Electrical Power and Machine Department, Faculty of Engineering, Zagazig University, Egypt.
J Adv Res. 2014 May;5(3):397-408. doi: 10.1016/j.jare.2013.06.010. Epub 2013 Jul 6.
One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.
应用于优化光伏系统以满足孤岛负载需求的最新优化技术之一是人工蜂群算法 (ABC)。所提出的方法应用于优化光伏系统的成本,包括光伏、电池组、电池充电器控制器和逆变器。提出了两个目标函数:第一个是要最大化的光伏模块输出功率,第二个是要最小化的生命周期成本 (LCC)。分析基于在埃及赫勒万市测量的太阳辐射和环境温度进行。对 ABC 算法和遗传算法 (GA) 的最优结果进行了比较。选择了另一个位于 Zagazig 的位置来检查 ABC 算法在任何位置的有效性。ABC 比 GA 更优。结果鼓励在埃及农村地区使用光伏系统为其供电。