Myopic Optimization Models for Simulation of Investment Decisions in the Electric Power Sector

Generation expansion planning models optimize investment and operational decisions over a time horizon of multiple decades, thereby typically assuming perfect foresight (PF). Recently, myopic optimization models, in which the foresight is restricted to a certain period, have been suggested to more realistically simulate the short-sightedness of investment decision makers. The literature has shown that the modeled level of foresight can have a significant impact on the results obtained. However, the literature does not contain an in-depth analysis of the investment decision making process in myopic optimization models. As a result, the implications of using myopic optimization models to simulate the decision making of private agents in liberalized electricity markets are unclear. This paper provides fundamental methodological insights into the decision making in both PF and myopic optimization models. The projections, at the time the investment decision is made, of the short-run profits that can be obtained by investing in a generation asset are analyzed in this regard. This analysis reveals a major limitation of the decision making process in myopic optimization models, i. e., the approach does not extrapolate trends, in terms of changes in the projected SR profits, expected within the window of foresight to later periods. This leads to decision making which cannot be considered to reflect reality.