Low-Carbon Based Multi-Objective Bi-Level Power Dispatching under Uncertainty

Xiaoyang Zhou, Canhui Zhao, Jian Chai, Benjamin Lev and Kin Keung Lai
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Xiaoyang Zhou: Institute of Cross-Process Perception and Control, Shaanxi Normal University, Xi’an 710119, China
Canhui Zhao: International Business School, Shaanxi Normal University, Xi’an 710062, China
Jian Chai: School of Economics and Management, Xidian University, Xi’an 710071, China
Benjamin Lev: LeBow College of Business, Drexel University, Philadelphia, PA 19104, USA
Kin Keung Lai: Institute of Cross-Process Perception and Control, Shaanxi Normal University, Xi’an 710119, China

Sustainability, 2016, vol. 8, issue 6, 1-23

Abstract: This research examines a low-carbon power dispatch problem under uncertainty. A hybrid uncertain multi-objective bi-level model with one leader and multiple followers is established to support the decision making of power dispatch and generation. The upper level decision maker is the regional power grid corporation which allocates power quotas to each follower based on the objectives of reasonable returns, a small power surplus and low carbon emissions. The lower level decision makers are the power generation groups which decide on their respective power generation plans and prices to ensure the highest total revenue under consideration of government subsidies, environmental costs and the carbon trading. Random and fuzzy variables are adopted to describe the uncertain factors and chance constrained and expected value programming are used to handle the hybrid uncertain model. The bi-level models are then transformed into solvable single level models using a satisfaction method. Finally, a detailed case study and comparative analyses are presented to test the proposed models and approaches to validate the effectiveness and illustrate the advantages.

Keywords: low carbon; carbon trading; power dispatching; hybrid uncertain multi-objective bi-level model; chance constrained programming; expected value programming; satisfaction method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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