Uncertainty Costs Optimization of Residential Solar Generators Considering Intraday Markets

Abstract

The uncertainty of solar generation and the bull market are unavoidable in energy dispatch. The purpose of this research is to validate an uncertainty cost function of residential photovoltaic energy in a real microgrid by varying the number of auctions in intraday markets. Therefore, the following procedure is proposed. First, the variability of photovoltaic generation is quantified through Monte Carlo simulations. Second, a statistical function calculates the variability costs of photovoltaic generation. Third, the uncertainty costs are estimated by varying intraday auction markets. Other complementary services are added to the network, such as battery exchange stations for electric vehicles, demand response loads, market power restrictions, and energy storage systems, which are estimated as total costs in an index ranking. The total costs are optimized in a benchmark microgrid and take complimentary services as a black box. Only the uncertainty costs of residential solar generators are discriminated. The main findings were that (1) the uncertainty costs have an error of less than 0.0168% compared to the Monte Carlo simulations and that (2) the uncertainty costs of solar generation are reduced with a decreasing trend to a more significant number of auction markets in intraday markets.