100 / 2017-08-13 15:34:54

An Intelligent Energy Management System for Renewables-based Virtual Power Plant

5726,15366,442,15368,15370

With the rapid development of the emerging technologies and significant cost reduction of the deployment for solar energy and wind power, the replacement of traditional power generation by renewable energy becomes feasible in the future. However, different from currently deployed centralized power sources, renewables are categorized as one kind of intermittent energy sources, and the scale of renewables is small and scattered. In the recent literature, the architecture of virtual power plant was proposed to replace the current smart grid in the future. However, the energy sharing concept and the uncertainties of intermittent energy sources will cause the short-term energy management for the future virtual power plant much more complicated than current centralized control energy management for traditional power generation system. To the best of our knowledge, no researcher has addressed on the above-mentioned short-term energy management problems for the future virtual power plant so far. Accordingly, a hierarchical day-ahead energy management system based on the architecture of virtual power plant is proposed in this work to tackle the complex energy management problems. We first collect electricity consumption data from smart appliances used in households and predict power-generating capacity of renewable energy sources at the prosumer level. Then, the proposed hierarchical energy management system is employed to schedule the usage of electricity for the customers by considering the efficiency of the use of distributed renewables. Notably, a reallocation mechanism is presented in this work to allocate excess electricity generated in a community virtual power plant to others facing with power supply shortage, and the maximal usage of renewables and reduction of the burden on community virtual power plants during time period of peak load can be achieved accordingly. The experimental results show that the hierarchical day-ahead energy management system proposed in this work can mitigate the dependency on community virtual power plants effectively, and balance peak and off-peak period load of electricity market.