Uncertain programming of building cooling heating and power (BCHP) system based on Monte-Carlo method

Uncertainty of building energy demands has large influence on accuracy of building cooling heating and power (BCHP) programming model. Uncertain programming model is proposed to optimize BCHP system with consideration of uncertainty of energy demands. Monte-Carlo method (MCM) and mixed-integer nonlinear programming (MINLP) are integrated in the model (M–M model for short). MCM can be used to simulate the uncertainty of energy demands avoiding dimension disaster and complex calculation. Correlation between different energy demands can also be considered in the model. And facility scheme and operation strategy can be optimized simultaneously in MINLP model. A numerical example is calculated with the M–M model. Convergence rate of expected values of the variables optimized in the model is high. Influence of energy demand uncertainty is studied with investigation of expected values, standard deviations of evaluation indicators and facility capacities. Sensitivity of the parameters to energy demand uncertainty is much different. It is unnecessary to consider uncertainty of energy demands when evaluating system feasibility with indicators of annual cost saving rate and annual natural gas saving rate, for they are influenced only a little by uncertainty of energy demands. While uncertainty of energy demands must be considered when studying parameters related to assistant facilities, which are very sensitive to the uncertainty. The result is valuable for designing strategy of facility scheme.