Integrating renewable energy sources for optimal demand-side management using decentralized multi-agent control

Demand-side management has garnered significant attention recently as a viable solution for electricity demand management. However, existing control approaches have encountered stability and energy efficiency issues that limit their effectiveness. To address these concerns, this work proposes a multi-agent control technique for optimal Demand-Side Management (DSM) in grid-connected mode. The proposed technique presents a novel multi-level nonlinear heterogeneous consensus control scheme to optimize the utilization of distributed energy sources and renewable energy resources under both fixed and dynamic communication scenarios. It validates the proposed model through extensive simulations and case studies conducted in MATLAB and JADE. Moreover, this work compares the performance of the proposed approach with state-of-the-art classical method, stochastic programming, model predictive control, and mixed linear programming techniques. The results of these techniques are evaluated and observe the superiority of the proposed approach. Decentralized coordination control results in energy savings of 21.4% through coordinated demand response schemes. Additionally, the proposed scheme surpasses other approaches in terms of active power sharing and delivering 14.2% more energy savings by effectively integrating energy storage sources and electric vehicles. Notably, the proposed approach achieve an impressive energy efficiency of 98.2% compared to 2% of other approaches. This remarkable efficiency translates to a 19% increase in energy storage capacity through multi-level coordination. This work further validates the practicality and feasibility of our proposed scheme to integrate distributed energy sources and renewable energy resources for sustainable and scalable energy models.