Extracting probability distribution functions applicable for PHEVs charging load profile

Abstract

Concerns over the adverse environmental impact of conventional vehicles have led to cleaner and more efficient vehicle technology. Plug-in hybrid electric vehicles (PHEVs) are the most promising approach to reducing petroleum use. While PHEVs partially rely on the electricity from the power grid, they raise concerns about their negative impacts on power generation, transmission, and distribution installations. The impacts of PHEVs on the power grid cannot be examined thoroughly unless extensive data on the utilization of each individual PHEV are available. For instance, in order to estimate the aggregated impact of PHEVs on the electricity demand profile, one needs to know i) when each PHEV would begin its charging process, ii) how much electrical energy it would require, and iii) what level of power would be available. Uncertainty regarding the above factors makes the researchers to come up with a series of probability distribution functions (PDFs). This paper extracts and analyzes the data that are available through national household travel surveys (NHTS). Based on 40,000 vehicle trips, probability distribution functions for arriving time and the required energy of PHEVs are extracted. Also, the probabilistic and deterministic PHEV charging load profiles are built and compared.