Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.2
3.0
Journals
Energies
Special Issues
Modeling Analysis and Optimization of Energy System
energies-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Energies Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Modeling Analysis and Optimization of Energy System

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F2: Distributed Energy System".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 3803

Special Issue Editors

Dr. Haoshui Yu

E-Mail Website
Guest Editor
Department of Chemistry and Bioscience, Aalborg University, 6700 Esbjerg, Denmark
Interests: energy system integration; green energy production; energy saving; energy system design; carbon capture; utilization and storage
Special Issues, Collections and Topics in MDPI journals
Dr. Lina Wang

E-Mail Website
Guest Editor
School of Marine Technology and Environment, Dalian Ocean University, Dalian, China
Interests: optimization of energy system; renewable energy; integrated energy systems; energy storage
Dr. Guillermo Diaz-Sainz

E-Mail Website
Guest Editor
Department of Chemical and Biomolecular Engineering, University of Cantabria, Santander, Spain
Interests: CO2 capture; CO2 utilization; electrochemistry; (photo)electroreduction; (photo)oxidation; green hydrogen
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the context of the ongoing energy transition and the global drive towards carbon neutrality, the optimization and efficient management of energy systems have become critical focal points for research and innovation. his special issue aims to highlight cutting-edge methodologies, analytical frameworks, and optimization strategies that address current challenges and opportunities within the energy sector.  We extend an invitation to researchers, academics, and industry professionals to submit original research articles, comprehensive review papers, and insightful case studies that push the boundaries of current knowledge in the modeling, analysis, and optimization of energy systems.

Topics of Interest

Submissions are encouraged but not limited to the following topics:

  • Innovative modeling techniques for renewable energy systems
  • Multi-generation system modeling and optmization
  • Advanced algorithms for the optimization of energy production, distribution, and consumption
  • Data analytics and machine learning applications in energy systems
  • Integration of renewable energy sources into existing grids
  • Energy storage technologies and their impact on energy systems
  • Policy implications and regulatory frameworks for sustainable energy systems
  • Economic and environmental impact assessments of energy systems
  • Case studies on successful implementation of integrated energy systems
  • Simulation and digital twin technologies for energy system optimization

Dr. Haoshui Yu
Dr. Lina Wang
Dr. Guillermo Díaz-Sainz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy systems
  • renewable energy
  • system integration
  • modeling and optimization

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 3364 KiB  
Article
A Study on Short-Term Air Consumption Prediction Model for Air-Jet Looms Combining Sliding Time Window and Incremental Learning
by Bo Yu, Liaoliao Fang, Zihao Wu, Chunya Shen and Xudong Hu
Energies 2024, 17(16), 4052; https://doi.org/10.3390/en17164052 - 15 Aug 2024
Viewed by 755
Abstract
The energy consumption of air-jet looms mainly comes from air compressors. Predicting the air consumption of air-jet looms for the upcoming period is significant for the variable frequency adjustment of air compressors, thereby aiding in energy saving and reducing fabric costs. This paper [...] Read more.
The energy consumption of air-jet looms mainly comes from air compressors. Predicting the air consumption of air-jet looms for the upcoming period is significant for the variable frequency adjustment of air compressors, thereby aiding in energy saving and reducing fabric costs. This paper proposes an innovative method that combines Sliding Time Windows (STW), feature analysis, and incremental learning to improve the accuracy of short-term air consumption prediction. First, the STW method is employed during the data collection phase to enhance data reliability. Through feature analysis, significant factors affecting the air consumption of air-jet looms, beyond traditional research, are explored and incorporated into the prediction model. The experimental results indicate that the introduction of new features improved the model’s R2 from 0.905 to 0.950 and reduced the MSE from 32.369 to 16.239. The STW method applied to the same random forest model increased the R2 from 0.906 to 0.950 and decreased the MSE from 32.244 to 16.239. The decision tree method, compared to the linear regression model, improved the R2 from 0.928 to 0.950 and reduced the MSE from 23.541 to 16.239, demonstrating significant predictive performance enhancement. After establishing the optimal model, incremental learning is used to continuously improve the reliability and accuracy of short-term predictions. Experiments show that the incremental learning method, compared to static models, offers better resilience and reliability when new data are collected. The proposed method significantly improves the accuracy of air consumption prediction for air-jet looms, providing strong support for the variable frequency adjustment of air compressors, and contributes to the goals of energy saving and cost reduction. The research results indicate that this method not only enhances prediction accuracy but also provides new insights and methods for future energy-saving research. Full article
(This article belongs to the Special Issue Modeling Analysis and Optimization of Energy System)
►▼ Show Figures

Figure 1

20 pages, 3619 KiB  
Article
Techno-Economic Analysis of Hydrogen as a Storage Solution in an Integrated Energy System for an Industrial Area in China
by Jincan Zeng, Xiaoyu Liu, Minwei Liu, Xi Liu, Guori Huang, Shangheng Yao, Gengsheng He, Nan Shang, Fuqiang Guo and Peng Wang
Energies 2024, 17(13), 3074; https://doi.org/10.3390/en17133074 - 21 Jun 2024
Viewed by 931
Abstract
This study proposes four kinds of hybrid source–grid–storage systems consisting of photovoltaic and wind energy, and a power grid including different batteries and hydrogen storage systems for Sanjiao town. HOMER-PRO was applied for the optimal design and techno-economic analysis of each case, aiming [...] Read more.
This study proposes four kinds of hybrid source–grid–storage systems consisting of photovoltaic and wind energy, and a power grid including different batteries and hydrogen storage systems for Sanjiao town. HOMER-PRO was applied for the optimal design and techno-economic analysis of each case, aiming to explore reproducible energy supply solutions for China’s industrial clusters. The results show that the proposed system is a fully feasible and reliable solution for industry-based towns, like Sanjiao, in their pursuit of carbon neutrality. In addition, the source-side price sensitivity analysis found that the hydrogen storage solution was cost-competitive only when the capital costs on the storage and source sides were reduced by about 70%. However, the hydrogen storage system had the lowest carbon emissions, about 14% lower than the battery ones. It was also found that power generation cost reduction had a more prominent effect on the whole system’s NPC and LCOE reduction. This suggests that policy support needs to continue to push for generation-side innovation and scaling up, while research on different energy storage types should be encouraged to serve the needs of different source–grid–load–storage systems. Full article
(This article belongs to the Special Issue Modeling Analysis and Optimization of Energy System)
►▼ Show Figures

Figure 1

15 pages, 3513 KiB  
Article
Multi-Objective Optimization of an Organic Rankine Cycle (ORC) for a Hybrid Solar–Waste Energy Plant
by Lina Wang, Jun Yang, Bing Qu and Chang Pang
Energies 2024, 17(8), 1810; https://doi.org/10.3390/en17081810 - 10 Apr 2024
Cited by 4 | Viewed by 1180
Abstract
In pursuit of sustainable development and mitigation of the intermittency challenge associated with solar energy, this study proposes a hybrid solar system integrating waste heat incineration alongside solar power generation and distinct heat provision. Leveraging the superior energy efficiency of the organic Rankine [...] Read more.
In pursuit of sustainable development and mitigation of the intermittency challenge associated with solar energy, this study proposes a hybrid solar system integrating waste heat incineration alongside solar power generation and distinct heat provision. Leveraging the superior energy efficiency of the organic Rankine cycle (ORC) in medium- and low-temperature scenarios, a parabolic trough collector (PTC) is selected for its cost-effectiveness and long-term operational reliability. Dowtherm A and toluene are identified as the optimal working fluids for the PTC and ORC, respectively. To optimize this complex system, a combination of artificial neural networks (ANNs) and multi-objective optimization via non-dominated sorting genetic algorithm II (NSGA-II) is employed, streamlining the optimization process. Thermal dynamic simulations are executed using Engineering Equation Solver (EES, V11) to validate the proposed system’s performance. TOPSIS is employed to identify the optimal solution from the Pareto frontier. The results indicate that the hourly cost of the system stands at USD 43.08, with an exergy efficiency of 22.98%. The economic analysis reveals that the solar collector constitutes the most significant portion of the total initial cost, representing 53.2%, followed by the turbine, thermoelectric generator (TEG), and waste heat incineration, in descending order of costliness. Full article
(This article belongs to the Special Issue Modeling Analysis and Optimization of Energy System)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: xploring Waste Heat Utilization in Refineries for Power Generation and Refrigeration: A Comprehensive Review
Authors: Jin Sun; Rujin Zhou; Li Wang; Dominic C. Y. Foo; Haoshui Yu*
Affiliation: 1: School of Chemical Engineering, Guangdong University of Petrochemical Technology, Maoming, 525000, Guangdong, China 2: Faculty of Science and Engineering, The University of Nottingham Malaysia, 43500 Semenyih, Selangor, Malaysia 3: Department of Chemistry and Bioscience, Aalborg University, Esbjerg 6700, Denmark
Abstract: This review investigates the potential of waste heat utilization in refineries for enhancing energy efficiency and reducing environmental impacts. It focuses on the technologies and case studies related to power generation, refrigeration, and their combined applications. By analyzing successful implementations, technical challenges, and future opportunities, this review provides a comprehensive understanding of waste heat recovery in the refinery industry. The findings aim to guide future research and policy-making towards sustainable energy practices in the petrochemical sector.

Back to TopTop