The integrated energy system is considered to beintroduced in buildings, which proposes a new effectiveapproach to improve energy structure in urban areas.The optimal design problem of building integratedenergy system is normally presented as mixed-integernonlinear programming model with deterministic anduncertainty parameters. Moreover, the uncertaintyproblem results in a more complex problem at a highcomputational cost. In present work, a two-stage multi-objective stochastic programming model underuncertainty is presented. The proposed model dependson clustering method to create different scenarios interms of solar radiation, wind speed and energy demand.In addition, the MINLP models of building integratedenergy system with stochastic scenarios anddeterministic scenarios is investigated to conduct trade-off Pareto optimization with cost-optimal andenvironment-optimal. The results indicate that thedeterministic programming model underestimates thecost and carbon emission of building integrated energysystem, while the result of stochastic programmingmodel is closer to the realistic design.
Keywords renewable energy resources, MINLP, stochastic programming, building integrated energy system, multi-objective optimization