Measuring the long-term impact of wind, run-of-river, solar renewable energy alternatives on market clearing prices

Fazıl Gökgöz and Öykü Yücel

Renewable Energy, 2025, vol. 241, issue C

Abstract: This study uses fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), canonical cointegrating regressions (CCR), and quantile regression to investigate the long-term association of solar, wind and run-of-river technologies with market clearing prices in the Turkish day-ahead market. The models are applied individually for each hour from January 2019 to December 2023. The quantile regression analysis covers a total of 9 quantiles. The findings show that wind and run-of-river technologies exhibit a negative long-term relation with market clearing prices (MCP). This influence is highest at the lower and upper quantiles. Regarding solar energy, there is a negative association with MCP during noon, when sunlight intensity is highest. Throughout other hours, solar generation displays both negative and positive coefficients across various quantiles. The overall long-term association is stronger for run-of-river technology, followed by wind and solar technologies. The main takeaway for policymakers is that if there is an adequate generation, renewable energy support incentives benefit the day-ahead market. The policymakers should consider additional support mechanisms, particularly those not directly tied to price caps, to encourage solar technologies.

Keywords: Financial modelling; FMOLS; DOLS; CCR; Quantile regression (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:241:y:2025:i:c:s0960148124023607

DOI: 10.1016/j.renene.2024.122292

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