Multi Objective Based Framework for Energy Management of Smart Micro-Grid

• Published in: IEEE access 2020, Vol.8, p.220302-220319
• Main Authors: Haseeb, Muhammad, Kazmi, Syed Ali Abbas, Malik, M. Mahad, Ali, Sajid, Bukhari, Syed Basit Ali, Shin, Dong Ryeol
• Format: Article
• Language: English
• Subjects: Control agent; Controllers; Distributed generation; Economic conditions; Economics; Electrical loads; Energy industry; Energy management; energy market management controller; Heuristic methods; Home appliances; home energy management controller; local generation; market management; micro-grid; multi objective grey wolf optimization; Particle swarm optimization; Pricing; Priorities; renewable energy resources; Residential energy; Schedules; Smart grids; Task analysis; Wind turbines
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3041473

The increasing demand of energy in the traditional grids is getting more complex, less feasible, harmful, uneconomical and high in power losses. This paper presents an efficient energy management approach to mitigate such issues with smart micro grid (SMG) and aims at a solution that is both cost effective and eco-friendly, within energy market paradigm. Goals are achieved with the help of Home Energy Management Controller (HEMC), Energy Market Management Controller (EMMC) and Control Agent (CA). The individual load is managed in the presence of local generation, storage system, user comfort, DGs and Utility within energy market paradigm. Two level energy management approach is proposed to achieve concerned goals. First is to manage load and schedule storage with respect to individual local generation and market pricing. Second is to manage energy market with the help of four different types of priorities and control agent input. The problem is solved with a variant of meta-heuristic method, Multi Objective Grey Wolf Optimization (MOGWO), which gives more comprehensive solution by comparing with Particle Swarm Optimization (PSO). The proposed methodology is implemented on a SMG based-community test system. Homes within that community have different economic conditions and personal priorities. Simulation results demonstrates achievement of aimed goals in presented work.