Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China

Ye, Bin1; Zhou, Minhua1; Yan, Dan2; Li, Yin3

2020-12-01

10.3390/en13236223

ENERGIES   影响因子和分区

1996-1073

The application of renewable energy has become increasingly widespread worldwide because of its advantages of resource abundance and environmental friendliness. However, the deployment of hybrid renewable energy systems (HRESs) varies greatly from city to city due to large differences in economic endurance, social acceptance and renewable energy endowment. Urban policymakers thus face great challenges in promoting local clean renewable energy utilization. To address these issues, this paper proposes a combined multi-objective optimization method, and the specific process of this method is described as follows. The Hybrid Optimization Model for electric energy was first used to examine five different scenarios of renewable energy systems. Then, the Technique for Order Preference by Similarity to an Ideal Solution was applied using eleven comprehensive indicators to determine the best option for the target area using three different weights. To verify the feasibility of this method, Xiongan New District (XND) was selected as an example to illustrate the process of selecting the optimal HRES. The empirical results of simulation tools and multi-objective decision-making show that the Photovoltaic-Diesel-Battery off-grid energy system (option III) and PV-Diesel-Hydrogen-Battery off-grid energy system (option V) are two highly feasible schemes for an HRES in XND. The cost of energy for these two options is 0.203 and 0.209 $/kWh, respectively, and the carbon dioxide emissions are 14,473 t/yr and 345 t/yr, respectively. Our results provide a reference for policymakers in deploying an HRES in the XND area.

renewable energy HOMER model cost of energy carbon emission off-grid grid-connected system

SCI ; EI

英语

第一

National Natural Science Foundation of China[71803074] ; Natural Science Foundation of Shenzhen City[JCYJ20190809162809440] ; High-level Special Funding of the Southern University of Science and Technology["G02296302","G02296402"] ; Foundation for Innovative Research Groups of the National Natural Science Foundation of China[71721001]

Energy & Fuels

Energy & Fuels

WOS:000597074900001

MDPI

20212310457666

Carbon dioxide ; Carbon dioxide process ; Diesel engines ; Electric batteries ; Energy utilization ; Global warming ; Multiobjective optimization ; Renewable energy resources

Atmospheric Properties:443.1 ; Energy Resources and Renewable Energy Issues:525.1 ; Energy Utilization:525.3 ; Foundry Practice:534.2 ; Diesel Engines:612.2 ; Electric Batteries:702.1 ; Inorganic Compounds:804.2 ; Management:912.2 ; Optimization Techniques:921.5

Web of Science

1.Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen 518055, Peoples R China
2.Guangzhou Univ, Sch Environm Sci & Engn, Guangzhou 510006, Peoples R China
3.Sun Yat Sen Univ, Sun Yat Sen Business Sch, Guangzhou 510275, Peoples R China

Ye, Bin,Zhou, Minhua,Yan, Dan,et al. Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China[J]. ENERGIES,2020,13(23).

Ye, Bin,Zhou, Minhua,Yan, Dan,&Li, Yin.(2020).Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China.ENERGIES,13(23).

Ye, Bin,et al."Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China".ENERGIES 13.23(2020).