A framework for uncertainty and sensitivity analysis of district energy systems considering different parameter types. (November 2021)

• Record Type: Journal Article
• Authors: Liu, Tianjie; Jiao, Wenling; Tian, Xinghao
• Is Part Of: Energy reports. Volume 7(2021)
• Page Start: 6908
• Page End: 6920
• Publication Date: 2021-11
• Subjects: District energy system -- Uncertainty identification -- Renewable energy -- Global sensitivity analysis; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2021.10.064
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: A variety of renewable energy sources, demand side loads, and other factors bring a lot of uncertainties to the operation of district energy systems. However, there is no strict standard for the selection of uncertainty factors. Too much uncertainty, or not enough of it, is not appropriate for the system optimization. In this paper, a method of uncertainty and sensitivity analysis for district energy system is proposed to identify the important uncertainties in the system optimization process. Firstly, the mathematical model of the system is established and the uncertain parameters are screened from technological, economic, environmental and demand-side perspectives. In addition, the selected parameters are divided into two categories according to whether they are time-related, and two methods are adopted to collect samples. Further, a global sensitivity analysis technique is introduced to calculate the sensitivity index of each parameter simultaneously. Case study is performed for a classic district energy system in a typical day of transition season. The sensitivity indexes under different objective functions are also discussed on this basis. The results show that the proposed framework can effectively analyze the uncertain parameters of the system, which can further contribute to the optimal operation decision. Highlights: A novel district energy system uncertainty analysis framework. Distinguish between time-dependent and time-independent parameters. A global sensitivity analysis method based on RBD-FAST is introduced. Operating cost is the most sensitive to gas price.