In this paper, the optimal planning of Distributed Energy Storage Systems (DESSs) in Active Distribution Networks (ADNs) has been addressed. As the proposed problem is mixed-integer, non-convex, and non-linear, this paper has used heuristic optimization techniques. In particular, five optimization techniques namely Genetic algorithm, Particle swarm optimization, Tabu search, Simulated annealing, and Pattern search optimization techniques have been applied to optimal planning of DESS. The problem has been formulated to consider distributed storage units’ optimal locations and sizes to be placed in an ADN while respecting the constraints of the system. The problem has been addressed on two levels. In the first level, an optimization technique is applied for DESS planning to determine the optimal solution and in the second level, the fitness value of this solution is evaluated by solving a daily AC Optimal Power Flow (OPF) problem. Simulations have been done for the IEEE 34 and IEEE 123 nodes network to demonstrate and compare the efficiency of different optimization techniques. The comparison of these optimization techniques has shown that Particle swarm optimization and Tabu search optimization (with a particular value of tabu tenure found by hit and trial) have performed better in finding the lowest DESS location corresponding to minimum fitness value as compared to other optimization techniques both for IEEE 34 nodes and IEEE 123 nodes network.

在本文中，已经解决了有源配电网络 (ADN) 中分布式储能系统 (DESS) 的优化规划问题。由于提出的问题是混合整数、非凸和非线性问题，本文采用了启发式优化技术。特别是遗传算法、粒子群优化、禁忌搜索、模拟退火和模式搜索优化技术等五种优化技术已应用于DESS的优化规划。该问题已被制定为考虑分布式存储单元的最佳位置和大小以放置在 ADN 中，同时尊重系统的约束。该问题已在两个层面上得到解决。在第一级，优化技术应用于 DESS 规划以确定最优解，在第二级，该解决方案的适应度值是通过解决每日交流最佳潮流 (OPF) 问题来评估的。已经对 IEEE 34 和 IEEE 123 节点网络进行了模拟，以演示和比较不同优化技术的效率。这些优化技术的比较表明，与其他优化技术相比，粒子群优化和禁忌搜索优化（通过命中和试验找到特定的禁忌任期值）在找到对应于最小适应度值的最低 DESS 位置方面表现更好IEEE 34 节点和 IEEE 123 节点网络。已经对 IEEE 34 和 IEEE 123 节点网络进行了模拟，以演示和比较不同优化技术的效率。这些优化技术的比较表明，与其他优化技术相比，粒子群优化和禁忌搜索优化（通过命中和试验找到特定的禁忌任期值）在找到对应于最小适应度值的最低 DESS 位置方面表现更好IEEE 34 节点和 IEEE 123 节点网络。已经对 IEEE 34 和 IEEE 123 节点网络进行了模拟，以演示和比较不同优化技术的效率。这些优化技术的比较表明，与其他优化技术相比，粒子群优化和禁忌搜索优化（通过命中和试验找到特定的禁忌任期值）在找到对应于最小适应度值的最低 DESS 位置方面表现更好IEEE 34 节点和 IEEE 123 节点网络。