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Sustainability 2016, 8(6), 533; doi:10.3390/su8060533

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

1
Institute of Cross-Process Perception and Control, Shaanxi Normal University, Xi’an 710119, China
2
International Business School, Shaanxi Normal University, Xi’an 710062, China
3
School of Economics and Management, Xidian University, Xi’an 710071, China
4
LeBow College of Business, Drexel University, Philadelphia, PA 19104, USA
5
Department of Management Sciences, City University of Hong Kong, Kowloon, Hong Kong
*
Author to whom correspondence should be addressed.
Academic Editor: Samuel Fankhauser
Received: 1 April 2016 / Revised: 29 May 2016 / Accepted: 1 June 2016 / Published: 4 June 2016
(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)
View Full-Text   |   Download PDF [1182 KB, uploaded 4 June 2016]   |  

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. View Full-Text
Keywords: low carbon; carbon trading; power dispatching; hybrid uncertain multi-objective bi-level model; chance constrained programming; expected value programming; satisfaction method low carbon; carbon trading; power dispatching; hybrid uncertain multi-objective bi-level model; chance constrained programming; expected value programming; satisfaction method
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zhou, X.; Zhao, C.; Chai, J.; Lev, B.; Lai, K.K. Low-Carbon Based Multi-Objective Bi-Level Power Dispatching under Uncertainty. Sustainability 2016, 8, 533.

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