Optimal real-time operation of battery energy storage systems for reducing on-load tap changer operation of substation transformers

Abstract

At present, renewable energy sources (RESs) from photovoltaic (PV) and wind turbine (WT) play an important role in electricity generations. On the other hand, battery energy storage systems (BESSs) have been conventionally used to store and supply energy to help smooth power generation. However, the intermittent nature of the RES can cause variations in the power produced by PV and WT generations. The system voltage fluctuations resulting from the changes in electrical power led to voltage stability problems. The on-load tap changer (OLTC) installed on substation transformers to control the voltage level will be overloaded. This excessive operation affects the lifespan of the component, damage, maintenance cost, and system reliability. These problems can be mitigated by effectively controlling the operation of the BESS to reduce voltage oscillations and the OLTC operations. This paper presents the optimal real-time operation of BESS to control system voltages and reduce OLTC operations under the power fluctuations from PV and WT intermittency. The system voltage can be controlled by charging/discharging BESS's active and reactive power using the proposed approach. The optimal BESS operation is formulated as an optimization problem solved by particle swarm optimization (PSO) to minimize the OLTC operations. The PSO algorithm is created as an m-file script in MATLAB for evaluating the optimal solution. The power system modeling and power flow analysis are carried out using a DPL script in DIgSILENT PowerFactory. The simulation case studies are performed using the IEEE 123-node test feeder, modified by BESS, PV, and WT installation. A comparative study is made between the conventional BESS operation for smoothing PV generation, and the proposed optimal BESS approach. The simulation test results show that the proposed approach significantly mitigates the system voltage fluctuation by 59.04% and reduces the number of OLTC operations by 50.0%, compared with those from the conventional BESS operation.