Abstract
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.
Highlights
battery energy storage system (BESS) is placed at the final optimal location for the second part of the optimisation process to determine the optimal BESS sizing needed for each hour using the same distribution network
The optimal BESS location and sizing proposed by Whale Optimisation Algorithm (WOA) was acknowledged as the optimal solutions for all studies
For the first study involving the optimisation for total system losses reduction alone, the BESS was proposed to be placed optimally at bus 7 and bus 18 with total BESS energy of 1079.97 MWh
Summary
Power systems are experiencing a change from the conventional passive system to the active system through the integration of distributed generations and energy storage Such a change is attributed to the need to reduce greenhouse gas emissions, deferral of transmission and distribution system expansion together with the improvement of power system reliability and quality [1]. The ESSs are capable of providing different functions in the power systems such as spinning reserve, peak shaving, generation output smoothing, voltage control, reverse power flow reduction, power losses reduction and uninterruptible power supply. These functions depend on the technical characteristics of the ESSs, including storage capacity, efficiency, cost, lifetime and power rating [2, 3]. Optimal planning of ESS in the power systems ensures overall reliability and performance while reducing the investment and operation cost [5, 6]
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