Optimization of power plant investments under uncertain renewable energy development paths - A multistage stochastic programming approach
Electricity generation from renewable energy sources (RES-E) is supposed to increase signi ficantly within the coming decades. However, uncertainty about the progress of necessary infrastructure investments, public acceptance and cost developments of renewable energies renders the achievement of political plans uncertain. Implementation risks of renewable energy targets are challenging for investment planning, because di fferent RES-E shares fundamentally change the optimal mix of dispatchable power plants. Speci cally, uncertain future RES-E deployment paths induce uncertainty about the steepness of the residual load duration curve and the hourly residual load structure. In this paper, we show how uncertain future RES-E penetrations impact the electricity system and try to quantify eff ects for the Central European power market. We use a multi-stage stochastic investment and dispatch model to analyze e ffects on investment choices, electricity generation and system costs. Our main findings include that the uncertain achievement of RES-E targets signi ficantly effects optimal investment decisions. First, a higher share of technologies with a medium capital/operating cost ratio is cost-efficient. Second, the value of storage units in systems with high RES-E penetrations might decrease. Third, in the case of the Central European power market, costs induced by the implementation risk of renewable energies seem to be rather small compared to total system costs.
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