Assessment Integration of Hybrid PV-DSTATCOM-BES-DG System in EDS under Uncertainties Using Chaotic Adaptive Inertia Weight PSO Algorithms

Recently, the production of energy decentralized has become one of the appropriate solutions to meet the continuous increase in energy demand, due to its rapid construction compared to classical stations. This paper addresses the optimal integration of simultaneous integration of many resources such as Photovoltaic source (PV-DG), Distribution Static Compensator DSTATCOM, Battery Energy Storage (BES), and Diesel Generator (DG) to minimize the Active Power Loss (APL), the Total Voltage Variation (TVV), and the Annual Losses Cost (ALC), by considering the uncertainty of both loads demand variation and the power output of PV in 24 hours, these are achieving by using Basic and various chaotic Adaptive inertia weight PSO algorithm, moreover, the validation of the efficiency of these algorithms are tested on the two Electrical Distribution Systems (EDS), which are standard IEEE 33-, and 69-bus systems. Results show the efficiency of the proposed algorithms in order to obtain the minimum active power loss and improved the voltages profile. The obtained results show the effect of the uncertainty on the planning to find the optimal location and size of decentralized sources.