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Advanced Decision-Making Methods for Hybrid Energy System Planning and Management under Complexities and Uncertainties

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (21 August 2022) | Viewed by 12098

Special Issue Editors

School of Economics and Management, Beijing University of Technology, Beijing 100124, China
Interests: energy planning; energy management; energy–water nexus; energy policy
Special Issues, Collections and Topics in MDPI journals
School of Economics and Management, Beijing University of Technology, Beijing 100124, China
Interests: intelligence decision support systems; expert systems and decision support; information management; artificial intelligence; fuzzy set theory; data mining; their application in various fields
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China
Interests: water resources system management; water system nexus simulation and planning; uncertainty optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Developing renewable energy sources has become a strategic choice worldwide to combat the energy crisis and achieve carbon-neutral targets. A hybrid energy system with renewable energy sources, combined heat and power generation, and energy storage devices is a promising option to improve system efficiency, enhance energy supply reliability, and promote traditional energy system transition. Sustainable planning and operation management of the hybrid energy system are two critical issues that need to be addressed. However, various factors such as technical, technological, sociopolitical, environmental, and economic factors need to be considered when implementing a hybrid energy system. Meanwhile, intermittent renewable energy generation, complementary of multi renewable energy sources, stochastic energy demand, fluctuant energy prices, as well as ambiguous policy bring great challenges to decision makers. Despite the fruitful literature, more advanced decision-making tools and multidisciplinary methods are desired to address the outstanding challenges in the planning and management of hybrid energy systems under various complexities and uncertainties.

We welcome original research articles, reviews, case, and analytical studies, as well as papers from different disciplines, which are relevant to advanced decision-making methods for hybrid energy system planning and management.

Dr. Ling Ji
Dr. Zaoli Yang
Prof. Dr. Yulei Xie
Guest Editors

Manuscript Submission Information

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Keywords

  • multi-attribute decision making
  • uncertain programming
  • multiobjective programming
  • risk management
  • hybrid energy system
  • renewable energy
  • energy system transition
  • energy efficiency management

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Published Papers (5 papers)

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Research

21 pages, 2926 KiB  
Article
Integrated Optimization for Biofuel Management Associated with a Biomass-Penetrated Heating System under Multiple and Compound Uncertainties
by Dianzheng Fu, Tianji Yang, Yize Huang and Yiming Tong
Energies 2022, 15(15), 5406; https://doi.org/10.3390/en15155406 - 26 Jul 2022
Viewed by 1281
Abstract
The biofuel management of a biofuel-penetrated district heating system is complicated due to its association with multiple and polymorphic uncertainties. To handle uncertainties and system dynamic complexities, an inexact two-stage compound-stochastic mixed-integer programming technique is proposed, innovatively based on the integration of different [...] Read more.
The biofuel management of a biofuel-penetrated district heating system is complicated due to its association with multiple and polymorphic uncertainties. To handle uncertainties and system dynamic complexities, an inexact two-stage compound-stochastic mixed-integer programming technique is proposed, innovatively based on the integration of different uncertain optimization approaches. The proposed technique can not only address the inexact recourse problems sourced from multiple and compound uncertainties existing in the pre-regulated biofuel supply–demand match mode, but can also quantitatively analyze the conflicts between the economic target that minimizes the system cost and the risk preference that maximizes the heating service satisfaction. The developed model is applied to a real-world biofuel management case study of a district heating system to obtain the optimal biofuel management schemes subject to supply–demand, policy requirement constraints, and the financial minimization objective. The results indicate that biofuel allocation and expansion schemes are sensitive to the multiple and compound uncertainty inputs, and the corresponding biofuel-deficit change trends of three heat sources are obviously distinct with the system’s condition, varying due to the complicated interactions of the system’s components. Beyond that, a potential trade-off relationship between the heating cost and the constraint-violation risk can be obtained by observing system responses with thermalization coefficient varying. Full article
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12 pages, 2183 KiB  
Article
An Integrated Energy System Operation Optimization Model for Water Consumption Control Analysis in Park Scale from the Perspective of Energy–Water Nexus
by Ruixin Gou, Guiping He, Bo Yu, Yanli Xiao, Zhiwei Luo and Yulei Xie
Energies 2022, 15(12), 4410; https://doi.org/10.3390/en15124410 - 16 Jun 2022
Cited by 2 | Viewed by 1988
Abstract
The water–energy nexus has become a key factor in the implementation of low-carbon green development, which has led to the need for exploring effective management within the coupled integrated system with multi-energy flow supplies. In this study, the coupled relationship between water resources [...] Read more.
The water–energy nexus has become a key factor in the implementation of low-carbon green development, which has led to the need for exploring effective management within the coupled integrated system with multi-energy flow supplies. In this study, the coupled relationship between water resources and energy in the integrated energy system was systematically analyzed, and a system operation optimization model was proposed through comprehensively considering cold, heat and electricity load, and nine kinds of energy conversion and supply equipment/technology from the perspective of a water resources and energy nexus in a typical industry park. The system operation scheme, energy supply mode, net benefit and water resource consumption under different water resource control scenarios were obtained. The results show that water resource control would directly bring about a directly positive influence on renewable energy utilization and energy storage reduction, and that a system’s external dependence and benefits, renewable energy utilization potential and other factors in an integrated energy system should be comprehensively considered. The development of more effective control indicators could be better to promote the effectiveness of bidirectional regulation in a water–energy nexus. Full article
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18 pages, 3114 KiB  
Article
Is the Renewable Portfolio Standard in China Effective? Research on RPS Allocation Efficiency in Chinese Provinces Based on the Zero-Sum DEA Model
by Shangjia Wang, Wenhui Zhao, Shuwen Fan, Lei Xue, Zijuan Huang and Zhigang Liu
Energies 2022, 15(11), 3949; https://doi.org/10.3390/en15113949 - 27 May 2022
Cited by 2 | Viewed by 2452
Abstract
As one of the countries with the most rapid development of new energy, China has been committed to exploring countermeasures to the challenges of new energy consumption. After more than ten years of consideration and consultation, the “renewable portfolio standard“(RPS) for “renewable energy [...] Read more.
As one of the countries with the most rapid development of new energy, China has been committed to exploring countermeasures to the challenges of new energy consumption. After more than ten years of consideration and consultation, the “renewable portfolio standard“(RPS) for “renewable energy power consumption responsibility weighting” has landed in China. However, in the official affirmation issued by the National Energy Administration, theoretical support for the basis of the initial quota allocation is still lacking. In this study, we examine the efficiency of the weight allocation scheme for renewable energy power consumption responsibilities, which was announced by the National Energy Administration in 2018 and which is based on the BCC-DEA efficiency model. The results indicate that most provinces have low allocation efficiency under this allocation scheme. Therefore, we propose an optimal allocation scheme for a renewable energy consumption quota, based on the ZSG-DEA model. With the achievement of its target, this study’s allocation scheme would ensure 100% efficiency in all provinces, improve provincial economic efficiency, and simultaneously bring economic growth. After analyzing the fairness before and after adjustment of the RPS, our findings suggest that the adjusted RPS allocation scheme can promote equity in per capita renewable electricity consumption. Full article
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20 pages, 5629 KiB  
Article
Inter-Provincial Electricity Trading and Its Effects on Carbon Emissions from the Power Industry
by Yanfeng Li, Yongping Li, Guohe Huang and Rubing Zheng
Energies 2022, 15(10), 3601; https://doi.org/10.3390/en15103601 - 14 May 2022
Cited by 4 | Viewed by 2550
Abstract
Electricity trading is an effective measure to minimize carbon emissions and alleviate the imbalance between reverse distribution of regional energy resources and power load. However, the effects of China’s electricity trading on carbon emissions have not been fully explored due to lack of [...] Read more.
Electricity trading is an effective measure to minimize carbon emissions and alleviate the imbalance between reverse distribution of regional energy resources and power load. However, the effects of China’s electricity trading on carbon emissions have not been fully explored due to lack of complete and balanced inter-provincial power transmission data. Therefore, the electricity generation–consumption downscaling model, logarithmic mean Divisia index (LMDI) model, and random forest clustering algorithm within a general framework were used in the present study to explore the effect of electricity trading on level of carbon emissions. Comprehensive inter-provincial electricity transmission data were generated, driving factors including electricity imports and exports were decomposed at the national and provincial scales, and clustered provincial policy implications were evaluated. The results revealed that: (i) although economic activities were the main driving factor for increase in carbon emissions at the national level, 382.95 million tons carbon emissions were offset from 2005 to 2019 due to inter-provincial electricity importation, whereas electricity export increased carbon emission by 230.30 million tons; (ii) analysis at the provincial level showed that electricity exports from Sichuan and Yunnan provinces accounted for more than 20% of the nation’s total electricity flow. Notably, this high level of exports did not significantly increase carbon emissions in these provinces owing to the abundant hydropower resources; (iii) emission reductions were only observed at the national level if the carbon intensity of the exporting provinces was lower compared with that of importing provinces, or if the electricity trading was generated from renewable sources; (iv) the effect of electricity import on emissions reduction was markedly higher relative to the effect of electricity export in most provinces, which reflected the actual situation of sustaining optimization of electricity generation structure in provincial grids of China. These findings provide a basis for decision makers to understand the contributions of electricity trading to the changes in carbon emissions from electricity generation, as well as form a foundation to explore practicable carbon emission mitigation strategies in the power industry. Full article
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11 pages, 1240 KiB  
Article
Solar Energy Deployment for the Sustainable Future of Vietnam: Hybrid SWOC-FAHP-WASPAS Analysis
by Nguyen Van Thanh and Nguyen Thi Kim Lan
Energies 2022, 15(8), 2798; https://doi.org/10.3390/en15082798 - 11 Apr 2022
Cited by 15 | Viewed by 2730
Abstract
In recent years, solar power has developed significantly in Vietnam, making an important contribution to ensuring energy conservation and decreasing greenhouse gas exposure. Recently, Vietnam has experienced impressive growth in the solar and wind energy sectors, showing the high potential of using renewable [...] Read more.
In recent years, solar power has developed significantly in Vietnam, making an important contribution to ensuring energy conservation and decreasing greenhouse gas exposure. Recently, Vietnam has experienced impressive growth in the solar and wind energy sectors, showing the high potential of using renewable electricity in addressing energy needs. The target of this study was to construct a fuzzy multicriteria decision-making, model including strengths-weaknesses-opportunities-challenges (SWOC) analysis, the fuzzy analytic hierarchy process (F-AHP) model, and the weighted aggregates sum product assessment (WASPAS) model, to select the location of a solar power plant in south Vietnam. The proposed fuzzy multicriteria decision-making model (MCDM) model is the first solar power plant location selection in southern Vietnam that utilizes literature reviews and expert interviews. Moreover, this is the first study to provide a case study on evaluating locations during solar power plant location selection that utilizes a combination of the SWOC, FAHP, and WASPAS models. The findings of this study provide valuable knowledge for the assessment and selection of suitable locations for renewable energy projects, including both solar power energy projects and other renewable energy projects. Full article
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