Optimal Design of a Distributed Energy System Using the Functional Interval Model That Allows Reduced Carbon Emissions in Guanzhong, a Rural Area of China

Sustainability

Yongping Li¹  Guohe Huang²  Xueting Zeng³  Xiaxia Yan⁴  Ying Zhu⁴  Quanling Tong⁴ 

[1] Environment and Energy Systems Engineering Research Center, School of Environment, Beijing Normal University, Beijing 100875, China;Institute for Energy, Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, SK S4S 0A2, Canada;School of Labor Economics, Capital University of Economics and Business, Beijing 100070, China;Shaanxi Key Laboratory of Environmental Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China;

关键词: distributed energy system;    optimal design;    rural area;    functional interval;    carbon emission;   

DOI  :  10.3390/su11071930

来源: DOAJ

【 摘 要 】

Nowadays, rural power supply in China plays an important role in restricting the economic development and improvement of residential living standards. In this study, an interval full-infinite programming rural energy model (IFIP-REM) was developed for supporting distributed energy system (DES) optimal design under uncertainties in rural areas. By affecting the upper and lower bounds of the interval by complex and variable external conditions, IFIP-REM could simulate the influence of external systems. To validate the model, a real case study of DES optimal design in Guanzhong, a rural area of China, was tested and aimed to minimize system cost and constraints of resources, energy supply reliability, and carbon emission mitigation. The data revealed generation of reasonable optimization schemes to obtain interval solutions of IFIP-REM. Compared to centralized energy system (CES), DES reduced electricity purchasing of the municipal grid by 47.5% and extended carbon emission of both upper and lower bounds to [17.13, 44.51] % and [12.42, 36.02] %, respectively. Overall, the proposed model could help managers make decisions of DES optimal design by coordinating conflicts among economic cost, system efficiency, and carbon emission mitigation.

【 授权许可】

Unknown