Enhanced performance of grid connected photovoltaic (PV) system using hybrid energy storage systems

Le résumé fourni par la source

Decentralized systems that interact with one another and with the electrical grid as a whole have revolutionized and progressed the electric power system. Integrating energy storage systems into microgrids is encouraged due to the fact that energy limitations and environmental concerns are driving forces behind the key problems of these systems. Energy storage technologies enhance the reliability and efficiency of microgrids. A hybrid energy storage system (HESS) for microgrid usage is suggested by this research, which combines superconducting magnetic energy storage (SMES) with batteries. This study presents a new cooperative control technique for a grid-connected system that uses photovoltaics to solve the problem of unstable output power caused by the inherent unpredictability and fluctuation of RES. Within the scope of a hybrid energy storage system (HESS), this technique makes use of both BESS and SMES. To achieve optimization of transient power allocation and dynamic regulation of the filtration coefficient, the control method utilizes a fuzzy control-based low-pass filter (LPF) at top-level control (TLC). Keeping the DC bus voltage stable using a one-step prediction horizon is accomplished simultaneously at the under-layer level control (ULC) using a rapid model predictive control (MPC) technique. Effectively validated under varied operating situations is the practicality and effectiveness of the suggested control technique, which proves to be effective in improving the grid-connected system’s stability and performance. Utilizing the MATLAB/Simulink platform, a comparison is made between the effectiveness of analysis of grid-connected systems with neural network controllers and fuzzy logic controllers.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.