DEVELOPMENT OF AN ALGORITHM TO EVALUATE THE PERFORMANCE AND ECONOMIC FEASIBILITY OF EXPANSION OF SOLAR AND WIND POWER GENERATION IN THE APPALACHIAN REGION

Author:

McCullough Ashley,Bischof Lillian,Alexander Ronald,Agbleze Selorme,Lima Fernando V.

Abstract

The United States is dependent on fossil fuels for energy production because 12% of energy consumed in the US in 2021 was derived from renewable resources as cited by the US Energy Information Administration. Some regions present strong capabilities for renewable energy systems to offset the use of fossil fuels and satisfy increasing energy demands. To expand renewable energy infrastructure in the US, the feasibility and locational applicability of these systems must be studied concurrently. The objective of this article is to propose an algorithm that sites and provides economic indicator estimates for potential large-scale renewable generation facilities. Through this algorithm, potential sites are selected, based on solar or wind energy potential as estimated by the EPA RE-Powering Initiative, and validated using the System Advisor Model (SAM). Then, recorded interval demand and pricing for the site's region is collected in AVEVA PI. Leveraging approximate plant sizing, relevant weather data, and plant specifications, plant operations are simulated in SAM. When paired with realistic Power Purchase Agreement prices, estimates of financial and energy-generation metrics are obtained. This proposed algorithm is accompanied by case studies in Appalachia. Results show that selected sites could have a nominal levelized price of electricity below the national average, highlighting the potential for these sites to sell at competitive market prices. Due to the accuracy of this algorithm, such models could be combined with fossil fuel power plants to develop a real-time optimization framework and provide realistic ramping rates for advanced control studies of fossil fuel power plants in the future.

Publisher

Begell House

Reference22 articles.

1. AVEVA, AVEVA PI System, AVEVA, accessed May 29, 2023, from https://www.aveva.com/content/dam/aveva/documents/brochures/Brochure_AVEVA_PI-System_22-06.pdf.coredownload.inline.pdf, 2022.

2. Bischof, L., Alexander, R., and Lima, F.V., Modeling of Solar and Wind Power Plants in West Virginia Using System Advisor Model (SAM), 2021 AIChE Annual Meeting, Boston, MA, 2021.

3. Bischof, L., Alexander, R., and Lima, F.V., Modeling and Economic Optimization of Solar Power Plant Expansion in West Virginia Using System Advisor Model (SAM), 2022 AIChE Annual Meeting, Phoenix, AZ, 2022.

4. James, J. and Hansen, E., Prospects for Large-Scale Solar on Degraded Land in West Virginia, Downstream Strategies, accessed Aug. 03, 2021, from http://downstreamstrategies.com/documents/reports_publication/utility-scale-solar-report_2-21-17.pdf, 2017.

5. Kim, R., Wang, Y., Vudata, S.P., Bhattacharyya, D., Lima, F.V., and Turton, R., Dynamic Optimal Dispatch of Energy Systems with Intermittent Renewables and Damage Model, Mathematics, vol. 8, no. 6, p. 868, 2020. DOI: 10.3390/math8060868

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