Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet

High renewable energy penetration worsens systems instability. Balancing consumption and generation output reduces this This paper introduces coordination control to coordinate the flow of electricity between MG buses stabilize system under variable load, conditions. The adopted regulates bidirectional DC/AC main converter using digital proportional resonant controllers in a synchronous reference frame. A maximum power point tracker-based boost DC/DC enables wind turbine solar photovoltaic harvest power. Traditional methods such as perturb observe incremental conductance trackers cannot solve nonlinearity inaccurate responses. work provides hybrid tracker strategy modify responses standard techniques based on particle swarm optimization-trained adaptive neuro-fuzzy inference (ANFIS-PSO) achieve quick with minimal oscillation tracking. Concerning management system, adopts recent meta-heuristic algorithms-based DSM program consumers’ use by shifting load appliances off-peak demand periods. algorithms for are sparrow search algorithm (SSA), binary orientation (BSOA), cockroach (CA). Finally, Internet technology, ThingSpeak cloud-based MATLAB is gather display real-time data streams generate graphical analyses. simulation results reveal that recommended coordinating produces grid frequency responsiveness zero steady-state errors. optimal minimizes peak from 5.2 kWh 4.6 kWh. All cost 439.1 $ per month, compared 484.4 nonscheduling profile.