Abstract
Integrating massive electric vehicles (EVs) into the power grid requires the charging to be coordinated to reduce the energy cost and peak to average ratio (PAR) of the system. The coordination becomes more challenging when the highly fluctuant renewable energies constitute a significant portion of the power resources. To tackle this problem, a novel two-stage EV charging mechanism is designed in this paper, which mainly includes three parts as follows. At the first stage, based on the knowledge of future energy requests and considering the elastic charging property of EVs, an offline optimal energy generation scheduling problem is formulated and solved in a day ahead manner to determine the energy generation in each time slot next day. Then at the second stage, based on the planned energy generation day-ahead, an adaptive real-time charging strategy is developed to determine the charging rate of each vehicle in a dynamic manner. Finally, we develop a charging rate compression (CRC) algorithm which tremendously reduces the complexity of the problem solving. The fast algorithm supports real-time operations and enables the small-step scheduling more efficiently. Simulation results indicate that the proposed scheme can help effectively save the energy cost and reduce the system PAR. Detailed evaluations on the impacts of renewable energy uncertainties show that our proposed mechanism achieves a good performance in enhancing the system fault tolerance against uncertainties and the noises of real-time data.
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