Impact of uncertain data in robust optimal bidding of RVPP in energy and reserve markets

Abstract

Different probability distributions yield different outcomes of optimization problems under uncertainty such as the optimal bidding problem of RES-only Virtual Power Plant (RVPP). Robust Optimization represents uncertainties by sets, which are parameterized according to the assumed underlying probability distributions. This paper analyzes the impact of uncertain data related to energy and reserve market prices as well as non-dispatchable renewable production and demand on the outcomes of the optimal RVPP electricity market bidding problem. Different parameters related to the accuracy and shape of data forecast are analyzed and their impact on the RVPP bidding strategy is obtained by sensitivity analysis.

Different probability distributions yield different outcomes of optimization problems under uncertainty such as the optimal bidding problem of RES-only Virtual Power Plant (RVPP). Robust Optimization represents uncertainties by sets, which are parameterized according to the assumed underlying probability distributions. This paper analyzes the impact of uncertain data related to energy and reserve market prices as well as non-dispatchable renewable production and demand on the outcomes of the optimal RVPP electricity market bidding problem. Different parameters related to the accuracy and shape of data forecast are analyzed and their impact on the RVPP bidding strategy is obtained by sensitivity analysis.