Robust planning of energy management systems with environmental and constraint-conservative considerations under multiple uncertainties

• Published in: Energy conversion and management Vol. 65; pp. 471 - 486
• Main Authors: Dong, C., Huang, G.H., Cai, Y.P., Liu, Y.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-01-2013; Elsevier
• Subjects: Applied sciences; Constraint conservativeness; Decision making; Direct power generation; Electricity; Energy; Energy management; Energy management system; Energy management systems; Environmental emissions; Exact sciences and technology; Fuzzy set theory; Intervals; Mathematical models; Multiple uncertainties; Robust; Uncertainty; Constraint conservativeness; Multiple uncertainties; Decision making; Environmental emissions; Energy management system; Robust
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2012.09.001

Analyze mutual interactions and restrictions within energy management systems. Tackle uncertainties expressed as fuzzy sets, and regular and radial intervals. Obtain optimal solutions under preferred satisfaction degrees and system benefits. Use protection level to reflect tradeoffs between constraint-violation and system reliability. Provide decision makers with effective energy management schemes.
In this study, a fuzzy radial interval linear programming (FRILP) model was developed for supporting robust planning of energy management systems with environmental and constraint-conservative considerations, facilitating the reflecting of multiple uncertainties that are existing in energy activities and environmental emissions and could be expressed as fuzzy sets, and regular and radial intervals. Particularly, it could ensure the generation of robust solutions that would be feasible with high probability under input data variations, reflecting tradeoffs between the conservatism levels of solutions and probability levels of constraint violation. Specifically, 24 radial intervals associated with the electricity generation efficiency and electricity demands under different protection levels based on the natural and technologic conditions, as well as decision makers’ expectation were determined. Totally, 30 scenarios under the combinations of five protection levels were analyzed. Through solving the developed model, the results showed that decision variables would be rising with the increase of protection levels and higher radii fluctuation levels of radial intervals would cause higher system cost and lower satisfaction degree. The generated solutions could offer detail energy management plans (e.g., energy conversion technology capacity expansions) for decision makers, and thus could guarantee optimal economic and environmental benefits under desirable system reliability.