Zero bus load flow method for the integration of renewable DGs by mixed‐discrete particle swarm optimisation‐based fuzzy max–min approach

Abstract

This study proposes an approach to determine the optimal placement and sizing of renewable distributed generations (DGs) and shunt capacitor in the distribution network (DN) with a pre‐defined energy contract strategy with the main grid by using fuzzy integrated mixed‐discrete particle swarm optimisation (MDPSO) based method. The proposed pre‐defined contract strategies are implemented in this study using the modified Newton–Raphson (NR) load flow method with the concept of the PQVδ−zero bus. The modifications in the Jacobian matrix in the NR load flow method is developed. MDPSO method is adopted to take care of both the continuous and the discrete variables, to determine the proper locations and the sizes of renewable DGs and shunt capacitor by reducing the active power loss, improving the voltage profile, and reducing the annual costs of the DGs. The multi‐objective optimisation is solved by using the fuzzy max–min‐based technique. The proposed method of DG placement is tested on 69 bus DN for three different scenarios. The results obtained from the proposed multi‐objective method are also compared with the weighted sum approach for different combinations.

Solar-Based DG Allocation Using Harris Hawks Optimization While Considering Practical Aspects

“…One of the most effective and widely used optimization strategies is the PSO [23][24][25]. Barik et al [26] presented a multiobjective PSO method for determining the best location and size of DG units while taking economic and technical factors into account. The advanced versions of PSO methods, such as improved PSO [27], binary PSO [28], social learning PSO [29], PSO with inertia weight, and PSO with constriction factor [30], are also applied in the DG allocation and sizing problems.…”