Optimal allocation of stochastically dependent renewable energy based distributed generators in unbalanced distribution networks
Optimal allocation of stochastically dependent renewable energy based distributed generators in unbalanced distribution networks
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DOI：
10.1016/j.epsr.2014.09.005
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发表时间：
2015-02
影响因子：
3.9
通讯作者：
A. Abdelaziz;Y. Hegazy;W. El-Khattam;Mahmoud M. Othman
中科院分区：
文献类型：
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作者：
A. Abdelaziz;Y. Hegazy;W. El-Khattam;Mahmoud M. Othman
本文提出了一种算法建模的随机依赖的可再生能源为基础的分布式发电机的适当规划的不平衡配电网的目的。该算法结合了对角带Copula函数和序贯蒙特卡罗方法，以准确地考虑风电、光伏发电与系统需求之间的多变量随机相关性。其次，提出了一种有效的算法的基础上修改传统的大爆炸-大紧缩方法的可调度分布式发电存在的可再生能源的分布式发电机的优化配置。该优化算法的目的是通过确定非可调度分布式发电机的最佳位置和可调度分布式发电机的最佳小时功率计划来最小化不平衡配电系统中的能量损失。在MATLAB环境下实现了所提出的算法，并在IEEE 37节点馈线上进行了测试。最后通过实例分析验证了算法的有效性.
This paper proposes an algorithm for modeling stochastically dependent renewable energy based distributed generators for the purpose of proper planning of unbalanced distribution networks. The proposed algorithm integrate the diagonal band Copula and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. Secondly, an efficient algorithm based on modification of the traditional Big Bang-Big crunch method is proposed for optimal placement of renewable energy based distributed generators in the presence of dispatchable distributed generation. The proposed optimization algorithm aims to minimize the energy loss in unbalanced distribution systems by determining the optimal locations of non-dispatchable distributed generators and the optimal hourly power schedule of dispatchable distributed generators. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithms.