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Article

A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China

1
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
2
The Vehicle Pollution Prevention and Control Center of Jinan, Jinan Environmental Protection Bureau, Jinan 250099, Shandong, China
3
Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, SK S4S 0A2, Canada
4
School of Economics and Management, Beijing University of Technology, Beijing 100124, China
*
Author to whom correspondence should be addressed.
Energies 2018, 11(8), 2108; https://doi.org/10.3390/en11082108
Received: 4 July 2018 / Revised: 23 July 2018 / Accepted: 3 August 2018 / Published: 13 August 2018
(This article belongs to the Special Issue Optimisation Models and Methods in Energy Systems)
In this study, in order to improve regional energy system adjustment, a multistage stochastic inexact robust programming (MSIRP) is proposed for electric-power generation planning and structure adjustment management under uncertainty. Scenario-based inexact multistage stochastic programming and stochastic robust optimization were integrated into general programming to reflect uncertainties that were expressed as interval values and probability distributions in the objective function and constraints. An MSIRP-based energy system optimization model is proposed for electric-power structure management of Zibo City in Shandong Province, China. Three power demand scenarios associated with electric-power structure adjustment, imported electricity, and emission reduction were designed to obtain multiple decision schemes for supporting regional sustainable energy system development. The power generation schemes, imported electricity, and emissions of CO2 and air pollutants were analyzed. The results indicated that the model can effectively not only provide a more stable energy supply strategies and electric-power structure adjustment schemes, but also improve the balanced development between conventional and new clear power generation technologies under uncertainty. View Full-Text
Keywords: scenario-based multistage stochastic programming; energy system management model; stochastic robust optimization; electric-power structure adjustment; energy conservation and emissions reduction scenario-based multistage stochastic programming; energy system management model; stochastic robust optimization; electric-power structure adjustment; energy conservation and emissions reduction
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MDPI and ACS Style

Xie, Y.; Wang, L.; Huang, G.; Xia, D.; Ji, L. A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China. Energies 2018, 11, 2108. https://doi.org/10.3390/en11082108

AMA Style

Xie Y, Wang L, Huang G, Xia D, Ji L. A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China. Energies. 2018; 11(8):2108. https://doi.org/10.3390/en11082108

Chicago/Turabian Style

Xie, Yulei, Linrui Wang, Guohe Huang, Dehong Xia, and Ling Ji. 2018. "A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China" Energies 11, no. 8: 2108. https://doi.org/10.3390/en11082108

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