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M. Eigruber, M. Ondra, W.S.A. Schwaiger:
"IAEE 2021";
Talk: IAEE - First International Online Conference: Energy, COVID, and Climate Change, Online (invited); 2021-06-07 - 2021-06-09.

This paper presents a stochastic Net-Present-Value based model for solving an investor's capacity budgeting problem. We consider an investor, who aims at finding the optimal levels of renewable energy technology investments within the Minimum exceedance probability (MEP) framework. In the MEP framework, the investor introduces a probabilistic constraint to evaluate the pro tability of a renewable energy portfolio, by requiring that the probability to obtain a NPV larger than a pre-speci fied threshold has to exceed an ex-ante speci fied confi dence level. As there are several investment levels and renewable energy portfolios that fu lfill this requirement an additional criteria has to be added for deriving the optimal solution. For this purpose the criteria of the minimal capital expenditure is taken. For solving the underlying Probabilistically Contraint Optimization (PCO) problem a numerical approach (the Sample Approximation) is applied. The modi fications of Markowitz's capital budgeting model are needed as in the direct investment domain the size of the investments is no longer fixed by the investor's initial wealth, but the investment levels have to be determined explicitly. The numerical approach to the PCO problem is data-driven so that no NPV distributions have to be assumed.