NETE A probabilistic economic/CO2eq emissions dispatch model: Real applications

The worldwide evolution of the electricsystems requires, i. a.: a) fossil-fuel generators with carboncapture and b) clean technologies based on renewableenergies. For this reason, dispatch centers are in constantsearch for solutions in order to improve decision-makingthat involve the generation matrix. Consequently, in thispaper a probabilistic economic dispatch model isproposed. The proposed methodology considersuncertainties, affecting the short–term control, theemission factors and the load dispatching. Wind speed,solar radiation and power demand are treated as randomvariables. Unavailability factors are also taken intoaccount. The solution strategy is based on the Monte Carlomethod and a bi-objective linear optimization constrainedprocedure.The approach involve multidimensional probabilities,descriptive statistics, clusters studies and bimodal analysis.The optimal solution yields the probability distributions ofsystem marginal prices, dual costs, load-shedding, thermaland renewable power generation and emission factors. Theproposed model and methodology are applied to theelectric power system of northern Chile.