Abstract
Abstract In this study, a fractile-based interval mixed-integer programming (FIMP) method is advanced for sustainable municipal-scale energy system planning and management. FIMP can handle uncertainties presented in terms of fuzzy boundary intervals that represent interval coefficients with independently fuzzy lower and upper bounds with possibility distributions. A FIMP-based municipal energy model (FIMP-MEM) is then formulated for managing various energy activities in the City of Shenzhen, China. Solutions for energy supply, electricity generation, oil-product production, air-pollutant mitigation, carbon dioxide control, capacity expansion, and electricity import/export are obtained. Results can be used to help the city's managers to identify desired system designs and to determine which of these designs can most efficiently accomplish optimizing the system objective under diverse p-necessity fractiles. The generated decision alternatives are beneficial for the city's energy system planning and management through (a) generating desired energy resources allocation, (b) identifying electricity generation and capacity-expansion scheme, (c) providing air pollution control plan, (d) analyzing the tradeoff among system cost, environmental impact, and system-failure risk.
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