Optimization and operational management of renewable Goldwind Microgrid test bed

Microgrid comprises of versatile type of alternate energy resources in order to distribute electricity economically, effectively and securely. In this study, the energy demand of Goldwind smart industrial park demand is forecasted and optimized based on daily load, wind and PV generation system using three techniques. PSO-NN, VAR for Forecasting and GA for optimization algorithm. The complete generation model consist of wind, PV, Vanadium redox flow Battery and Microturbine Generator. The system is based on an hourly operating cost to meet the electricity demand of a smart park located in Beijing. An objective relation is built by using all the constraints and then optimize the battery charging and discharging time as well as power trading between the utility and the Goldwind Microgrid test bed. The model is validated on the real time test window of approximately one month.