Department of Electrical and Control Engineering, Arab Academy for Science, Technology and Maritime Transport, Cairo, Egypt.
Department of Electrical Power and Machines, Fayoum University, Fayoum, Egypt.
PLoS One. 2018 Feb 21;13(2):e0193224. doi: 10.1371/journal.pone.0193224. eCollection 2018.
This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.
本文提出了一种新颖的优化技术,用于研究孤岛微电网的能源管理。该系统由各种分布式能源资源(DER)、柴油发电机(DG)、风力涡轮发电机(WTG)、光伏(PV)阵列以及由燃料电池/电解槽供能的氢气储存系统为短期储存提供支持。通过非支配排序遗传算法进行多目标优化,以满足给定约束下的负载需求。利用一种新颖的多目标花授粉算法来检查结果。比较和评估了这两种优化技术的优缺点。使用 MATLAB 软件包对孤岛微电网进行建模,进行有功/无功功率调度,以及带有松弛母线选择的最优潮流分析,以在实际约束下最小化燃料成本和线路损耗。研究和分析了系统在夏季和冬季条件下的性能,并为每种条件提出了三个案例研究。使用修改后的 IEEE 15 母线系统来验证所提出的算法。