Cost of Valued Energy for design of renewable energy systems. (June 2020)

• Record Type: Journal Article
• Authors: Simpson, Juliet; Loth, Eric; Dykes, Katherine
• Is Part Of: Renewable energy. Volume 153(2020)
• Page Start: 290
• Page End: 300
• Publication Date: 2020-06
• Subjects: LCOE -- Wind -- Solar -- LACE -- Net value -- Renewable energy; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2020.01.131
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: The design of renewable energy systems such as wind turbines or solar panels conventionally employs Levelized Cost of Energy (LCOE), but this metric fails to account for the time-varying value of energy. This is true both for a single turbine or an entire wind farm. To remedy this, two novel, relatively simple metrics are developed herein to value energy based on the time of generation and the grid demand: Levelized Avoided Cost of Energy simplified (LACEs) and Cost of Valued Energy (COVE). These two metrics can be obtained with: 1) a linear price-demand relationship, 2) an estimate of hourly demand, and 3) an estimate of predicted hourly generation data. The results show that value trends for both wind and solar energy were reasonably predicted with these simplified models for the PJM region (a mid-Atlantic region in the USA) with less than 6% error on average, despite significant stochastic variations in actual price and demand throughout the year. A case study with wind turbine machine design showed that increasing Capacity Factor can significantly reduce COVE and thus increase Return on Investment. As such, COVE and LACEs can be valuable tools (compared to LCOE) when designing and optimizing renewable energy systems. Highlights: LCOE is inadequate for valuing energy produced by a renewable energy system. Two new market-based cost metrics are proposed to improve upon LCOE: COVE and LACEs. A linear price-demand relationship provides a first-order value of energy. Return on Investment increases with wind turbine capacity factor (for a fixed LCOE).