basic operation control strategy may give priority to using renewable energy to meet the load demand and store excess electricity in the energy storage system. At the same time, the operating power of gas turbines and hydropower stations is appropriately reduced to reduce equipment wear and energy consumption.

[0153] It is assumed that the target operation control strategy is a basic operation control strategy, but the basic operation control strategy does not belong to the relevant operation control strategy sequence.

[0154] The server reorders the operation control strategies except the relevant operation control strategy sequence and the focus operation control strategy of the preset dimension according to the strategy coding sequence number. For example, the original coding sequence number of the basic operation control strategy is "005", which becomes "010" after reordering.

[0155] The server determines the second strategy feature label based on the rearranged strategy coding sequence, such as "independent stable operation-010". The second target feature label is set as "extreme weather conditions-power supply reliability priority". The basic operation plan data includes the possible output forecast of various energy equipment under extreme weather conditions, the anti-interference capability parameters of the equipment, etc.

[0156] The server generates target operation plan data accordingly. In extreme weather conditions, in order to ensure the reliability of power supply, the basic operation control strategy may start backup power generation equipment, such as increasing the number of gas turbines in operation or increasing their output power, while strengthening the monitoring and management of the energy storage system to ensure that the load demand can be stably met when the output of renewable energy drops significantly.

[0157] In another scenario, assuming that the virtual power plant is in a period of rapid growth in electricity demand, the second target feature label is “demand growth period - energy supply expansion priority”.

[0158] If the target operation control strategy is a collaborative operation control strategy, the collaborative strategy label may be "Cross-regional energy cooperation expansion-003". The target operation scenario data generated by the server may include establishing a closer energy cooperation relationship with virtual power plants in other regions, jointly investing in the construction of new power generation facilities, or sharing energy storage equipment to meet the growing energy demand.

[0159] If the target operation control strategy is a basic operation control strategy and belongs to a related operation control strategy sequence, the first strategy feature label may be "Internal Equipment Upgrade and Optimization-004". The generated target operation plan data may involve technical upgrades to existing power generation equipment to improve its power generation efficiency and optimize the energy distribution system to more efficiently utilize internal resources to meet growing demand.

[0160] If the target operation control strategy is a basic operation control strategy and does not belong to the relevant operation control strategy sequence, the second strategy characteristic label is, for example, "New Energy Facility Planning-011". The generated target operation plan data may include planning and building new wind farms or solar farms to increase the total energy output capacity of the virtual power plant.

[0161] Consider another scenario where the energy policy in the region where the virtual power plant is located has changed, encouraging more use of clean energy and providing corresponding subsidies. The second objective feature label at this time is "policy adaptation-maximization of clean energy utilization".

[0162] When the target operation control strategy is a collaborative operation control strategy, the collaborative strategy label may be "Clean Energy Collaborative Promotion-005". The target operation plan data may be to jointly formulate a clean energy promotion plan with surrounding virtual power plants and exchange technologies and experiences in the use of clean energy.

[0163] When the target operation control strategy is a basic operation control strategy belonging to a related operation control strategy sequence, the first strategy feature label may be "internal clean energy scheduling optimization-006". The generated target operation plan data may be to adjust the power generation priority of internal clean energy and optimize the storage strategy of the energy storage system for clean energy.

[0164] When the target operation control strategy is a base operation control strategy that does not belong to the sequence of related operation control strategies, the second strategy characteristic label may be "clean energy equipment acquisition plan-012". The generated target operation plan data may be a plan to purchase new clean energy equipment, such as more efficient solar panels or advanced wind turbines.

[0165] In short, the server will comprehensively consider the second target feature label, strategy label and basic operation plan data according to different situations, and generate the target operation plan data that best suits the current stage and conditions for the virtual power plant, so as to achieve efficient, stable and economical operation of the virtual power plant.

[0166] In a possible implementation, the relevant operation control strategy sequence includes various relevant operation control strategies arranged in sequence, and the strategy tag set includes relevant strategy tags corresponding to the sequential coding numbers in the relevant operation control strategy sequence.

[0167] Step A132 includes: obtaining, from the policy tag set, a relevant policy tag corresponding to the sequential coding number of the basic operation control strategy in the relevant operation control strategy sequence as a second policy feature tag.

[0168] In this embodiment, after a series of analysis and screening, a relevant operation control strategy sequence is determined, and the relevant operation control strategy sequence is sorted according to specific logic and priority.

[0169] For example, the relevant operation control strategy sequence is:

[0170] 1. "Prioritize the use of renewable energy and balance energy storage-001"

[0171] 2. "Flexibly deploy gas turbines according to load demand-002"

[0172] 3. "Optimizing Hydroelectric Power Station Output and Energy Storage-003"

[0173] The policy tag set includes relevant policy tags corresponding to the above sequence coding numbers:

[0174] 1. "Renewable Energy Optimization-001"

[0175] 2. "Gas Turbine Flexible Deployment-002"

[0176] 3. "Hydropower Generation and Energy Storage Optimization-003"

[0177] Assume that the currently determined basic operation control strategy is "flexibly deploying gas turbines according to load demand", and its sequence coding number in the relevant operation control strategy sequence is 2.

[0178] The server obtains the relevant policy tag "Gas Turbine Flexible Allocation-002" corresponding to the sequence code number 2 from the policy tag set, and uses it as the first policy feature tag.

[0179] In a specific scenario, for example, the current virtual power plant is facing a peak load during the noon period. The basic operation control strategy "flexibly deploying gas turbines according to load demand" is determined as an applicable strategy. After the server obtains the corresponding first strategy feature label "Flexible deployment of gas turbines-002", it generates a specific operation plan based on this label and other relevant information (such as current energy output data, load demand data, etc.).

[0180] A possible solution is to gradually increase the output power of the gas turbine from 50% to 80% between noon and 1 p.m. to meet the sharply increased load demand. At the same time, monitor the status of the energy storage system. If the remaining capacity of the energy storage system is sufficient, appropriately reduce the increase to save fuel consumption and equipment wear of the gas turbine.

[0181] For example, in another scenario, weather changes occurred in the area where the virtual power plant was located, and the output of renewable energy was affected. Since the basic operation control strategy is "flexibly deploying gas turbines according to load demand", after the server obtains the corresponding first strategy feature tag, the operation plan formulated may be: when the output of renewable energy is 30% lower than expected, immediately increase the output power of the gas turbine to 70%, and continuously monitor load changes, and conduct evaluation and adjustments every 15 minutes to ensure the stability of power supply.

[0182] For example, during holidays, load demand shows different patterns from weekdays. The basic operation control strategy remains unchanged, and the solution generated by the server based on the corresponding first strategy feature label may be: predict the peak load period of holidays in advance, increase the output power of the gas turbine to 60% one hour before the peak, and gradually adjust the output power by 5% according to the actual load during the peak period until the load demand is met without causing energy waste.

[0183] In one possible implementation, the method includes:

[0184] Step B110, obtaining the target operation plan data corresponding to the virtual power plant in this stage, and obtaining the target operation control strategy corresponding to the target operation plan data.

[0185] Step B120: When the target operation control strategy is a coordinated operation control strategy, a plurality of enabled operation control strategies corresponding to the coordinated operation control strategy are obtained.

[0186] Step B130, perform simulation operations respectively according to each enabled operation control strategy, generate simulation operation test results corresponding to each enabled operation control strategy, coordinate and integrate each simulation operation test result to generate a coordinated operation test result, analyze the target operation plan data according to the coordinated operation test result, and generate the operation plan data of this stage corresponding to the virtual power plant of this stage.

[0187] In this embodiment, the server first obtains the target operation plan data corresponding to the virtual power plant in this stage. For example, the target operation plan data may include arranging the operating power of various energy devices and the charging and discharging strategy of the energy storage system according to weather and load forecasts within a specific time period.

[0188] Then, the server obtains the target operation control strategy corresponding to the target operation scheme data, assuming that the target operation control strategy is determined to be a collaborative operation control strategy.

[0189] When the target operation control strategy is a collaborative operation control strategy, the server obtains multiple enabled operation control strategies corresponding to the collaborative operation control strategy. For example, the enabled operation control strategy may include a strategy for energy trading with surrounding virtual power plants when there is excess energy, a strategy for sharing energy storage facilities with other power plants, etc.

[0190] The server performs simulation operations according to each enabled operation control strategy. For example, for the energy trading strategy, the server simulates the process of energy trading with surrounding virtual power plants during periods of energy surplus, including the setting of trading prices, the determination of trading electricity, etc., and generates corresponding simulation operation test results, such as the economic benefits obtained after a successful transaction, the impact on the energy balance of the power plant, etc. For the shared energy storage facility strategy, the server simulates the energy storage allocation, charging and discharging coordination, etc. during the sharing process, and generates corresponding simulation operation test results, such as the improvement of the utilization efficiency of energy storage facilities, changes in maintenance costs, etc.

[0191] Next, the server will coordinate and integrate the results of various simulation operations. For example, it will comprehensively consider the economic benefits brought by the energy trading strategy and the improvement in equipment utilization efficiency brought by the shared energy storage facility strategy, and at the same time evaluate their possible comprehensive impact on the operation stability and cost of the power plant to generate coordinated operation test results.

[0192] Based on the collaborative operation test results, the server analyzes the target operation plan data. Assume that the collaborative operation test results show that the energy trading strategy has significant benefits under certain conditions, but there are certain challenges to operational stability, while the shared energy storage facility strategy can effectively improve equipment efficiency and has good stability. Based on this, the server adjusts and optimizes the target operation plan data to generate the current stage operation plan data corresponding to the virtual power plant at this stage.

[0193] In specific scenarios, for example, before the peak electricity consumption period in summer, the target operation plan data was originally planned to rely mainly on its own power generation equipment and energy storage system to meet the load demand. However, after the collaborative operation control strategy is determined, after simulation operation and collaborative integration, the operation plan data generated by the server at this stage may be adjusted to sell part of the excess electricity to the surrounding virtual power plants at a preferential price during the trough period before the peak electricity consumption, and obtain certain support electricity from the surrounding power plants during the peak period, and coordinate the use of energy storage systems with the surrounding power plants to more efficiently cope with the peak load and ensure the stability and economy of the power supply.

[0194] For example, in winter, due to the relative reduction in wind and solar power output, the target operation plan data may focus on starting gas turbines to ensure power supply. However, under the collaborative operation control strategy, through simulation operation and collaborative integration, the operation plan data at this stage may be changed to cooperate with nearby virtual power plants with abundant coal resources, increase the input of coal-fired power generation, and optimize the energy distribution and storage management of both parties to reduce the overall operating cost and improve energy efficiency.

[0195] In this way, the most optimized operation plan data for this stage can be generated according to the actual situation and coordination needs of the virtual power plant, ensuring the efficient and stable operation of the virtual power plant.

[0196] In a possible implementation, step B110 includes:

[0197] Step B111, when the target operation scheme data includes a collaborative strategy tag, determining that the target operation control strategy is the collaborative operation control strategy.

[0198] Step B112, when the target operation plan data does not include a collaborative strategy tag, determine that the target operation control strategy is the basic operation control strategy corresponding to the virtual power plant in this stage.

[0199] In a possible implementation, step B112 includes:

[0200] Step B1121, when the target operation scheme data includes a first target feature tag, determining that the basic operation control strategy is a focus operation control strategy of a preset dimension.

[0201] Step B1122, when the target operation plan data includes a first strategy feature tag, determine the relevant operation control strategy sequence corresponding to the target operation plan data based on the linkage operation control strategy corresponding to the linkage operation plan data of the target operation plan data, and determine the basic operation control strategy as the relevant operation control strategy in the relevant operation control strategy sequence that matches the first strategy feature tag.

[0202] Step B1123, when the target operation plan data includes a second strategy characteristic label, the other operation control strategies except the relevant operation control strategy sequence and the focus operation control strategy of the preset dimension are rearranged according to the strategy coding number, and from the various strategy coding numbers generated by the rearrangement, the strategy coding number matching the second strategy characteristic label is used as the target coding number, and the basic operation control strategy is determined to be the operation control strategy corresponding to the target coding number.

[0203] In this embodiment, the server obtains target operation plan data, for example, the target operation plan data includes information such as the estimated output of various energy equipment, the forecast of load demand, and the operation status of the equipment.

[0204] If the target operation plan data includes a collaborative strategy tag, such as "energy mutual trading strategy with surrounding virtual power plants-001", the server determines that the target operation control strategy is a collaborative operation control strategy.

[0205] If the target operation plan data does not include a collaborative strategy tag, the server will perform further analysis.

[0206] If the target operation plan data includes the first target characteristic tag, such as "ensuring the stability of energy supply", the server determines the basic operation control strategy as the focus operation control strategy of the preset dimension, which may be "prioritize the startup of stable energy supply equipment-002".

[0207] Assume that the target operation plan data includes a first strategy feature tag, such as "Optimize energy output and load matching strategy-003". The server determines the relevant operation control strategy sequence corresponding to the target operation plan data based on the linkage operation control strategy corresponding to the linkage operation plan data of the target operation plan data, such as "Strategy to cope with peak load together with adjacent virtual power plants-004". This sequence may include "Flexible allocation of energy equipment output strategy-005", "Energy storage strategy based on load demand-006", etc. Then, the server determines the basic operation control strategy as the relevant operation control strategy in the relevant operation control strategy sequence that matches the first strategy feature tag, assuming it is "Flexible allocation of energy equipment output strategy-005".

[0208] If the target operation plan data includes a second strategy feature tag, such as "Strategy for dealing with sudden energy shortages-007". The server will re-arrange the other operation control strategies except for the relevant operation control strategy sequence and the preset dimension's focus operation control strategy according to the strategy coding sequence number. After re-arranging and generating new strategy coding sequences, the server finds the strategy coding sequence number that matches the second strategy feature tag as the target coding sequence number. Assuming that the target coding sequence number is "Emergency start-up backup energy equipment strategy-008", the server determines that the basic operation control strategy is the operation control strategy corresponding to the target coding sequence number.

[0209] In a specific scenario, for example, in spring, the industrial load demand in the area where the virtual power plant is located gradually increases. The target operation plan data does not have a collaborative strategy tag, but contains the first target feature tag "ensure energy supply stability". Based on this, the server determines the basic operation control strategy as "prioritize the start of stable energy supply equipment-002", which may mean giving priority to increasing the output power of hydropower and gas turbines to stably meet the demand for load growth.

[0210] For example, during the peak electricity consumption period in summer, the target operation plan data includes the first strategy feature label "Optimize energy output and load matching strategy-003", and there is also linkage operation plan data for coping with peak load with adjacent virtual power plants. The server determines the relevant operation control strategy sequence and selects "Flexible allocation of energy equipment output strategy-005" as the basic operation control strategy. It may dynamically adjust the output power of various energy equipment according to the real-time energy output and load conditions.

[0211] For example, when extreme weather in winter causes a sudden energy shortage, the target operation plan data contains the second strategy feature label "Strategy for dealing with sudden energy shortages-007". The server re-arranges other operation control strategies and determines "Emergency start-up backup energy equipment strategy-008" as the basic operation control strategy to quickly start the backup power generation equipment to ensure power supply.

[0212] Therefore, through detailed analysis of the target operation plan data, the target operation control strategy suitable for the current operating conditions of the virtual power plant can be accurately determined.

[0213] Further, Figure 2 FIG. 1 is a schematic diagram of the hardware structure of a virtual power plant operation control system 100 for implementing the method provided in the embodiment of the present application. Figure 2 As shown, the virtual power plant operation control system 100 includes a memory 111, a storage controller 112, a processor 113, a peripheral interface 114, an input and output unit 115, an audio unit 116, a display unit 117 and a radio frequency unit 118.

[0214] The memory 111, the storage controller 112, the processor 113, the peripheral interface 114, the input / output unit 115, the audio unit 116, the display unit 117, and the radio frequency unit 118 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines.

[0215] The memory 111 may be, but not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electric erasable programmable read-only memory (EEPROM), etc. The memory 111 is used to store the application 210, and the processor 113 executes the application 210 after receiving the execution instruction. The processor 113 and other possible components may access the memory 111 under the control of the storage controller 112.

[0216] The processor 113 may be an integrated circuit chip with signal processing capabilities. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present invention may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0217] The peripheral interface 114 couples various input / output devices to the processor 113 and the memory 111. In some embodiments, the peripheral interface 114, the processor 113 and the memory controller 112 can be implemented in a single chip. In other embodiments, they can be implemented by separate chips.

[0218] The input-output unit 115 is used to provide input data to the user to implement the interaction between the user and the virtual power plant operation control system 100. The input-output unit 115 can be, but is not limited to, a mouse and a keyboard.

[0219] The audio unit 116 provides an audio interface to the user and may include one or more microphones, one or more speakers, and an audio circuit.

[0220] The display unit 117 provides an interactive interface (such as a user operation interface) between the virtual power plant operation control system 100 and the user or is used to display image data. In this embodiment, the display unit 117 can be a liquid crystal display or a touch display. If it is a touch display, it can be a capacitive touch screen or a resistive touch screen that supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations generated from one or more locations on the touch display, and the sensed touch operations are handed over to the processor for calculation and processing.

[0221] The radio frequency unit 118 is used to receive and send radio wave signals (such as electromagnetic waves) to achieve mutual conversion between radio waves and electrical signals, thereby realizing communication between the virtual power plant operation control system 100 and the network or other communication equipment.

[0222] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of the embodiments of the present application are described. Other embodiments are within the scope of the attached claims. In some cases, the actions or steps recorded in the claims can be performed according to an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0223] Each embodiment in the embodiments of the present application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the above different embodiments, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0224] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program. The above program may be stored in a computer-readable storage medium, and the above storage medium may be a read-only memory, a disk or an optical disk, etc.

Claims

1. A virtual power plant operation control method, characterized in that: The method comprises: Obtaining a standby operation control strategy corresponding to the virtual power plant at this stage; the standby operation control strategy includes a basic operation control strategy and a coordinated operation control strategy; According to the basic operation control strategy, the operation of the virtual power plant in this stage is regulated and controlled to generate a first operation regulation cost corresponding to the basic operation control strategy; Acquire multiple enabled operation control strategies corresponding to the collaborative operation control strategy, simulate the operation of the virtual power plant in this stage according to each enabled operation control strategy, generate simulated operation test results corresponding to each enabled operation control strategy, coordinately integrate each simulated operation test result to generate a collaborative operation test result, and generate a second operation regulation cost corresponding to the collaborative operation control strategy according to the collaborative operation test result; Determining the target operation control strategy corresponding to the virtual power plant in this stage from the basic operation control strategy and the collaborative operation control strategy according to the first operation regulation cost and the second operation regulation cost; The step of obtaining the standby operation control strategy corresponding to the virtual power plant at this stage includes: From a plurality of template operation control strategies, obtain a template operation control strategy with the minimum operation and regulation cost for the virtual power plant at the current stage as the basic operation control strategy corresponding to the virtual power plant at the current stage; The obtaining of a plurality of enabled operation control strategies corresponding to the coordinated operation control strategy includes: From each template operation control strategy, according to the linkage operation control strategy corresponding to the linkage virtual power plant of the virtual power plant in this stage, a template operation control strategy associated with the basic operation control strategy is obtained as the first related operation control strategy; the linkage operation control strategy is a template operation control strategy with the minimum operation regulation cost for the linkage virtual power plant; Acquire a preset dimension of interest operation control strategy as a second related operation control strategy, and generate a related operation control strategy sequence corresponding to the virtual power plant in this stage according to the second related operation control strategy and each first related operation control strategy; From the sequence of related operation control strategies, according to the descending order of the relevance to the basic operation control strategy, a plurality of related operation control strategies are obtained as the enabled operation control strategies corresponding to the coordinated operation control strategy; The virtual power plant of the current stage is simulated and operated respectively according to each enabled operation control strategy, and the simulated operation test results corresponding to each enabled operation control strategy are generated, including: Obtaining the reconstruction operation test results corresponding to the linkage virtual power plant of the virtual power plant in this stage; From the reconstructed operation test results, based on the reconstructed operation node state parameters corresponding to the operation nodes that match the simulated operation tasks corresponding to the operation control strategy enabled in this stage, generate the simulated operation test results corresponding to the operation control strategy enabled in this stage; Generating a second operation regulation cost corresponding to the collaborative operation control strategy according to the collaborative operation test result includes: According to the state parameter deviation between the virtual power plant in this stage and the associated operation nodes in the collaborative operation test result, the operation cost corresponding to each group of associated operation nodes is generated; the operation cost and the corresponding state parameter deviation are in a positive correlation relationship; Accumulating various operation costs to generate a global operation cost corresponding to the collaborative operation control strategy; A second operation regulation cost corresponding to the collaborative operation control strategy is generated according to the global operation cost.

2. The virtual power plant operation control method according to claim 1, characterized in that: The method further comprises: According to the target operation control strategy, the operation of the virtual power plant at this stage is regulated and controlled, and basic operation plan data corresponding to the virtual power plant at this stage is generated; When the target operation control strategy is the basic operation control strategy, and the basic operation control strategy is a focus operation control strategy of a preset dimension, the target operation plan data corresponding to the virtual power plant at this stage is generated according to the first target feature tag and the basic operation plan data; When the target operation control strategy is not the focus operation control strategy of the preset dimension, a strategy tag set is obtained, and the target operation plan data corresponding to the virtual power plant in this stage is generated according to the second target feature tag, the strategy tag set and the basic operation plan data; The first target feature tag represents that the basic operation control strategy is a focus operation control strategy of a preset dimension, the second target feature tag represents that the basic operation control strategy is not a focus operation control strategy of a preset dimension, and the strategy tag set includes a related strategy tag representing that a related operation control strategy in a related operation control strategy sequence is adopted, and a collaborative strategy tag representing that a collaborative operation control strategy is adopted; the related operation control strategy sequence is used to determine the multiple enabled operation control strategies; Wherein, the method comprises: Obtain target operation plan data corresponding to the virtual power plant in this stage, and obtain target operation control strategy corresponding to the target operation plan data; When the target operation control strategy is a coordinated operation control strategy, obtaining a plurality of enabled operation control strategies corresponding to the coordinated operation control strategy; Perform simulation operations according to each enabled operation control strategy, generate simulation operation test results corresponding to each enabled operation control strategy, coordinate and integrate each simulation operation test result to generate a coordinated operation test result, analyze the target operation plan data according to the coordinated operation test result, and generate the operation plan data of this stage corresponding to the virtual power plant of this stage; Wherein, the obtaining of the target operation control strategy corresponding to the target operation scheme data includes: When the target operation scheme data includes a collaborative strategy tag, determining that the target operation control strategy is the collaborative operation control strategy; When the target operation scheme data does not include a collaborative strategy tag, determining that the target operation control strategy is a basic operation control strategy corresponding to the virtual power plant at this stage; Wherein, when the target operation scheme data does not include a collaborative strategy tag, determining that the target operation control strategy is the basic operation control strategy corresponding to the virtual power plant at this stage includes: When the target operation scheme data includes a first target feature tag, determining that the basic operation control strategy is a focus operation control strategy of a preset dimension; When the target operation scheme data includes a first strategy feature tag, determining a related operation control strategy sequence corresponding to the target operation scheme data according to the linkage operation control strategy corresponding to the linkage operation scheme data of the target operation scheme data, and determining the basic operation control strategy as a related operation control strategy in the related operation control strategy sequence that matches the first strategy feature tag; When the target operation plan data includes a second strategy characteristic label, the other operation control strategies except the relevant operation control strategy sequence and the focus operation control strategy of the preset dimension are rearranged according to the strategy coding number, and from the various strategy coding numbers generated by the rearrangement, the strategy coding number matching the second strategy characteristic label is used as the target coding number, and the basic operation control strategy is determined to be the operation control strategy corresponding to the target coding number.

3. The virtual power plant operation control method according to claim 2, characterized in that: The generating, based on the second target feature tag, the strategy tag set and the basic operation plan data, the target operation plan data corresponding to the virtual power plant at this stage includes: When the target operation control strategy is the collaborative operation control strategy, the collaborative strategy tag is obtained from the strategy tag set, and the target operation plan data corresponding to the virtual power plant in this stage is generated according to the second target feature tag, the collaborative strategy tag and the basic operation plan data; When the target operation control strategy is the basic operation control strategy, if the basic operation control strategy belongs to the relevant operation control strategy sequence, a relevant strategy tag matching the basic operation control strategy is obtained from the strategy tag set as a first strategy feature tag, and the target operation plan data corresponding to the virtual power plant at this stage is generated according to the second target feature tag, the first strategy feature tag and the basic operation plan data; When the target operation control strategy is the basic operation control strategy, if the basic operation control strategy does not belong to the relevant operation control strategy sequence, the other operation control strategies except the relevant operation control strategy sequence and the focus operation control strategy of the preset dimension will be rearranged according to the strategy coding serial number, and the second strategy feature label will be determined according to the strategy coding serial number obtained after the rearrangement of the basic operation control strategy, and the target operation plan data corresponding to the virtual power plant in this stage will be generated according to the second target feature label, the second strategy feature label and the basic operation plan data.

4. The virtual power plant operation control method according to claim 3, characterized in that: The relevant operation control strategy sequence includes various relevant operation control strategies arranged in sequence, and the strategy tag set includes relevant strategy tags corresponding to the sequential coding numbers in the relevant operation control strategy sequence; The step of acquiring the relevant strategy tag matching the basic operation control strategy from the strategy tag set as the first strategy feature tag includes: From the strategy tag set, a relevant strategy tag corresponding to the sequential coding number of the basic operation control strategy in the relevant operation control strategy sequence is obtained as a second strategy feature tag.

5. A virtual power plant operation control system, characterized in that: The virtual power plant operation control system includes a processor and a machine-readable storage medium, in which machine-executable instructions are stored. The machine-executable instructions are loaded and executed by the processor to implement the virtual power plant operation control method described in any one of claims 1-4.

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