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Optimization Strategy for New Energy Consumption Based on Intuitionistic Fuzzy Rough Set Theory

Xinrui LiuSchool of Information Science & Engineering, Northeastern University, ShenyangXinying ZhaoSchool of Information Science & Engineering, Northeastern University, ShenyangPeng JinTianqi LuState Grid Liaoning Electric Power Company Limited Economic Research Institute, Shenyang
2020en
ABI

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Imitate the consumption method for wind power segment compensation, using intuitionistic fuzzy rough set theory, propose the use of ambiguity, uncertainty and other properties to dynamically divide the state of wind power consumption, divides a combined heat and power system containing an electro-thermal hybrid model including equipment such as electrolytic hydrogen, microturbine, electric boiler, etc. into a normal state, an alert state, and an emergency state. Then, on the basis of situational division, establish system optimization models in different situations, and the particle swarm algorithm is used to solve the model. The analysis results of the calculation examples show that the operating cost of the system divided by the intuitionistic fuzzy rough set theory is lower than that required by the traditional situation division method; under the intuitionistic fuzzy division method, the system state judgment is more flexible and accurate, compared with the traditional division method, the electro-thermal hybrid model in this mode can absorb more abandoned wind and meet the system's electricity and heat requirements.

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