LAPSE:2023.27843v1
Published Article

LAPSE:2023.27843v1
Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China
April 11, 2023
Abstract
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.
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.
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Keywords
carbon emission, cost of energy, HOMER model, off-grid/grid-connected system, Renewable and Sustainable Energy
Subject
Suggested Citation
Ye B, Zhou M, Yan D, Li Y. Multi-Objective Decision-Making for Hybrid Renewable Energy Systems for Cities: A Case Study of Xiongan New District in China. (2023). LAPSE:2023.27843v1
Author Affiliations
Ye B: School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Zhou M: School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Yan D: School of Environmental Science and Engineering, Guangzhou University, Guangzhou 510006, China
Li Y: Sun Yat-sen Business School, Sun Yat-sen University, Guangzhou 510275, China
Zhou M: School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Yan D: School of Environmental Science and Engineering, Guangzhou University, Guangzhou 510006, China
Li Y: Sun Yat-sen Business School, Sun Yat-sen University, Guangzhou 510275, China
Journal Name
Energies
Volume
13
Issue
23
Article Number
E6223
Year
2020
Publication Date
2020-11-26
ISSN
1996-1073
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PII: en13236223, Publication Type: Journal Article
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LAPSE:2023.27843v1
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https://doi.org/10.3390/en13236223
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