Economic-Environmental Optimal Management of Smart Residential Micro-Grid Considering CCHP System

摘要

Due to issues such as air pollution and global warming, Distributed Energy Resources (DERs) including Distributed Generations (DGs), Energy Storage Systems (ESSs) and Demand Response Programs (DRPs) are gaining increasing attention to reduce dependency on fossil fuels as well as environmental pollution. In this article, a multi-objective optimization of economic environmental scheduling of DERs in a smart residential Micro-Grid (MG) considering numerous constraints and Demand Response Programs (DRPs) has been presented. To optimize the aforementioned objective functions, a new algorithm called Adaptive Fuzzy Multi-Objective Particle Swarm Optimization (AFMOPSO) has been proposed. This algorithm has a great capability to avoid local optimal solutions by finding a compromise between the general and local search within the decision making area. In addition, a comprehensive Combined Cooling Heating and Power (CCHP) system based on various thermodynamic equations has been proposed. The results demonstrate the efficient performance of the proposed algorithm compared to the other traditional optimization methods via some diversity and spacing criteria.