Decision Support for Plug-in Hybrid Electric Vehicle Charging in a Power Market Setting with Uncertainty: Cost Saving Opportunities and Synergies with Wind Generation

EPA Grant Number: FP917156
Title: Decision Support for Plug-in Hybrid Electric Vehicle Charging in a Power Market Setting with Uncertainty: Cost Saving Opportunities and Synergies with Wind Generation
Investigators: Foster, Justin MacLeod
Institution: Boston University
EPA Project Officer: Zambrana, Jose
Project Period: September 1, 2010 through August 31, 2013
Project Amount: $111,000
RFA: STAR Graduate Fellowships (2010) RFA Text |  Recipients Lists
Research Category: Academic Fellowships , Fellowship - Science & Technology for Sustainability: Environmental Behavior & Decision Making


This project develops decision-making support tools, which utilize Smart Grid data and hold promise towards a sustainable energy future. It explores the complementary nature of certain clean energy technologies across industry sectors in order to promote economically feasible opportunities for joint market penetration. In particular, it examines the ability of flexible-load to optimally provide the fast reserve capacity necessary for substantial increases in wind generation, while maintaining the quality of service the general public demands from electric utilities.

Reduction in greenhouse gas emissions requires the incorporation of clean energy technologies in the transportation and electric power sectors, which will strain the existing energy infrastructure. Embedded in the Smart Grid platform is the ability to manage these technologies in a way to minimize the disruptive impact. This project develops the decision support tools necessary for the market-based coordination of intermittent renewable and distributed generation as well as demand response.


Preliminary research will focus on effective market-based coordination of plug-in hybrid electric vehicles (PHEVs) and renewable electricity generation — in particular, wind — that will contribute to the broad adoption of both technologies. Decisions must be managed and implemented across time-scales in the day-ahead market, intra-daily adjustment markets, and real-time market. The intermittent nature of wind generation requires additional capacity reserves, which can be called upon to insure the real-time balance of energy supply and demand. Given that fast reserve capacity prices range from $20 – $80 per megawatt-hour, these costs are likely to impose a significant barrier to wind generation expansion. In addition, the electrification of the light-vehicle fleet, in the absence of smart charging, will require costly distribution network infrastructure investments. This project will develop an optimal battery charging management strategy that will increase the supply of fast capacity reserves, thus controlling the costs, and result in energy cost savings for PHEV owners. This can be accomplished using load scheduling, which shifts demand in synchrony with system requirements and alleviates power system congestion in the transmission, distribution, and generation infrastructure.

Expected Results:

The project will include simulation of the optimal PHEV charging decision support methodology to provide an important component in the evaluation of the costs and benefits associated with the electrification of the U.S. light-vehicle fleet and increased penetration of intermittent clean energy generation. The ideas of ‘smart-charging’ and ‘smart-use’ can be adapted to other types of load management, as well as to the management of distributed generation. Findings will provide important insight into the changes in energy market design necessary for demand-side participation in reserve markets and expanded retail markets at the distribution level. The research can be applied towards the development of comprehensive plans for expanding the existing distribution network and aid in the delay of costly expansion projects. Finally, and perhaps most importantly, the research will offer insight into efficient investment in the cyber infrastructure embedded in the Smart Grid.

Potential to Further Environmental/Human Health Protection
High renewable generation adoption will have a downward effect on wholesale energy prices. PHEV batteries can also increase the supply of capacity reserves and lower costs. Thus, in addition to the positive environmental impact, the cumulative effect on electricity markets will be in the direction of more affordable electric energy for the general public. Moreover, implementation of the proposed methodology in other developed and developing countries holds promise for dramatic global effects on sustainable energy.

Supplemental Keywords:

sustainable power systems, renewable electricity generation, Smart Grid, demand-side response, decision theory, dynamic programming, optimization,