Development of an interval-credibility-chance constrained energy-water nexus system planning model—a case study of Xiamen, China. (15th August 2019) - Liu, J.; Nie, S.; Shan, B.G.; Li, Y.P.; Huang, G.H.; Liu, Z.P.
Abstract: In this study, an interval-credibility-chance constrained programming (ICCCP) method which is capable of handling uncertainties presented as interval and interval-fuzzy-random values existed in the energy-water nexus (EWN) system is developed. An ICCCP-EWN model is formulated for planning energy-water nexus system of Xiamen that is heavily relies on fossil fuels (e.g., coal is a main energy source). A set of probability and credibility levels related to energy-water availabilities, energy-water demands, and pollutant-emission mitigations are examined. Results discover that uncertainties have significant effects on the system planning strategies. System cost, heat generation, imported energy, and water supply would decrease with the raised probability level and increase with the raised credibility level. Coal-fired would be the main contributor to electricity generation; however, its proportion would reduce from [59.4, 59.9]% to [40.5, 41.8]%. Gas-fired would increase from [27.4, 27.6]% to [41.5, 43.9]% of the total electricity generation. Surface water would be the main water source, sharing more than 65% of the total amount. One of the major water users would be gas-fired electricity generation, increasing from [32.1, 32.6]% to [42.1, 44.6]% in future. These findings can provide useful information for the study city to adjust the existing energy and water planning strategies to achieve the goal of sustainable development. Highlights: An interval-credibility-chance constrained programming model is proposed. Energy-water nexus system planning model is formulated for Xiamen, China. Interval-fuzzy-random uncertainties can affect the planning policies. The system transforms from coal-dominated to gas-dominated (over 40%). Surface water would be main water source (over 65%) and gas would be main consumer.