Enhancing Power Quality in Photovoltaic Systems Through the Integration of SSA-PSO Algorithm and DSMC Technique

With the increasing reliance on standalone photovoltaic battery systems (SPVBS), it is necessary to develop robust control techniques to optimize system performance and lifetime. Aiming at the problems of SPVBS, such as voltage instability, low-frequency ripple, MPPT tracking speed, and dynamic performance, a novel SSA-PSO-DSMC control system is proposed, which employs hybrid singular spectrum analysis and particle swarm optimization (SSA- PSO) in combination with an intelligent, direct sliding mode controller (DSMC) to eliminate the instability and fluctuation of the dc-bus voltage, and the DSMC acts as a bidirectional DC-DC converter and boosts converter to enhance the dynamic MPPT capability of the system. By simulating the measured data of a PV power plant in Gansu Province, the results show that the proposed SSA-PSO-DSMC technique has good results in DC bus regulation, output power extraction, and current harmonics reduction compared with PSO, SSA, Cuckoo Search Optimization (CSO) and Gray Wolf Optimization (GWO).