Integrated Planning for Regional Electric Power System Management with Risk Measure and Carbon Emission Constraints: A Case Study of the Xinjiang Uygur Autonomous Region, China

Yulei Xie,Dehong Xia,Wentao Lu,Han Wang,Zhenghui Fu,Guohe Huang

doi:10.3390/en12040601

Abstract

With the carbon reduction targets being set in the Paris Agreement on Climate Change, China is facing great pressure to meet its emission reduction commitment. The electric power industry as the major source of carbon emissions needs to be a focus. However, the uncertainty of power systems, the risk of reducing emissions and the fuzziness of carbon capture technology popularization rate and carbon reduction targets makes previous planning methods unsatisfactory for current planning. This paper establishes an interval fuzzy programming with a risk measure model which takes carbon capture technology and carbon reduction targets into account, to ensure that the complex electric management system achieves the best developmental state. It was concluded that in order to reduce carbon emissions, wind power and hydropower would be the best choices, and coal-fired power would be the suboptimal choice, and solar power would play a complementary role. Besides, decision makers should put much more effort into promoting and improving carbon capture technology instead of simply setting emission reduction targets. The non-synchronism of the downward trend in carbon emissions per unit of electricity generation and electric power industry total carbon emissions need to be taken seriously.

Highlights

Human activities are changing the atmospheric composition either directly or indirectly, and the emission of greenhouse gases caused by the utilization of fossil fuels has played a significant role in this progress [1,2,3,4,5]
Interval-parameter programming, fuzzy programming and risk measure are integrated into a framework where the connection between the degree of satisfaction and membership function would be established, and the uncertainties are reflected as functional intervals
With the risk measure part, a simple linear combination of deterministic total system costs and risk measure allows to explore the impact of risk on the optimal solution

Summary

Introduction

Human activities are changing the atmospheric composition either directly (via emissions of gases or particles) or indirectly (via atmospheric chemistry), and the emission of greenhouse gases caused by the utilization of fossil fuels has played a significant role in this progress [1,2,3,4,5]. In order to relieve the carbon reduction pressures, some technical routes are under study, including energy substitution (wind power, hydroelectric, solar power, biomass energy, etc.) and carbon capture technology [6,7,8,9]. Though these routes can reduce carbon emissions to some extent, some problems exist such as the Energies 2019, 12, 601; doi:10.3390/en12040601 www.mdpi.com/journal/energies. The choice between the methods of generating electricity and carbon capture technology is very important to balance and relieve the great conflict between the goal of carbon reduction and the growing electricity demands, in order to get the optimal reduction target and economy. Prebeg et al proposed a two-level approach with multi-objective optimization on the global level, and used it to design a Croatian

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Conclusion