Microgrid energy management system based on IEC (International Electrotechnical Commission) 61850 and multi-agent method

Abstract

The invention relates to a system in the technical field of information, and in particular relates to a microgrid energy management system based on the IEC (International Electrotechnical Commission) 61850 and a multi-agent method. The microgrid energy management system comprises a distributed power supply / load control unit agent, a microgrid central control unit agent and a power distribution grid control unit agent, wherein according to the modeling standard of the IEC 61850 and the characteristics of all units forming the microgrid system, by using an information model defined by the IEC 61850 as a uniform reference of message transmission among the agents, the information model is mapped to an ontology element of an agent communication language (ACL), the compatibility of the IEC 61850 and the multi-agent method is realized, the working state of a microgrid is described by the information model based on the IEC 61850 inside the agents, and the agents are communicated through the ACL. The multi-agent method is applied to the microgrid energy management system, and the information model of the IEC 61850 is used as the basis of the message transmission among the agents, so that the instantaneity, the uniformity and the interoperability of information interaction among the agents are ensured, and all-network ideal operation of all distributed power supplies and the microgrid system is realized by using a dynamic game in an optimizing process on the basis of a simulated annealing algorithm.

Description

technical field [0001] The invention relates to a system in the field of information technology, in particular to a microgrid energy management system based on IEC 61850 and a multi-agent method. Background technique [0002] The proposal of micro-grid technology is closely related to the application and development of Distributed Generation (DG) technology. Compared with traditional power sources that rely on long-distance power transmission and distribution, distributed generation technology has diversified energy forms and high energy utilization efficiency. and environmental friendliness and many other advantages. The flexible and decentralized installation location of the distributed generation system perfectly adapts to the decentralized power demand and resource distribution, delaying the huge investment required for the upgrade of the transmission and distribution network. Reliability is improved, effectively solving many potential problems of large centralized grid...

AI Technical Summary

Problems solved by technology

[0008] The application of various algorithms introduced above in the microgrid optimization operation provides new ideas for the energy management of the microgrid, but so far there is still no algorithm that can fully realize the optimal analysis of the microgrid energy management. In the existing microgrid energy management technical solutions, most of the various optimization algorithms are combined with centralized management. Because there are many types of distributed power sources and loads in the microgrid, and their operating characteristics are different, this is the energy of the microgrid. Management leads to two contradictory situations: 1) In order to accurately obtain the optimal solution or approximate optimal solution of microgrid energy management, the microgrid central control unit must obtain as many operating parameters as possible of each distributed power source and load in the system , which makes the centralized energy management parameters surge, the operation efficiency is low, and the burden of communication lines in the microgrid system increases, and the information transmission overhead increases; 2) In order to quickly obtain the optimal solution or approximate optimal solution of the microgrid energy management, At the same time, the construction of communication lines is reduced to save costs. The central control unit of the microgrid only needs to know the main working status of each distributed power source and load in the system, which makes the optimal solution or approximate optimal solution not necessarily the optimal solution of each distributed power supply. The description of the best working state of the power supply may even cause low efficiency of distributed power supply, increase of operating cost or damage to environmental protection

If the distributed power sources and loads in the microgrid system belong to different users or owners, it will inevitably make centralized energy management more difficult

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