This paper suggests a method to place and size the battery energy storage system (BESS) optimally to minimise total system losses in a distribution system. Subsequently, the duck curve phenomenon is taken into consideration while determining the location and sizing. The locations and sizing of BESS were optimised using a metaheuristic algorithm with high exploration and exploitation ability which is known as the Whale Optimisation Algorithm (WOA). Meanwhile, the performance of WOA was validated using other algorithms, i.e., Particle Swarm Optimisation and Firefly Algorithm. The results demonstrated the capability of WOA to determine the optimal BESS location and sizing for all cases, with and without considering the duck curve issue for loss reduction. Besides that, the duck curve issue can be mitigated by appropriately optimising the energy storage system (ESS) to reduce the steep ramp of the duck neck and ducktail and to lift the duck belly. In conclusion, although less loss reduction was achieved as a tradeoff to fulfil the constraint on net load ramp limit, the required BESS sizing was much smaller than the case without those constraints and charging operation, which makes this solution economically viable.

In this paper, a metaheuristic method is suggested to attain the optimal locations and sizing of the battery energy storage system (BESS), with the intention to decrease the overall system losses in a distribution system. To increase the reliability of the outcome, simultaneous optimization approach is employed, where the optimization problem is solved using Whale Optimization Algorithm (WOA). The hourly variation of photovoltaic (PV) generation and load profile for up to one week is considered in this work. The performance of WOA is validated with Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). The optimization outcomes proved the ability of WOA in attaining the optimal BESS allocations for overall system losses reduction where the optimal solutions suggested by WOA has achieved the highest overall system losses reduction, followed by PSO while FA has the worst performance in this application.

This paper presents an approach using quantum-inspired lightning search algorithm (QLSA) in obtaining the optimal power quality monitors (PQMs) placement in the power grid. An objective function with the idea of topological monitor reach area is formulated considering the system observability constraint. The effectiveness of the suggested technique has been verified using IEEE 118-bus system and comparison has been done with another quantum-inspired algorithm. The results show that QLSA is able to perform well in PQMs placement problem.

In this paper, a novel metaheuristic optimization approach is introduced to attain the optimal locations and sizing of the battery energy storage system (BESS), with the intention to reduce the overall system losses in a distribution system. Apart from system losses reduction, the duck curve issue is considered in terms of optimization constraint. The hybrid of whale optimization algorithm and artificial immune system (WOA-AIS) which is effective in handling duck curve constraint is proposed to perform the optimization process. The performance of WOA-AIS is validated with hybridized Particle Swarm Optimization (PSO-AIS) and Firefly Algorithm (FA-AIS). The results displayed the ability of WOA-AIS in attaining the optimal BESS allocations by considering duck curve issue as constraint, where it can be observed that the optimal allocations suggested by WOA-AIS has achieved the highest losses reduction. Meanwhile, it can be concluded that the amount of total BESS energy may not proportionate to the losses reduction attained by each algorithm as the overall system losses had been affected by the location of BESS.