A novel demand side management strategy on electric vehicle charging behavior

Demand side management (DSM) is a classic topic which has been investigated for the last decade and further developed to embrace the emerging of electrical vehicles nowadays. The dramatic increasing number of electric bicycles in China in recent years has brought difficult issues to electric engineering, such as the soaring cost and inefficient usage of electric power. To solve such issues, in this paper, we propose an optimization problem targeting on automatically manage electric bicycles charging behaviors based on Time of Day (TOD) pricing and daily based load shifting in both peak time and non-peak time. Apart from that, a instruction based SDM strategy has been developed to specify the details of our pricing and load shifting techniques based on the optimization, we hereby name the strategy as Optimal Load Shifting and Pricing scheme (OLSP). Based on real time and spatial data, we successfully simulate the optimal daily power load on behalf of electric bicycles consumers side in Chinese City, Nanning. The numerical results show our proposed mathematical programming method provides dramatic gain in energy efficiency and reduction on electricity cost compared to traditional customer side greedy behaviors load assignment.