Capacity Budgeting: Investments in Renewable Energy Resources
Problem: The output of renewable energy resources (RES) is very erratic and heavily depending on meteorological influences (e.g. wind velocity and solar irradiance). Such high volatilities and weather dependencies are of main importance, when planning the capacity of RES investments. For this purpose, the portfolio selection theory (Markowitz) applied in the Finance domain is not adequate. On one side, the investment amount (volume) is not fixed, but has to be determined. On the other side, the meteorological influences and their stochastic developments are too complex for being modeled with a 1-period rate of return.
Research Method: Instead of following the practical approach of using Exceedance Probability as risk measure, the Minimum Exceedance Probability (MEP)-Framework is applied. In this framework the ‚Chance Constraint Programming‘ optimization (Charnes/Cooper) is combined with the ‚Sampling and Discarding‘ algorithm (Campi/Garatti) in order to allow a ‚Linear Programming‘ solution. By using empirical meteorological data from the location under consideration, geographically optimal capacity volumes for RES investment are derived.
Ondra/Schwaiger/Eigruber: Direct investments in renewable energy portfolios – Stochastic NPV-based capacity budgeting, Conference on Energy, COVID, and Climate Change, Online, International Association of Energy Economics (IAEE), 2021.
Schwaiger/Eigruber: Autarcic Energy @ Home – Geografisch optimale Kapazitätsplanung von Investitionen in erneuerbare Energien mit dem MEP-Framework, WINGbusiness 1/22, Graz, 2022.