Stochastic Multi-Objective Optimization of a Residential Microturbine-Driven CHP System Considering Probabilistic Reliability Constraint

Abstract

Abstract Recently, micro combined heat and power (M-CHP) systems have been increasingly used worldwide. M-CHP is supposed to play a meaningful role in reducing carbon dioxide emission, increasing energy resource efficiency, and economic saving in the future. This article suggests a new multi-objective optimization approach for optimal planning of microturbine-based CHP systems by considering the uncertainty of equipment availability. The proposed model consists of three competing objective functions: full investment/operation cost, exergy efficiency, and gaseous emissions. To model the uncertainty source, a scenario-based method, using the forced outages of the electrical grid components, auxiliary boiler, and M-CHP, is incorporated into the proposed model. Furthermore, a new achievement function-based directed search domain (AF-DSD) method is proposed to effectively extract the Pareto frontier of this multi-objective problem. The proposed model and solution method are tested on a real-world M-CHP system. The results have shown that, using the AF-DSD method, both sides of the utopia hyper-plane are covered, and all Pareto-optimal solutions can be found for both convex and non-convex problems. The numerical results show that minimizing total cost, primary exergy, and emission promotes an efficient energy supply system where all energy resources are utilized effectively.