1. Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm
- Author
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Zheng Wenguang, Lin Da, Ke Dongdong, Zhou Yuhao, Zhang Zhongping, and Mou Min
- Subjects
0209 industrial biotechnology ,Mathematical optimization ,Multidisciplinary ,Article Subject ,General Computer Science ,Energy management ,Computer science ,020209 energy ,Node (networking) ,Sorting ,QA75.5-76.95 ,02 engineering and technology ,Energy consumption ,Power (physics) ,020901 industrial engineering & automation ,Electronic computers. Computer science ,Genetic algorithm ,Thermal ,0202 electrical engineering, electronic engineering, information engineering ,Energy supply ,Microgrid ,Energy (signal processing) - Abstract
Because of the problems of low operation efficiency and poor energy management of multienergy input and output system with complex load demand and energy supply, this paper uses the double-layer nondominated sorting genetic algorithm to optimize the multienergy complementary microgrid system in real-time, allocating reasonably the output of each energy supply end and reducing the energy consumption of the system on the premise of meeting the demand of cooling, thermal and power load, so as to improve the economy of the whole system. According to the system load demand and operation mode, the first layer of this double-layer operation strategy calculates the power required by each node of the microgrid system to reduce the system loss. The second layer calculates the output of each equipment by using nondominated sorting genetic algorithm with various energy values calculated in the first layer as constraint conditions, considering the operation characteristics of various equipment and aiming at economy and environmental protection. In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.
- Published
- 2020