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Model Shows Clean Power Plan Can Have Minimal Cost Impact on Virginia Ratepayers

Posted by Advanced Energy Economy on Jan 20, 2016

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Model Shows Clean Power Plan Can Have
Minimal Cost Impact on Virginia Ratepayers

Cheapest way for Virginia to comply is using energy efficiency and renewables;
even lowers electric rates under some scenarios

[Washington, D.C. – January 20, 2016]: Implementing the U.S. Environmental Protection Agency’s Clean Power Plan would have minimal impact on electricity costs in Virginia, and could even provide savings for ratepayers under some scenarios, compared with projected energy costs in 2030. Those are the findings of scenarios run through a new analytic tool developed for the Advanced Energy Economy Institute and applied to Virginia. The open-access tool is available for free to help state officials and other stakeholders consider compliance options and their economic impacts.

Modeling Low Cost Approaches to Clean Power Plan Compliance for Virginia,” published today by the AEE Institute, presents the results of two specific scenarios that are representative of multiple runs of the new State Tool for Electricity Emissions Reduction (STEER). The demonstrated scenarios are based on varying considerations, but find that, the least expensive way to reach EPA’s prescribed emission targets includes a significant amount of energy efficiency and renewables and does not include any additional plant retirements beyond those already announced.

“STEER is an extremely valuable tool for understanding the options available to Virginia for complying with the Clean Power Plan,” said Malcolm Woolf, Senior Vice President for Policy and Government Affairs for Advanced Energy Economy (AEE), a national business association. “It shows that, under a wide variety of scenarios, energy efficiency and renewable energy are the cheapest ways to meet the Clean Power Plan targets with minimal impact on electric rates, and even saving money for ratepayers under some circumstances.”

The analysis is available for download here, as is the STEER-Virginia model, which allows users to use publicly available data on Virginia energy demand and resources to assess the cost impact of compliance options, just as electric utilities are able to do.

“STEER is an easy-to-use tool that allows state officials and other interested parties to identify the lowest cost path to Clean Power Plan compliance under a variety of assumptions,” said Matt Stanberry, Vice President of Market Development for AEE and head of analytics for the affiliated AEE Institute.

For each scenario of assumptions run through the tool, STEER identifies the combination of generation sources, efficiency improvements, and other measures that represents the lowest cost means of meeting the state’s electric power needs in 2030 while complying with Clean Power Plan standards for Virginia. The compliance period established by EPA for the carbon emission regulation begins in 2022, with final standards for carbon emissions from the electric power sector in each state in 2030.

In the two scenarios detailed in the paper, Virginia is able to reach compliance with the Clean Power Plan in 2030 with minimal increases or small savings in electricity prices compared with a business-as-usual projection of electricity costs for that year. The two scenarios hold constant assumptions about natural gas prices (setting natural gas at the U.S. Energy Information Administration’s 2030 projection of $6.73/MMBtu) and do not consider the option of trading emission allowances or credits, although STEER can be used to calculate the effect of such variations. As STEER shows that Virginia can easily meet its target, the state could generate additional credits for sale to other states. Both scenarios also assume growing electricity demand in the Commonwealth as projected by PJM, the regional grid operator.

Under both scenarios, coal and natural gas capacity remain unchanged, meaning there are no additional plant retirements compared to business-as-usual. Despite the assumption of additional load growth in Virginia, there is an overall decrease in generation under both scenarios, due to increases in energy efficiency, with coal and natural gas generation decreasing and renewable generation increasing. Under Scenario A, there is a substantial expansion of renewable capacity, in particular solar, while there is very little additional renewable capacity added under Scenario B. The primary difference between the two scenarios is the role played by energy efficiency in least-cost compliance.

Under Scenario A, which uses Dominion Virginia’s recent estimates of energy efficiency potential, least-cost compliance in 2030 would be achieved by substantial amounts of new renewable energy and energy efficiency, with a small amount of switching from coal to natural gas generation. This scenario achieves Clean Power Plan compliance with just a small rate increase ($0.004/kWh, or less than half a penny per kilowatt-hour) over business-as-usual.

Scenario B holds other assumptions constant, but relies on the Virginia State Corporation Commission’s energy efficiency study, which finds even more potential for energy savings. Under Scenario B, there is also no change to the state’s existing fossil-fuel generating capacity beyond business-as-usual. Scenario B finds that efficiency improvements are sufficient for nearly all of Clean Power Plan compliance, with just a small amount of new renewable energy and coal-to-gas switching. Under this scenario, Clean Power Plan compliance actually saves money, with rates in 2030 reduced slightly ($0.002/kWh) compared with business as usual.

STEER was developed by the University of Michigan and 5 Lakes Energy for the AEE Institute. STEER is being delivered to a number of states as a free, open-access model so that anyone with an interest in thinking about the Clean Power Plan will have access to the necessary data and calculations for an informed analysis. First developed for application to EPA’s Clean Power Plan as it was proposed in June 2014, STEER has been revised to account for the changes made by EPA in finalizing the carbon emissions rule. 

STEER for VIRGINIA is available for download as an Excel spreadsheet, with user manual, at http://info.aee.net/steer-virginia. After downloading the model, evaluating any scenario takes only a few minutes, enabling the user to develop a deeper understanding of the tradeoffs involved in various approaches to implementing the Clean Power Plan. STEER optimizes for least cost and analyzes the economic impacts of compliance, including rate impacts to multiple customer classes. The model has a default set of data, which is composed of publicly available data for Virginia; however, a user can incorporate more granular data if available.

Background Materials:
STEER models and analyses are available for Ark., Ill., Mich., Penn., and Va. here.

Learn more with "This Is Advanced Energy," a directory of 52 technologies here.

About Advanced Energy Economy Institute
The Advanced Energy Economy Institute is a 501 (c)(3) charitable organization whose mission is to raise awareness of the public benefits and opportunities of advanced energy. AEE Institute provides critical data to drive the policy discussion on key issues through commissioned research and reports, data aggregation and analytic tools. AEE Institute also provides a forum where leaders can address energy challenges and opportunities facing the United States. AEE Institute is affiliated with Advanced Energy Economy (AEE), a 501(c)(6) business association, whose purpose is to advance and promote the common business interests of its members and the advanced energy industry as a whole. AEE and its State and Regional Partner organizations are active in 26 states across the country, representing more than 1,000 companies and organizations in the advanced energy industry. 

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Media Contact:

Monique Hanis
Director, Media Relations & Publications
Advanced Energy Economy
The business voice of advanced energy

1000 Vermont Ave., N.W., Third Floor, Washington, D.C. 20005
O: 202-391-0884 | mhanis@aee.net | www.AEE.net | @AEEnet @GreenerMonique


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