Optimal Scheduling of Programmable Appliances for Demand Management in Energy Communities

Increasing the share of Renewable Energy Sources (RES) in energy consumption is perceived today as essential to decarbonizing energy systems. In this context, the Renewable Energy Communities (RECs) have been recently introduced to create a more decentralized energy system, where each member may share RES-based energy production to increase local self-consumption. To maximize the benefits for each member, the RES-based energy generation should match the demand. Thus, demand management may contribute in this regard by introducing load-shifting for the electric appliances used by REC's members. In this view, different modeling approaches are proposed as Mixed Integer Linear Programming and Mixed Integer Quadratic Programming. Solutions can be used to suggest possible changes to the end-users' current habits. Simulations are performed to compare energy, economic, and environmental Key Performance Indicators, including self-consumption, self-sufficiency, and CO2 emission savings.