Non-sequential Monte Carlo simulation tool in order to minimize gaseous pollutants emissions in presence of fluctuating wind power

In this paper, an original non-sequential Monte Carlo simulation tool is developed. This tool permits to compute the optimal dispatch of classical (coal, oil, etc.) thermal generation in order to minimize polluting gases (NOx, CO2, etc.) emissions in presence of wind power and under constraints. These constraints include, e.g., the maximal generation cost or the ability of the electrical system to cover the load, … In comparison with existing analytical tools that are based on restrictive hypotheses when it comes to wind power modelling (generally represented by a single entirely correlated global wind park), unexpected outages of conventional parks or fluctuating representation of the load, the use of Monte Carlo simulation allows to remove all those limitations. Indeed, thanks to the developed tool, the optimal dispatch of classical thermal generation can be reached under several load conditions. Well-known reliability indices can also be computed and, moreover, following the wind speed sampling that is used, entirely correlated, independent or more accurate correlation level between wind parks can be considered. Finally, it is thought that the proposed solution can be a useful tool for electrical system operators in order to dispatch the polluting thermal units under cost, reliability, emissions, fluctuating wind power and unexpected outages constraints.

► Development of a Monte Carlo simulation tool to minimize pollutants emissions.
► Random behaviour of wind generation and of hourly load taken into account.
► Long-term impact of wind power on the grid adequacy and on pollutants emissions.
► Great help for electrical system operators.
► Adequate dispatch of the classical generation with wind power and under constraints.