Optimized DBN‐based control scheme for power quality enhancement in a microgrid cluster connected with renewable energy system

Abstract The increasing energy consumption and changing load variations place a significant burden on the sophisticated utility grid, which affects the source's dependability and quality. Researchers examining modern power networks must focus on those factors to prevent grid breakdowns. Superior power quality (PQ) is still intended to make sure everything runs smoothly under diverse organizations. The main cause of PQ problems, however, is now renewable energy used in power electronic converters that are integrated into the electrical grid. Even though new, better solutions are still being developed, adhering to international standards have been strongly advised. Consequently, microgrid clusters powered through renewable energy and incorporating multiple structures in an urban area has been proposed in this paper. This increases the dependability of the power sources by managing the energy that is available inside the cluster instead of having it focused around the utility grid. Additionally, a deep belief network model based on Improved Dwarf Mongoose Optimization is recommended for regulating the inverter by generating optimal pulse‐width modulated signals that increases the quality of the power supplies. When compared to other conventional techniques, the suggested technique possesses less real power and reactive power setting duration of 0.8 ms and 0.75 ms, respectively.