Intelligent Load Management System Development with Renewable Energy for Demand Side Management

Abstract

Electric smart grid reliability and stability could be increased by the application of demand response initiatives and renewable energy resources. This study provides a brand new demand side management paradigm for smart grids with renewable energy integration that is based on intelligent optimisation. The suggested system combines real-time demand response programmes from electric utility companies and makes use of fuzzy logic to forecast consumer energy consumption patterns. Using demand response programmes, a smart energy management controller adjusts consumer energy usage forecasts to produce an operation schedule. Using simulations employing real-world data, we assess the efficacy of the suggested intelligent demand side management framework. According to the findings, compared to the load management-free method, total electricity costs and carbon emissions have significantly decreased. A potential strategy for demand side management with the integration of renewable energy, the proposed intelligent hybrid optimisation method of load management achieves superior performance in regulating energy consumption, peak loads, and carbon emissions. By presenting a useful and effective paradigm for demand-side management with renewable energy integration, this research makes a contribution to the field of energy management.

Optimal Positioning of Distributed Energy using Intelligent Hybrid Optimization

“…In [32,33], a quick analytic method to establish the ideal distribution generation size at the ideal power factor was put out. Control of every electric infrastructure is very important [34] and optimal placement in this case is kind of a control and achieved using proposed hybrid algorithm [35,36]. This paper is discussed as follows.…”