The problem of optimal placement and sizing (OPS) of renewable distributed generation (RDG) is followed by numerous technical, economical, geographical, and ecological constraints. In this paper, it is investigated from two viewpoints, namely the simultaneous minimization of total energy loss of a distribution network and the maximization of profit for RDG owner. The stochastic nature of RDG such as the wind turbine and photovoltaic generation is accounted using suitable probabilistic models. To solve this problem, a hybrid metaheuristic algorithm is proposed, which is a combination of the phasor particle swarm optimization and the gravitational search algorithm. The proposed algorithm is tested on an IEEE 69-bus system for several cases in two scenarios. The results obtained by the hybrid algorithm shows that it provides high-quality solution for all cases considered and has better performances for solving the OPS problem compared to other metaheuristic population-based techniques.

中文翻译：

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混合元启发式算法在可再生分布式发电的最优布置和选型中的应用。

可再生分布式发电（RDG）的最佳布局和大小（OPS）问题随之而来，其技术，经济，地理和生态方面受到诸多限制。本文从两个角度进行研究，即同时使配电网的总能量损失最小化和RDG所有者的利润最大化。RDG的随机性质（例如风力涡轮机和光伏发电）使用适当的概率模型进行解释。为了解决这个问题，提出了一种混合元启发式算法，该算法结合了相量粒子群算法和引力搜索算法。在两种情况下，针对几种情况，在IEEE 69总线系统上对提出的算法进行了测试。