IAEE Members and subscribers to The Energy Journal: Please log in to access the full text article or receive discounted pricing for this article.

The Costs of Electricity Systems with a High Share of Fluctuating Renewables: A Stochastic Investment and Dispatch Optimization Model for Europe

Renewable energies are meant to cover a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions. In this article, we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include a lower value of fluctuating renewables and higher system costs compared to deterministic investment and dispatch models. Furthermore, the value of solar technologies is--relative to wind turbines--underestimated when neglecting negative correlations between wind speeds and solar radiation.

Purchase ( $25 )

Energy Specializations: Energy Modeling – Energy Data, Modeling, and Policy Analysis; Energy Modeling – Sectoral Energy Demand & Technology; Electricity – Generation Technologies; Electricity – Markets and Prices ; Renewables – Policy and Regulation

JEL Codes: Q42: Alternative Energy Sources, Q41: Energy: Demand and Supply; Prices, Q54: Climate; Natural Disasters and Their Management; Global Warming, Q35: Hydrocarbon Resources, C51: Model Construction and Estimation, C53: Forecasting Models; Simulation Methods

Keywords: Stochastic programming, Electricity, Renewable energy

DOI: 10.5547/01956574.34.4.8

References: Reference information is available for this article. Join IAEE, log in, or purchase the article to view reference data.

Published in Volume 34, Number 4 of the bi-monthly journal of the IAEE's Energy Economics Education Foundation.


© 2022 International Association for Energy Economics | Privacy Policy | Return Policy