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Affine Method for Multi-objective Optimizing Configuration of Battery Energy Storage System

机译:电池储能系统多目标优化配置的仿射方法

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In this paper, an affine method considering both randomness of the wind power and the load for multi-objective optimizing configuration of battery energy storage system (BESS) is proposed. According to the method, affine arithmetic is used to solve the uncertain power flow and the network loss, the voltage improvement rate (VIR) and the BESS cost are chosen as the objective functions. New metrics are provided to distinguish the dominance relation between two affine numbers and an improved particle swarm optimizing algorithm is also proposed to get the final Pareto optimal solution set. The IEEE 14-bus transmission system is studied to demonstrate the effectiveness and the efficiency of the method. Case results suggest that the Pareto optimal solution set achieved by the method can effectively solve the problem of the results, which lack diversity and comprehensiveness, in the existing methods.
机译:在本文中,提出了考虑风电的随机性和电池储能系统(BESS)的多目标优化配置的随机性的仿射方法。 根据该方法,使用仿射算术来解决不确定的功率流量和网络损耗,因此选择电压提高率(VIR)和BESS成本作为目标函数。 提供了新的指标,以区分两个仿射数与改进的粒子群优化算法的优势关系,也提出了最终帕累托最优解决方案集。 研究了IEEE 14总线传输系统,以展示该方法的有效性和效率。 案例结果表明,通过该方法实现的帕累托最优解决方案可以有效地解决现有方法中缺乏多样性和全面性的结果。

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