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This article presents an optimal placement and sizing of distribution static compensator (DSTATCOM) in radial distribution networks as multi-objective optimization with the objective of power loss reduction, voltage profile improvement and network reliability considering different variable demands using whale optimization algorithm (WOA). The WOA is inspired by the hunting behavior of humpback whales. The optimal location and size of DSTATCOM are considered as decision variables that are determined using the WOA. Network reliability is defined as energy not supplied (ENS) of the customers caused by line outages. The proposed method is implemented on IEEE 33-bus and Ahvaz 59-bus distribution networks. The optimal placement and sizing of DSTATCOM are investigated considering different residential, commercial and industrial loads, and also the effect of incorporating reliability is evaluated on power loss, minimum voltage and ENS. The simulation results show that the power loss and ENS are declined and also voltage profile is improved by determining the location and size of DSTATCOM in the networks in different loading conditions using the WOA. The obtained results demonstrate that considering reliability further reduces the ENS and more customer demand is met. The power loss decreases 21.60%, 30.71%, and 22.03% for residential, commercial and industrial loads in the 33-bus network and 26.86%, 31.94%, and 24.39% for the 69-bus network, respectively compared to base networks. Moreover, the performance of the WOA is compared with previous studies and the results indicate the superiority of the proposed method.

In this paper, multi-objective reactive power compensation based on optimal and simultaneous allocation of capacitors and distribution static compensator (DSTATCOM) in radial distribution networks based on fuzzy decision making is proposed with the aim of reducing power losses cost, reactive investment cost and reducing voltage deviations considering power loss reduction factor (PLRF) to identify candidate buses. Optimal location and size of reactive resources is determined based using multi-objective improved golden ratio optimization algorithm (MOIGROM) inspired by Fibonacci series and improved using nonlinearly inertia weight strategy. This method is performed on a 13 bus distribution network, 69 and 118 buses IEEE standard networks in various scenarios including capacitor allocation only, DSTATCOM allocation only and optimal and simultaneous capacitor and DSTATCOM allocation (hybrid allocation). The simulation results showed that the hybrid allocation has less power losses and voltage deviations in different scenarios using fuzzy decision making based on Pareto front set. Also the impact of different loading conditions on problem solution cleared that with increasing the load level, especially during the heavy load, the power losses and voltage deviations of the networks increase and vice versa. In addition, the advantage of the MOIGROM method over the other methods is confirmed.