The deployment of large numbers of plug-in electric vehicles (PEVs), in order to satisfy zero-emission-vehicle (ZEV) goals in the State of California, brings both potential benefits and costs for the electric grid. Since early 2009, the issue of so-called vehicle-grid integration (VGI) has become a center-stage policy discussion among the electricity and transportation sectors. This dissertation encompasses three studies related to VGI. By conducting a policy process analysis, the first study addresses the questions of how the policy process for VGI regulations has been formed in California, and what have been the major challenges in policy-making. The results show that a policy window for VGI was opened for the first time by the political stream, through State Senate Bill 626 in 2009, and later, supported by the Governor’s ZEV action plan in 2012. These legislations gave California Public Utilities Commission (CPUC) the authority to implement regulations on enabling PEV load management systems and PEV-based grid services. In response, Energy Division Staff at CPUC became a policy entrepreneur, and has adopted an incremental policy-making strategy targeting investor-owned utilities (IOUs). The two largest barriers facing an effective policy solution are identified as; (1) the complexities involved in quantifying economic value from VGI; and (2) the feasibility concerns about adopting VGI enabling technologies on the grid. The second study focuses on the VGI feasibility issues mentioned above. This study provides a feasibility assessment, focusing on technical and market challenges in VGI. The results show that both, technical and market challenges exist in each of the load management strategies. The findings feature a list of technical and market challenges that need to be taken into consideration by stakeholders in VGI-related decision-making. Finally, the third study develops a stochastic-systems approach to VGI modeling where PEV load management strategies are compared for their economic value to PEV consumers and their local utility companies. The proposed methodology provides several improvements to the VGI modeling literature. These improvements include combining assessments for generation and distribution systems in the same model, and advancing uncertainty analysis for PEV consumer behavior considering real-world data sets.

This study develops a stochastic-systems approach in modeling vehicle-grid integration (VGI), where load management strategies can be compared in terms of their economic value to plug-in electric vehicle (PEV) consumers and their local utility companies. The proposed methodology is demonstrated in an assessment of VGI for the Sacramento Municipal Utility District (SMUD) in California. Monte-Carlo simulations have been performed to randomly assign PEV charging characteristics of the households based on given statistical distributions. Consumer adoption of time-of-use (TOU) rates is modeled as an optimization problem where consumers seek the earliest PEV charge start time among the charge schedules resulting lowest cost and satisfying their transportation needs. The preliminary results show that, considering today’s grid system, the deployment of 60,000 PEVs in Sacramento Region will have significant but manageable impacts. These impacts included increasing annual peak demand by 86MWs (5%), and overloading up to 101 neighborhood transformers in the distribution system. On the other hand, adopting proper TOU rates presents a high potential for minimizing these negative impacts of widespread PEV deployment on the grid. The proposed methodology provided several improvements to the VGI modeling literature. These improvements included combining assessments for generation and distribution systems in the same model, and advancing uncertainty analysis for the PEV consumer behavior with considering real world data sets.

This empirical study first identifies vehicle-grid integration (VGI) strategies as discussed by stakeholders in California, then, provides a feasibility assessment for these strategies focusing on technical and market challenges. VGI strategies presented in this paper include four components: (1) plug-in electric vehicle (PEV) load identification and tracking; (2) choice of a load management strategy, (3) deployment of enabling technologies, and, finally, (4) providing grid services and compensating participants. The assessment is performed based on a qualitative analysis of expert opinions gathered by a series of stakeholder interviews. These interviews were conducted with representatives of 18 organizations from the government, electric utility, and PEV sectors. The participants expressed their opinions about potential VGI strategies based on personal or company experiences. The qualitative data is analyzed under three categories of load management, which include dynamic pricing, demand response, and energy storage. The results show that both, technical and market challenges exist in each of the load management strategies, except the most basic dynamic pricing strategy. This strategy, which provides special time-of-use rates for PEV-owner households, is currently being implemented by all major utilities in California. The findings also feature a list of technical and market challenges that need to be taken into consideration by stakeholders in VGI-related decision-making.

The deployment of large numbers of plug-in electric vehicles (PEVs), in order to satisfy zero-emission-vehicle (ZEV) goals in California, brings both potential benefits and costs for the electric grid. Since early 2009, the issue of so-called vehicle-grid integration (VGI) has become a center-stage policy discussion among the electricity and transportation sectors. By conducting a policy process analysis, this research addresses the questions of how the policy process for VGI regulations has been formed in California, and what have been the major challenges in policy-making. A series of interviews were conducted between with representatives of 18 organizations from the government, electric utility, and PEV sectors. The qualitative data is analyzed under the three dimensions of policy process; problem, politics, and policy as suggested by Multiple Streams framework (Kingdon, 1995). The results show that a policy window for VGI regulations was opened for the first time by the political stream, through State Senate Bill 626 in 2009, and later, supported by the Governor’s ZEV action plan in 2012. In response, the California Public Utility Commission became a policy entrepreneur, and has adopted an incremental policy-making strategy targeting investor-owned utilities (IOUs). The two largest barriers facing an effective policy solution are identified as the complexities involved in quantifying economic value from VGI and the feasibility concerns about adopting VGI enabling technologies on the grid.