基于改进蝙蝠算法含分布式电源的无功优化

Reactive Power Optimization with Distributed Generators Based on the Improved Bat Algorithm

将分布式电源与传统的配电网电压调节方式相结合,分析包含分布式电源的配电网系统无功优化的问题,并建立了有功网络损耗最低以及电压稳定裕度最大的多目标优化数学模型,利用模糊理论将分布式电源的多目标无功优化问题转换成单目标优化问题,进一步减少了有功网损,提高了电压稳定性。鉴于传统蝙蝠群体易于聚集于局部极值,导致早熟,将混沌序列以及自适应调整策略融入到蝙蝠优化算法中,提出了一种改进型多目标蝙蝠优化算法,利用混沌理论以及动态自适应机制调整的特性,对蝙蝠算法参数进行调整。通过IEEE-33测试系统验证,所提算法具有良好的实用性和适应性,并且也证明了所提模型的实际意义。

Integrates the distributed generators（DGs） with traditional grid voltage regulation, analyzes the grid reactive power optimization of distributed generators, and builds the multi-objective optimized mathematical model with less active power network loss and maximum voltage stability margin. Applies fuzzy theory to transform the multi-objective reactive power optimization into single-objective optimization, further reduces active power network loss and improves the voltage stability. In order to overcome the problem of traditional bat algorithm tending to fall into the local optimal solution,integrates the chaos sequence and adaptive adjustment strategy into the bat optimization algorithm and proposes an improved multi-objective bat optimization algorithm. Adjusts the bat algorithm parameters by chaos theory and dynamic adaptive mechanism adjust characteristics. Through the IEEE-33 test system, verifies the practicability and adaptability of the proposed algorithm, and it also proves the practical significance of the model.