Virtual power plant dispatching system

Abstract

The invention provides a virtual power plant dispatching system. The virtual power plant scheduling system comprises: an integrated scheduling platform, which is adopted to perform unified management and scheduling on various distributed energy resources in a virtual power plant, and realizes real-time monitoring and coordinated scheduling on various resources through an integrated console; the integrated scheduling platform system processes and predicts historical data and real-time data by introducing an intelligent scheduling algorithm of artificial intelligence and through a machine learning and data analysis technology. According to the virtual power plant scheduling system provided by the invention, through an integrated scheduling platform, an intelligent scheduling algorithm, a real-time monitoring and feedback mechanism, multi-level decision support, an efficient communication network and a user-friendly operation interface, the scheduling precision, the response speed and the system stability of the virtual power plant can be remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power systems, and in particular relates to a virtual power plant dispatching system. Background Art

[0002] With the rapid development of renewable energy and the increasing complexity of the power market, traditional power dispatching methods face many challenges. The dispatching system of traditional power plants is mainly aimed at large centralized power generation facilities, while modern power systems are more decentralized. As an emerging power management method, virtual power plants use information technology and intelligent means to integrate and optimize the dispatching of decentralized distributed energy resources (such as wind power, photovoltaics, energy storage, etc.) to achieve efficient use of power resources.

[0003] However, the existing virtual power plant dispatching system still faces some problems in practical applications, such as insufficient dispatching accuracy, poor real-time response capability and poor system stability. Therefore, a more advanced and efficient virtual power plant dispatching system is needed to improve the accuracy of power dispatching and the overall operating efficiency of the system. Summary of the invention

[0004] The technical problem solved by the present invention is to provide a virtual power plant dispatching system which can significantly improve the dispatching accuracy, response speed and system stability of virtual power plants through an integrated dispatching platform, intelligent dispatching algorithm, real-time monitoring and feedback mechanism, multi-level decision support, efficient communication network and user-friendly operation interface.

[0005] In order to solve the above technical problems, the virtual power plant dispatching system provided by the present invention includes: an integrated dispatching platform, which can be used to uniformly manage and dispatch various distributed energy resources in the virtual power plant. The integrated dispatching platform system realizes real-time monitoring and coordinated dispatching of various resources through an integrated console;

[0006] The integrated dispatching platform system introduces an intelligent dispatching algorithm based on artificial intelligence, and processes and predicts historical data and real-time data through machine learning and data analysis technology, thereby optimizing the power dispatching plan;

[0007] The integrated dispatching platform system is equipped with a real-time monitoring module, which can monitor the operation status of the power system throughout the process, and then obtain the status information of various energy resources in real time through sensors and data acquisition technology installed in various energy resources and power grids, and transmit it to the central control platform. The real-time feedback mechanism can make instant adjustments to the dispatching plan according to the monitoring data, so as to cope with emergencies and system changes;

[0008] The integrated scheduling platform system has multi-level scheduling decision support functions, including short-term scheduling, medium-term scheduling and long-term planning. The short-term scheduling mainly focuses on real-time power demand and resource allocation, the medium-term scheduling focuses on optimization in daily operations, and the long-term planning involves future energy resource allocation and development trend forecasts. Therefore, through multi-level decision support, the integrated scheduling platform system can perform optimized scheduling on different time scales to ensure the efficient operation of the virtual power plant.

[0009] As a further solution of the present invention, the energy resources include but are not limited to photovoltaics, wind power, energy storage and loads, and the algorithm can automatically adjust the scheduling strategy according to changes in electricity demand and fluctuations in energy resources to improve energy utilization efficiency and power supply stability.

[0010] As a further solution of the present invention, the integrated scheduling platform system adopts efficient communication network technology, thereby ensuring fast data transmission and information exchange between various modules in the system. The integrated scheduling platform system uses low-latency communication protocols and data encryption technology, so the integrated scheduling platform system can ensure the timeliness and security of scheduling instructions and improve the response speed and reliability of the overall scheduling.

[0011] As a further solution of the present invention, the integrated dispatching platform system also includes an operation interface, through which users can conveniently view the operating status, dispatching plans and optimization suggestions of the power system in real time, and then can conveniently and timely perform convenient operations and adjustments, thereby greatly reducing the difficulty of operation and improving the usability of the system.

[0012] As a further solution of the present invention, the integrated dispatching platform realizes real-time monitoring and coordinated dispatching of various resources through an integrated console, and the platform can integrate power data, energy storage status and load demand from different types of power generation sources, thereby realizing unified dispatching management across devices and regions.

[0013] As a further solution of the present invention, the intelligent scheduling algorithm can automatically adjust the scheduling strategy according to changes in electricity demand, fluctuations in energy resources and power grid operation conditions to improve energy utilization efficiency and power supply stability.

[0014] As a further solution of the present invention, the core of the algorithm is the prediction model and the optimization model, which uses deep learning technology to predict power load and renewable energy power generation, and combines the optimization algorithm to formulate an optimal scheduling plan.

[0015] As a further solution of the present invention, the network architecture of the integrated scheduling platform adopts a distributed design, which reduces the risk of single point failure, supports high-concurrency data transmission requirements, and improves the response speed and reliability of the overall scheduling.

[0016] As a further solution of the present invention, the data collection includes but is not limited to power load, power generation, energy storage status and meteorological data. The collected data needs to be preprocessed, including data cleaning, normalization and missing value filling, so as to ensure the quality and accuracy of the data.

[0017] As a further solution of the present invention, feature engineering is required after the data preprocessing. The extracted features include time series features, meteorological impact features and load change patterns. The purpose of feature engineering is to convert complex data into a form that can be processed by a machine learning model to improve the performance of the prediction model.

[0018] Compared with related technologies, the virtual power plant dispatching system provided by the present invention has the following beneficial effects:

[0019] 1. The present invention can significantly improve the scheduling accuracy, response speed and system stability of virtual power plants through an integrated scheduling platform, intelligent scheduling algorithm, real-time monitoring and feedback mechanism, multi-level decision support, efficient communication network and user-friendly operation interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0021] Figure 1 It is a structural block diagram of the virtual power plant dispatching system of the present invention. DETAILED DESCRIPTION

[0022] Please refer to Figure 1 ,in, Figure 1 The virtual power plant dispatching system of the present invention is a structural block diagram. The virtual power plant dispatching system includes: an integrated dispatching platform, which can be used to uniformly manage and dispatch various distributed energy resources in the virtual power plant. The integrated dispatching platform system realizes real-time monitoring and coordinated dispatch of various resources through an integrated console;

[0023] The integrated dispatching platform system introduces an intelligent dispatching algorithm based on artificial intelligence, and processes and predicts historical data and real-time data through machine learning and data analysis technology, thereby optimizing the power dispatching plan;

[0024] The integrated dispatching platform system is equipped with a real-time monitoring module, which can monitor the operation status of the power system throughout the process, and then obtain the status information of various energy resources in real time through sensors and data acquisition technology installed in various energy resources and power grids, and transmit it to the central control platform. The real-time feedback mechanism can make instant adjustments to the dispatching plan according to the monitoring data, so as to cope with emergencies and system changes;

[0025] The integrated scheduling platform system has multi-level scheduling decision support functions, including short-term scheduling, medium-term scheduling and long-term planning. The short-term scheduling mainly focuses on real-time power demand and resource allocation, the medium-term scheduling focuses on optimization in daily operations, and the long-term planning involves future energy resource allocation and development trend forecasts. Therefore, through multi-level decision support, the integrated scheduling platform system can perform optimized scheduling on different time scales to ensure the efficient operation of the virtual power plant.

[0026] The energy resources include but are not limited to photovoltaics, wind power, energy storage and loads. The algorithm can automatically adjust the scheduling strategy according to changes in electricity demand and fluctuations in energy resources to improve energy utilization efficiency and power supply stability.

[0027] The integrated scheduling platform system adopts efficient communication network technology, so it can ensure fast data transmission and information exchange between various modules in the system. The integrated scheduling platform system uses low-latency communication protocols and data encryption technology, so the integrated scheduling platform system can ensure the timeliness and security of scheduling instructions and improve the response speed and reliability of the overall scheduling.

[0028] The integrated dispatching platform system also includes an operation interface, through which users can conveniently view the operating status, dispatching plans and optimization suggestions of the power system in real time, and then can conveniently and timely perform convenient operations and adjustments, thereby greatly reducing the difficulty of operation and improving the usability of the system.

[0029] The integrated dispatching platform realizes real-time monitoring and coordinated dispatching of various resources through an integrated console, and the platform can integrate power data, energy storage status and load demand from different types of power generation sources, thereby realizing unified dispatching management across devices and regions.

[0030] The intelligent scheduling algorithm can automatically adjust the scheduling strategy according to changes in power demand, fluctuations in energy resources and power grid operation conditions to improve energy utilization efficiency and power supply stability.

[0031] The core of the algorithm is the prediction model and optimization model, which uses deep learning technology to predict power load and renewable energy power generation, and combines the optimization algorithm to formulate the optimal scheduling plan.

[0032] The network architecture of the integrated scheduling platform adopts a distributed design, which reduces the risk of single point failure, supports high-concurrency data transmission requirements, and improves the response speed and reliability of the overall scheduling.

[0033] The data collection includes but is not limited to power load, power generation, energy storage status and meteorological data. The collected data needs to be preprocessed, including data cleaning, normalization and missing value filling, so as to ensure the quality and accuracy of the data.

[0034] After the data preprocessing, feature engineering is required. The extracted features include extracting time series features, meteorological impact features and load change patterns. The purpose of feature engineering is to convert complex data into a form that can be processed by a machine learning model to improve the performance of the prediction model.

[0035] The present invention is based on the combination of intelligent scheduling algorithm and real-time monitoring function, which can enable the scheduling plan to accurately match power demand and resource supply, reduce scheduling errors and resource waste, and the efficient communication network and real-time feedback mechanism can enable the system to quickly respond to changes in power demand and emergencies, ensuring the stability and reliability of power supply.

[0036] The hierarchical scheduling decision support function can be optimized at different time scales to ensure the rational allocation and efficient utilization of energy resources. The integrated scheduling platform and intelligent scheduling algorithm improve the overall stability of the system and reduce system failures and operational risks.

[0037] Through an integrated dispatching platform, intelligent dispatching algorithm, real-time monitoring and feedback mechanism, multi-level decision support, efficient communication network and user-friendly operation interface, the dispatching accuracy, response speed and system stability of the virtual power plant can be significantly improved.

[0038] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A virtual power plant dispatching system, characterized in that: include: Integrated dispatching platform: The integrated dispatching platform can be used to uniformly manage and dispatch various distributed energy resources in the virtual power plant. The integrated dispatching platform system can realize real-time monitoring and coordinated dispatch of various resources through an integrated console. The integrated dispatching platform system introduces an intelligent dispatching algorithm based on artificial intelligence, and processes and predicts historical data and real-time data through machine learning and data analysis technology, thereby optimizing the power dispatching plan; The integrated dispatching platform system is equipped with a real-time monitoring module, which can monitor the operation status of the power system throughout the process, and then obtain the status information of various energy resources in real time through sensors and data acquisition technology installed in various energy resources and power grids, and transmit it to the central control platform. The real-time feedback mechanism can make instant adjustments to the dispatching plan according to the monitoring data, so as to cope with emergencies and system changes; The integrated scheduling platform system has multi-level scheduling decision support functions, including short-term scheduling, medium-term scheduling and long-term planning. The short-term scheduling mainly focuses on real-time power demand and resource allocation, the medium-term scheduling focuses on optimization in daily operations, and the long-term planning involves future energy resource allocation and development trend forecasts. Therefore, through multi-level decision support, the integrated scheduling platform system can perform optimized scheduling on different time scales to ensure the efficient operation of the virtual power plant.

2. The virtual power plant dispatching system according to claim 1, characterized in that: The energy resources include but are not limited to photovoltaics, wind power, energy storage and loads. The algorithm can automatically adjust the scheduling strategy according to changes in electricity demand and fluctuations in energy resources to improve energy utilization efficiency and power supply stability.

3. The virtual power plant dispatching system according to claim 1, characterized in that: The integrated scheduling platform system adopts efficient communication network technology, so it can ensure fast data transmission and information exchange between various modules in the system. The integrated scheduling platform system uses low-latency communication protocols and data encryption technology, so the integrated scheduling platform system can ensure the timeliness and security of scheduling instructions and improve the response speed and reliability of the overall scheduling.

4. The virtual power plant dispatching system according to claim 1, characterized in that: The integrated dispatching platform system also includes an operation interface, through which users can conveniently view the operating status, dispatching plans and optimization suggestions of the power system in real time, and then can conveniently and timely perform convenient operations and adjustments, thereby greatly reducing the difficulty of operation and improving the usability of the system.

5. The virtual power plant dispatching system according to claim 1, characterized in that: The integrated dispatching platform realizes real-time monitoring and coordinated dispatching of various resources through an integrated console, and the platform can integrate power data, energy storage status and load demand from different types of power generation sources, thereby realizing unified dispatching management across devices and regions.

6. The virtual power plant dispatching system according to claim 1, characterized in that: The intelligent scheduling algorithm can automatically adjust the scheduling strategy according to changes in power demand, fluctuations in energy resources and power grid operation conditions to improve energy utilization efficiency and power supply stability.

7. The virtual power plant dispatching system according to claim 1, characterized in that: The core of the algorithm is the prediction model and optimization model, which uses deep learning technology to predict power load and renewable energy power generation, and combines the optimization algorithm to formulate the optimal scheduling plan.

8. The virtual power plant dispatching system according to claim 1, characterized in that: The network architecture of the integrated scheduling platform adopts a distributed design, which reduces the risk of single point failure, supports high-concurrency data transmission requirements, and improves the response speed and reliability of the overall scheduling.

9. The virtual power plant dispatching system according to claim 1, characterized in that: The data collection includes but is not limited to power load, power generation, energy storage status and meteorological data. The collected data needs to be preprocessed, including data cleaning, normalization and missing value filling, so as to ensure the quality and accuracy of the data.

10. The virtual power plant dispatching system according to claim 1, characterized in that: After the data preprocessing, feature engineering is required. The extracted features include extracting time series features, meteorological impact features and load change patterns. The purpose of feature engineering is to convert complex data into a form that can be processed by a machine learning model to improve the performance of the prediction model.

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