Multi-vector energy management system including scheduling electrolyser, electric vehicle charging station and other assets in a real scenario

Today, in the field of energy, main goal is to reduce emissions with aim maintaining a clean environment. To energy consumption from fossil fuels, new tools for micro-grids have been proposed. In context multi-vector management systems, present work proposes an optimal scheduler based on genetic algorithms manage flexible assets system, such as storage and manageable demand. This tool applied case study Spanish technology park (360 kW peak) photovoltaic wind generation (735 peak), hydrogen production (15 kW), electric fuel cell charging stations. It provides hourly day-ahead scheduling existing assets: electrolyser, vehicle station, refuelling heating, ventilation, air conditioning system one building park. A set experiments carried out over period 14 days, using real data performing computations time, order test validate tool. The analysis results show that solution maximises use local renewable (demand shifted those hours when there surplus generation), which means reduction costs, whereas computational cost allows implementation time. • paper algorithm implementing controlling different assets. proposed scheme performs 24-hour micro-grid. Assets conditioning; station; electrolyser; station are scheduled paper. includes done installations be pilot.