A Short-Term Hybrid Energy System Robust Optimization Model for Regional Electric-Power Capacity Development Planning under Different Pollutant Control Pressures

Jixian Cui,Jianguang Yin,Chenghao Liao,Yulei Xie,Yangping Yu,Ling Ji

doi:10.3390/su132011341

Abstract

This paper is aimed at proposing a short-term hybrid energy system robust optimization model for regional energy system planning and air pollution mitigation based on the inexact multi-stage stochastic integer programming and conditional value-at-risk method through a case study in Shandong Province, China. Six power conversion technologies (i.e., coal-fired power, hydropower, photovoltaic power, wind power, biomass power, and nuclear power) and power demand sectors (agriculture, industry, building industry, transportation, business, and residential department) were considered in the proposed model. The optimized electricity generation, capacity expansion schemes, and economic risks were selected to analyze nine defined scenarios. Results revealed that electricity generations of clean and new power had obvious increasing risks and were key considerations of establishing additional capacities to meet the rising social demands. Moreover, the levels of pollutants mitigation and risk-aversion had a significant influence on different power generation schemes and on the total system cost. In addition, the optimization method developed in this paper could effectively address uncertainties expressed as probability distributions and interval values, and could avoid the system risk in energy system planning problems. The proposed optimization model could be valuable for supporting the adjustment or justification of air pollution mitigation management and electric power planning schemes in Shandong, as well as in other regions of China.

Highlights

IntroductionEnvironmental contradictions (e.g., single-energy structure, small proportion of clean energy, and environmental quality improvement) from energy activities have become a more significantly critical and complex issue in China [1,2,3,4]
Due to economic development and resource service loads increasing, energy–environmental contradictions from energy activities have become a more significantly critical and complex issue in China [1,2,3,4]
Among these lay uncertain information that is presented as interval numbers, which can be reflected through interval-parameter programming [25], while random information system dynamic characters and policy implications can be effectively addressed by multi-stage stochastic programming [26]

Summary

Introduction

Environmental contradictions (e.g., single-energy structure, small proportion of clean energy, and environmental quality improvement) from energy activities have become a more significantly critical and complex issue in China [1,2,3,4]. Coal-fired power conversion technologies have occupied large proportions of electricity production compared to other energy conversion technologies. According to the China Statistical Yearbook (2018), the amount of electricity generation of coal-fired power has increased from 3.3 × 106 GWh to 4.4 × 106 GWh from 2010 to 2016. Sustainability 2021, 13, 11341 to environment protection and generate both a series of air pollutants (e.g., sulfur dioxide (SO2 ), nitrogen oxides (NOx), and particulate matter (PM)) and greenhouse gases [5,6]. The total discharged amount of pollutants from electricity generation has brought significant impacts on the atmospheric environment quality protection, with the values of

Objectives

Methods

Results

Conclusion