A Comprehensive Forecasting–Optimization Analysis Framework for Environmental-Oriented Power System Management—A Case Study of Harbin City, China

Yang Zhang, Zhenghui Fu, Yulei Xie, Qing Hu, Zheng Li and Huaicheng Guo
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Yang Zhang: College of Environmental Science and Engineering, Peking University, Beijing 100871, China
Zhenghui Fu: Chinese Research Academy of Environmental Sciences, Beijing 100871, China
Yulei Xie: School of Energy and Environmental Engineering, University of Science and Technology, Beijing 100083, China
Qing Hu: College of Environmental Science and Engineering, Peking University, Beijing 100871, China
Zheng Li: College of Environmental Science and Engineering, Peking University, Beijing 100871, China
Huaicheng Guo: College of Environmental Science and Engineering, Peking University, Beijing 100871, China

Sustainability, 2020, vol. 12, issue 10, 1-26

Abstract: In this study, a comprehensive research framework coupled with electric power demand forecasting, a regional electric system planning model, and post-optimization analysis is proposed for electric power system management. For dealing with multiple forms of uncertainties and dynamics concerning energy utilization, capacity expansions, and environmental protection, the inexact two-stage stochastic robust programming optimization model was developed. The novel programming method, which integrates interval parameter programming (IPP), stochastic robust optimization (SRO), and two-stage stochastic programming (TSP), was applied to electric power system planning and management in Harbin, China. Furthermore, the Gray-Markov approach was employed for effective electricity consumption prediction, and the forecasted results can be described as interval values with corresponding occurrence probability, aiming to produce viable input parameters of the optimization model. Ten scenarios were analyzed with different emissions reduction levels and electricity power structure adjustment modes, and the technique for order of preference by similarity to ideal solution (TOPSIS) was selected to identify the most influential factors of planning decisions by selecting the optimal scheme. The results indicate that a diversified power structure that dominates by thermal power and is mainly supplemented by biomass power should be formed to ensure regional sustainable development and electricity power supply security in Harbin. In addition, power structure adjustment is more effective than the pollutants emission control for electricity power system management. The results are insightful for supporting supply-side energy reform, generating an electricity generation scheme, adjusting energy structures, and formulating energy consumption of local policies.

Keywords: emissions reduction; optimization model; post-optimization analysis; power demand forecasting; structure adjustment; uncertainties (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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