Decision making under uncertainty in energy systems: State of the art

• Published in: Renewable & sustainable energy reviews Vol. 28; pp. 376 - 384
• Main Authors: Soroudi, Alireza, Amraee, Turaj
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.12.2013; Elsevier
• Subjects: Applied sciences; decision making; Economic data; Energy; Energy economics; Energy policy; Exact sciences and technology; Fuzzy arithmetic; General, economic and professional studies; Info-gap decision theory; Interval based analysis; issues and policy; Methodology. Modelling; planning; Probabilistic modeling; Robust optimization; uncertainty; Z-number; Probabilistic modeling; Info-gap decision theory; Robust optimization; Interval based analysis; Fuzzy arithmetic; Z-number
• ISSN: 1364-0321; 1879-0690
• DOI: 10.1016/j.rser.2013.08.039

The energy system studies include a wide range of issues from short term (e.g. real-time, hourly, daily and weekly operating decisions) to long term horizons (e.g. planning or policy making). The decision making chain is fed by input parameters which are usually subject to uncertainties. The art of dealing with uncertainties has been developed in various directions and has recently become a focal point of interest. In this paper, a new standard classification of uncertainty modeling techniques for decision making process is proposed. These methods are introduced and compared along with demonstrating their strengths and weaknesses. The promising lines of future researches are explored in the shadow of a comprehensive overview of the past and present applications. The possibility of using the novel concept of Z-numbers is introduced for the first time.