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Project 21:
Effect of Electric Vehicles on Power System Expansion and Operation


Examine the effects of electric vehicles on electric power system design and operation. This work includes using an existing Hawaii developed model that will be validated against an established utility-scale model. The work will evaluate the benefits of optimally-timed EV charging and the requirements and costs of electric grid infrastructure to serve different types of vehicle fleets. It will also assist in evaluating the effects on battery life of battery duty cycles used in grid-to-vehicle and vehicle-to-grid applications.

Brief Description

This project will examine the effects of electric vehicles (EVs) on Hawaii's electricity systems and their operation and expansion. The tasks include four interrelated parts: (1) benchmarking an open-source power system planning model previously developed by University of Hawaii researchers against an industry-standard production cost model; (2) evaluating the benefits of scheduling EV charging at optimal times each day; (3) calculating the technical requirements and costs of electric grid infrastructure to serve different types of vehicle fleets; and (4) estimating battery duty cycles for grid-to-vehicle and vehicle-to-grid applications.

Research Results

Implementation of Research

Part 1. SWITCH is an open-source power system planning model previously developed by researchers at the University of Hawaii. It consists of a lightweight, hourly production cost model nested within a multi-decade capacity expansion model. SWITCH is designed to choose optimal plans for expansion and operation of power systems based on the hourly behavior of renewable resources, demand response, storage and conventional power plants. This work will benchmark SWITCH's production-cost modeling capabilities against results from GE MAPS, an industry-standard production-cost model, when considering a future Hawaii power system with large shares of renewable power and electric vehicles.

Part 2. The second part of this work will use both the capacity planning and production cost capabilities of SWITCH to calculate the economic benefits of charging EVs at optimal times. These benefits include obtaining a larger share of power from renewables and high-efficiency baseload generators, and reducing the need for new generation, transmission and storage capacity.

Part 3. The third part of this work will compare the effects of three different kinds of vehicle fleet on the power system: primarily traditional internal combustion engine vehicles (ICE), primarily pure-electric vehicles (EVs) or primarily plug-in hybrid electric vehicles. For each type of fleet, the research will use SWITCH to identify the grid infrastructure needed, the average cost of power for non-vehicle uses, and the average cost of providing transport. Various effects are possible and will be included in this assessment: for example, the extra load from EVs and PHEVs may force the system to adopt lower-quality and higher-cost renewable resources, raising costs compared to the ICE case; alternatively, well-timed charging of EVs and PHEVs could help with integrating large-scale renewable energy, reducing costs. The limited all-electric range of PHEVs may mean they shift less transport energy onto renewable sources than EVs do; on the other hand, PHEVs may reduce the need to build conventional power plants, since they can revert to gasoline-only mode on days when wind and solar power are scarce.

Part 4. The fourth part of this work will report duty-cycles for vehicle batteries used for inter-hour load shifting (charging at optimal times during their plugged-in period). This work will be an input for battery degradation analysis reported in other projects.

Completed Work

Part 1 - Benchmarking SWITCH vs. GE MAPS

Part 2 - Economic benefits of optimizing timing of EV charging

Future Work

Part 1 - Benchmarking SWITCH vs. GE MAPS

Part 2 - Economic benefits of optimizing timing of EV charging

Part 3 - Comparing the cost of ICE and EV fleets

Part 4 - Duty cycles for EVs providing grid support

Impacts/Benefits of Implementation

The increasingly popular SWITCH power system planning model has been rewritten to eliminate any dependencies on proprietary frameworks. SWITCH is now available as free and open-source software for all users. This allows any user to conduct state-of-the-art research on electric power system expansion and adaptation, based on hourly behavior of EVs and renewable energy.

Data for the SWITCH-Hawaii version of the model are also available for any users who want to study integration of EVs and renewable energy in Hawaii. Some members of the University of Hawaii Dept. of Economics are now using it to study the benefits of dynamic electricity pricing in Hawaii, working with Dr. Fripp.

Numerous additional capabilities have been added to the SWITCH modeling framework (spinning reserves; part-load heat rates; fuel markets; battery storage; modeling of arbitrary, high-complexity demand functions).

SWITCH has been used to provide technically grounded guidance to the Hawaiian Electric Company, regulators and other stakeholders as they make plans to meet the state's new 100% renewable electricity target by 2045.

Novel techniques have been developed to represent the charging requirements and flexibility of the EV fleet, based on first principles and nationally representative transportation surveys. Profiles of business-as-usual charging and fleet flexibility are now available for other users. Additional techniques have been developed to integrate these exceptionally rich profiles efficiently into power system production cost models and capacity expansion models.


M. Fripp; Development of SWITCH-Hawaii Model: Loads and Renewable Resources, Report Number: HI-13-16, August 2016.



Project Title:
Effect of Electric Vehicles on Power System Expansion and Operation

University of Hawaii

Principal Investigator:
Matthias Fripp

PI Contact Information:

Funding Source:
Research and Innovative Technology Administration
1200 New Jersey Avenue, SE
Washington, DC 20590

Denise Dunn

Total Project Cost:

Agency ID or Contract Number:

Start date:
October 1, 2013

End date:
September 30, 2018