Factorial Based Stochastic Optimization Approach for Energy and Environmental Systems Management Under Uncertainty

In this study, an optimization programming based on inexact stochastic method and factorial design was proposed to support management of energy and environmental systems under uncertain conditions. It could be used for analyzing various policy scenarios associated with different levels of economic penalties when promised targets are violated. Moreover, it can obtain optimal decisions of primary energy supply, electricity, and thermal power generation, capacity expansion, and emission control scheme. The developed model has been applied to a case study within a multifacility, multiperiod, and multidemand-level context to demonstrate the feasibility of the proposed methodology. Factorial method has been used for sensitivity analysis to address the interactive uncertainties in modeling parameters, as well as providing a trade-off analysis between the economic objective and the relevant energy and environmental policies. The generated approach will be able to reflect dynamic complexities in energy and environmental systems under social–economic–environmental requirements. It is helpful for adjusting the interrelationship among conflicting economic objectives and environmental benefits under multiple uncertainties, formulating allocation patterns of energy resources and services, and identifying the effectiveness of current regulations.