A Tri-Layer Optimization Framework for Day-Ahead Energy Scheduling Based on Cost and Discomfort Minimization

Over the past few decades, industry and academia have made great strides to improve aspects related with optimal energy management. These include better ways for efficient asset management, generating opportunities optimization of distribution, discomfort minimization, production, cost reduction more. This paper proposes a framework multi-objective analysis, acting as novel tool that offers responses management through decision support system. The novelty is in structure methodology, since it considers two distinct problems actors, consumers aggregators, solution being able completely or partly interact other one form demand response signal exchange. overall formulated by bi-objective problem consumer side, aiming at minimization reduction, single objective aggregator side minimization. consists three architectural layers, namely, consumer, system (DSS), forming tri-layer multiple interacting objects, such functions, variables, constants constraints. DSS layer responsible forecasting day-ahead requirements. main purpose this study achieve resources, considering both preferences goals, whilst abiding real-world conducted detailed simulations using real data from pilot, part Terni Distribution System portfolio.