Abstract
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.
Highlights
In the development of social and economic situation of a country, energy plays a vital role
Energy market management controller (EMMC) will get power and price data from distributed generations (DGs) consisting of Utility that will share this data with Home Energy Management Controller (HEMC) to schedule the load and storage system
Proposed work has been implemented on microgrid based community, details are given in Appendix
Summary
In the development of social and economic situation of a country, energy plays a vital role. Decision making controller proposed in [3], optimally manages generation, load and storage. A multi-objective optimization is proposed in [10], to solve the energy management based economic and environmental problem for MG using Mixed Integral Linear Programming (MILP). The literature review of related work indicates that researchers have solved technical issues i.e. user comfort, consumption, generation, storage and trading etc. Proposed approach suggests intelligent trading mechanism based on consumers economic situation, load utilization and reducing gas emissions. This work proposes cost and GHG minimization using demand response (load control) while maximizing the utilization of local resources. Priority based energy trading within community, utility and distributed generation is integrated to meet energy deficiency and to sell surplus energy This is categorized as pricing scenarios, power utilization patterns and minimizing the emissions. State of the device x and type y, 1for ON and 0 for OFF Utilization of local generation
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
