A Smart Microgrid System with Artificial Intelligence for Power-Sharing and Power Quality Improvement

The widespread popularity of renewable and sustainable sources energy such as solar wind calls for the integration into electrical power grids development. Microgrids minimize quality issues in main grid by linking with an active filter furnishing reactive compensation, harmonic mitigation, load balancing at point common coupling. reliability faced standalone DC microgrids can be managed interlinking a grid. An artificial intelligence-based Icosϕ control algorithm sharing improvement smart microgrid systems is proposed here to render grid-integrated more intelligent. controller considers various uncertainties caused variations, state charge battery microgrids, tariff based on availability microgrids. This paper presents detailed analysis dynamic flow management order improve reduce burden, thereby strengthening central A system multiple coupled source judicious was simulated power-sharing improvement. hardware prototype nonlinear also implemented successfully. Furthermore, economic viability investigated ensure feasibility design