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

机译:基于直觉模糊粗糙集理论的新能源消费优化策略

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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.
机译:模仿直觉模糊粗糙集理论的风电段补偿消耗方法,提出利用模糊性,不确定性和其他属性动态划分风电消耗状态,划分包含电热混合动力的热电联产系统该模型包括电解氢,微型涡轮机,电锅炉等设备进入正常状态,警报状态和紧急状态。然后,在情境划分的基础上,建立不同情境下的系统优化模型,并采用粒子群算法对该模型进行求解。算例分析结果表明,采用直觉模糊粗糙集理论进行划分的系统的运行成本要低于传统情景划分方法所需要的运行成本。在直觉模糊分割法下,系统状态判断更加灵活,准确,与传统的分割法相比,该模式下的电热混合模型能够吸收更多的弃风,满足系统的电热需求。

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