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Optimal schedule of dispatchable DG in electrical distribution systems with extended dynamic programming

机译:扩展动态规划中配电系统调度DG的最优时间表

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In this paper, the optimal schedule of dispatchable distributed generation (DG) units connected to radial electrical distribution systems (EDS) is solved using an extended dynamic programming approach. The objective of the optimal DG scheduling problem is to determine the hour-by-hour active generation output of each dispatchable DG unit, in order to minimize the total active power losses of the EDS and the generation costs. The proposed extended dynamic programming (EDP) is an advantageous approach because convexity is not required to obtain a global optimal solution, and the “curse of dimensionality” is not a concern since the computational complexity of the algorithm grows linearly with the size of the network. Besides, the state variables have only two dimensions, one to represent the active power flows and the other to represent the nodal voltages. A 56-nodes MV distribution system with two dispatchable DG units is used to evaluate the performance of the proposed EDP approach, considering a deterministic and a stochastic case. A set of Monte Carlo simulations is used to analyze the influence of uncertainties. Results confirm that the proposed methodology is a suitable approach to unveil the best operation schedule for dispatchable DG units.
机译:在本文中,使用扩展动态编程方法解决了连接到径向配电系统(EDS)的调度分布式发电(DG)单元的最佳时间表。最佳DG调度问题的目的是确定每个调度DG单元的每小时主动发电输出,以便最小化EDS的总有效功率损耗和生成成本。所提出的扩展动态编程(EDP)是一种有利的方法,因为不需要凸起来获得全局最优解,并且“维度的诅咒”不是一个问题,因为算法的计算复杂性随着网络的大小而直线增长。此外,状态变量仅具有两个维度,一个代表有效功率流量,另一个尺寸来表示节点电压。考虑到确定性和随机壳体,使用具有两种调度DG单元的56节点MV分配系统来评估所提出的EDP方法的性能。一组蒙特卡罗模拟用于分析不确定性的影响。结果证实,所提出的方法是揭示调度DG单位的最佳运行计划的合适方法。

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