A multi-objective optimization system and method for a microgrid with composite energy storage

Abstract

The invention discloses a multi-objective optimization system and a multi-objective optimization method containing a composite energy storage micro grid. The multi-objective optimization system containing a composite energy storage micro grid is composed of a micro grid central controller, an energy storage controller, a photovoltaic controller, a load controller, and a communication network. According to the multi-objective optimization method containing a composite energy storage micro grid, a multi-objective optimization model is established for a grid-connected composite energy storage micro grid including photovoltaic batteries, flow batteries, lithium batteries and other energy storage devices, with the purpose of minimizing micro grid electricity purchasing cost and tie line power fluctuation. The weighting coefficient is determined based on a two-person zero-sum game method, and the model is converted into a single-objective optimization problem and solved using a linear weighted method. By adopting the multi-objective optimization system containing a composite energy storage micro grid, the utilization rate of renewable energy of the micro grid can be maximized effectively, tie line power fluctuation and distributed power supply grid-connected operation shock can be reduced, and the economical efficiency of micro grid operation can be improved.

Description

technical field [0001] The invention belongs to the technical field of micro-grid energy management, in particular to a multi-objective optimization system and method for a micro-grid with composite energy storage. Background technique [0002] With the enhancement of people's awareness of environmental protection, distributed power generation has received more and more attention and applications, and the research on microgrids formed by small-capacity distributed power sources has attracted more attention. Distributed power sources in this type of microgrid mainly include wind turbines, solar photovoltaic cells, fuel cells, micro gas turbines, etc., and different types of distributed power sources have different operating characteristics. When ensuring the normal operation of the micro-grid, how to manage these distributed power sources reasonably to ensure that the micro-grid can meet the power quality requirements of the load at different times and obtain the most ideal e...

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Problems solved by technology

[0004] After searching the existing technical literature, it is found that for the multi-objective optimization management problem of micro-grid energy, the multi-objective optimization of micro-grid energy management with distributed generation (Wang Xingang, Ai Qian, Xu Weihua, Han Peng. Micro-grid energy with distributed generation Multi-objective optimization of management [J]. Power System Protection and Control, 2009,20:79-83.) A multi-objective immune algorithm using niche evolution is proposed to optimize microgrid energy management, but the algorithm does not take into account the randomness of renewable energy output Volatility; Research on Multi-objective Optimal Control of Microgrid Based on Genetic Algorithm (Han Xiaoqing, Liu Hailong. Research on Multi-objective Optimal Control of Microgrid Based on Genetic Algorithm [A]. China Electrotechnical Society. Proceedings of the 2011 China Electrotechnical Society Annual Conference [ C]. China Electrotechnical Society:, 2011:5.) and multi-objective operation optimization of microgrid based on dynamic dispatch of battery energy storage system (Zhong Yufeng, Huang Minxiang, Ye Chengjin. Multi-objective operation optimization of microgrid based on dynamic dispatch of battery energy storage system [J]. Electric Power Automation Equipment, 2014, 06: 114-121.) respectively proposed to use genetic algorithm and dynamic programming method to solve the problem, but they did not consider the selection optimization problem of weight coefficient

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