Colonial Competitive Algorithm-based Optimal Design and Scheduling of a Hybrid Grid-Connected Photovoltaic and Wind Generation System for Residential District of a City

One of the critical disadvantages of using renewable energy resources is their low reliability due to their dependence on weather conditions. Therefore, Hybrid renewable energy systems (HRES) have been proposed in many studies as an alternative method that can accumulate their unique strength and eliminate their weaknesses as much as possible. In HRES, several types of renewable energy resources are combined in an integrated system to improve the reliability of the whole system. One of the requirements of using HRESs is to find their component’s optimal capacity size to reduce their installation cost and then schedule to reduce the operation cost according to the location specification. In this work, by using the Colonial Competitive Algorithm (CCA), the optimal components’ capacity size of an HRES, including photovoltaic arrays (PV), wind turbines (WT), and battery energy storage systems (BESS), is obtained through real-world data of a specific location. To validate the optimization results and investigate the effect of each factor, several sensitivity analyses are applied, and the results are compared. The result demonstrates that considering the BESS’s wear cost according to the exchanged kWh affects the whole system significantly, which was neglected in many recent studies. Moreover, the effect of finding the optimal initial charge at the beginning of each day is analyzed, and the results are investigated. In the end, the results of other algorithm methods are compared with CCA to show its effectiveness, and by getting an offset in BESS capacity size, scheduling is conducted for the worst-case scenario.