Stochastic Optimal Energy Management of Microgrid Based on Adaptive Neuro-Fuzzy Inference System by Transmission Line Power Control with D-FACTS Equipment

M Jirdehi, V Sohrabi Tabar, Msc Student, Hemmati
Tabriz Journal of Electrical Engineering   unpublished
This paper focus on optimal scheduling of microgrid based on adaptive neuro-fuzzy inference system including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical storage), and D-FACTS devices. D-FACTS are included in the line between main network and microgrid to achieve more power transfer to the upstream grid. In the proposed planning, wind speed, solar radiation,
more » ... loads are modeled as uncertain parameters based on the stochastic approach. Problem is expressed as a linear, mixed integer, constrained, and multi objective optimization aiming at minimizing cost and pollution at the same time. Operation improvement is illustrated in final results by considering D-FACTS as cost is decreasedto a considerable amount. Also, will be shown that simulation time will be decreased to a noticeable amount that can be applicable in large scale management systems by using adaptive neuro-fuzzy inference system.The proposed multi objective and stochastic problem is solved using augmented Epsilon-constraint method. All results and calculations are calculated using GAMS24.1.3CPLEX12.5.1.
fatcat:f24lcreplfcrvhcat2fqxu6nzq