EECS Seminar: EV Charging Station Planning Based on POI and Historical Transaction Data

McDonnell Douglas Engineering Auditorium (MDEA)
Shuai Lu, Ph.D.

Founder and CEO, EnerMod

Abstract: Electric vehicles (EVs) are becoming a preferred transportation choice in many countries because of limited petroleum reserves and the environmental impacts of internal combustion engines (ICE). A major obstacle for EV adoption in China is that the number of EV charging stations is still too few to make EV charging as convenient as filling up ICE vehicles. With private parking space being scarce in big cities, building public charging stations in the right places is key to the growth of EV penetration. The focus of this work is to develop an optimal process for the planning of charging stations. The first problem in the process is to determine charging requirement of the EVs in the planning region. A model that considers population, geographic information, road network (POI) data and historical EV charging transaction data is developed to predict the distribution of charging requirements with respect to time and locations. The planning of charging stations considers both the interest of charging station investors and the convenience of EV drivers. An optimization problem is formulated, where the locations and charging capacity are decision variables, and the best cost benefit ratio is the objective. The problem is solved by combined genetic algorithm and mixed integer programming. Actual transaction data of charging stations in Beijing, China, has been analyzed and then used together with POI data to test the proposed planning approach. The study shows that the proposed approach can yield reasonable planning results, and a software program based on this approach has been deployed on the Connected EV Platform by the State Grid Corporation of China.

Bio: Shuai Lu founded EnerMod in 2015. The company provides software and consulting services in power grid and microgrid planning and operations, particularly with the integration of renewables and DERs. Prior to this endeavor, Lu led research efforts in power grid operations and DER modeling at the Pacific Northwest National Laboratory (PNNL). He orchestrated wind, PV or DER operation impact assessments for several U.S. power companies, including BPA, NV Energy and Duke Energy. Before joining PNNL in 2006, Lu developed digital control systems for static VAr compensators and designed undersea power delivery circuits. Lu has over 50 peer-reviewed publications.He received his bachelor's and master's degrees from Tsinghua University in China, and his doctorate from the University of Washington in the U.S., all in electrical engineering.

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