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Processes
Special Issues
Modeling and Optimization of Hybrid Energy Systems
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Modeling and Optimization of Hybrid Energy Systems

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (5 March 2023) | Viewed by 16314

Special Issue Editors

Dr. Weiping Zhang

E-Mail Website
Guest Editor
Electronic and Information Engineering, Nanchang University, Xuefu Road 999, Nanchang, China
Interests: mathematical framework of intelligent computing algorithms with applications in machine learning; data analysis; signal modeling & analysis; image matching & mining; process identification; optimization to fully utilize the potential of artificial intelligence paradigm for addressing challenging problems of real-world
Dr. Akbar Maleki

E-Mail Website
Guest Editor
Mechanical Engineering, Shahrood University of Technology, Shahrood 9WVR+757, Iran
Interests: mathematical framework of intelligent computing algorithms with applications in machine learning; data analysis; signal modeling & analysis; image matching & mining; process identification; optimization to fully utilize the potential of artificial intelligence paradigm for addressing challenging problems of real-world

Special Issue Information

Dear Colleagues,

In order to achieve sustainable development, it is necessary to improve the quality of energy systems. The performance of energy systems can be evaluated based on several criteria, such as economic, environmental, and technical aspects. Modeling of energy systems provides the possibility of assessing their performance on the basis of the mentioned criteria. In addition to modeling, optimization of energy systems leads to more favorable and efficient performance. In this regard, the current Special Issue aims to focus on energy system modeling and optimization, and the main interest of the current issue is publication of both original and review studies in related fields. The most attractive topics are:

  • Novel methods used for optimization and evaluation of energy systems (hybrid optimization algorithms, improved optimization algorithms, useful models and efficient optimization methods);
  • Modeling of hybrid energy systems integrated with desalination units;
  • Intelligence methods applicable for modeling of energy technologies;
  • Energy system optimization based on renewable energy (solar and wind energy) for thermal and electrical generation;
  • Combined heat and power systems optimization based on hybrid optimization algorithms;
  • Applications of evolutionary methods in optimizing energy systems (heat and electricity production units in the energy systems);
  • Exergy and exergoeconomic analyses of energy systems;
  • Electrical and thermal analysis of energy systems using intelligence methods;
  • Economics and performance analysis of energy system using optimization algorithms;
  • Integration of secure solutions for thermal and electrical generation systems;
  • Electrical and thermal energy management using intelligence methods.

In addition to the above-mentioned subjects, high-quality articles on related subjects will be considered for publication in this Special Issue.

Prof. Dr. Weiping Zhang
Dr. Akbar Maleki
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. Processes is an international peer-reviewed open access monthly 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 2400 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
  • optimization algorithms
  • modeling of hybrid energy systems

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Published Papers (7 papers)

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Research

27 pages, 12938 KiB  
Article
Radial Basis Function Based Meta-Heuristic Algorithms for Parameter Extraction of Photovoltaic Cell
by Peng He, Xinze Xi, Shengnan Li, Wenlong Qin, Chao Xing and Bo Yang
Processes 2023, 11(6), 1606; https://doi.org/10.3390/pr11061606 - 24 May 2023
Cited by 2 | Viewed by 1173
Abstract
Accurate parameter estimation of photovoltaic (PV) cells is crucial for establishing a reliable cell model. Based on this, a series of studies on PV cells can be conducted more effectively to improve power output; an accurate model is also crucial for the operation [...] Read more.
Accurate parameter estimation of photovoltaic (PV) cells is crucial for establishing a reliable cell model. Based on this, a series of studies on PV cells can be conducted more effectively to improve power output; an accurate model is also crucial for the operation and control of PV systems. However, due to the high nonlinearity of the cell and insufficient measured current and voltage data, traditional PV parameter identification methods are difficult to solve this problem. This article proposes a parameter identification method for PV cell models based on the radial basis function (RBF). Firstly, RBF is used to de-noise and predict the data to solve the current problems in the parameter identification field of noise data and insufficient data. Then, eight prominent meta-heuristic algorithms (MhAs) are used to identify the single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM) parameters of PV cells. By comparing the identification accuracy of the three models in two datasets in detail, the final results show that this method can effectively achieve parameter extraction, with advantages such as high extraction accuracy and stability, greatly improving the accuracy and reliability of parameter identification. Especially in the TDM, the I-V data and P-V data obtained from the PV model established through the identified parameters have very high fitting accuracy with the measured I-V and P-V data, reaching 99.58% and 99.65%, respectively. The research can effectively solve the low accuracy problem caused by insufficient data and noise data in the traditional method of identifying PV cells and can greatly improve the accuracy of PV cell modeling. It is of great significance for the operation and control of PV systems. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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22 pages, 5544 KiB  
Article
Optimal Planning of Hybrid Electricity–Hydrogen Energy Storage System Considering Demand Response
by Zijing Lu, Zishou Li, Xiangguo Guo and Bo Yang
Processes 2023, 11(3), 852; https://doi.org/10.3390/pr11030852 - 13 Mar 2023
Cited by 5 | Viewed by 2090
Abstract
In recent years, the stability of the distribution network has declined due to the large proportion of the uses of distributed generation (DG) with the continuous development of renewable energy power generation technology. Meanwhile, the traditional distribution network operation mode cannot keep the [...] Read more.
In recent years, the stability of the distribution network has declined due to the large proportion of the uses of distributed generation (DG) with the continuous development of renewable energy power generation technology. Meanwhile, the traditional distribution network operation mode cannot keep the balance of the source and load. The operation mode of the active distribution network (ADN) can effectively reduce the decline in operation stability caused by the high proportion of DG. Therefore, this work proposes a bi-layer model for the planning of the electricity–hydrogen hybrid energy storage system (ESS) considering demand response (DR) for ADN. The upper layer takes the minimum load fluctuation, maximum user purchase cost satisfaction, and user comfort as the goals. Based on the electricity price elasticity matrix model, the optimal electricity price formulation strategy is obtained for the lower ESS planning. In the lower layer, the optimal ESS planning scheme is obtained with the minimum life cycle cost (LCC) of ESS, the voltage fluctuation of ADN, and the load fluctuation as the objectives. Finally, the MOPSO algorithm is used to test the model, and the correctness of the proposed method is verified by the extended IEEE-33 node test system. The simulation results show that the fluctuation in the voltage and load is reduced by 62.13% and 37.06%, respectively. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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19 pages, 3625 KiB  
Article
Research on Dam Deformation Prediction Model Based on Optimized SVM
by Yin Xing, Yang Chen, Saipeng Huang, Peng Wang and Yunfei Xiang
Processes 2022, 10(9), 1842; https://doi.org/10.3390/pr10091842 - 13 Sep 2022
Cited by 10 | Viewed by 1891
Abstract
Although constructing a dam can bring significant economic and social benefits to a region, it can be catastrophic for the population living downstream when it breaks. Given the dynamic and nonlinear characteristics of dam deformation, the traditional dam prediction model has been unable [...] Read more.
Although constructing a dam can bring significant economic and social benefits to a region, it can be catastrophic for the population living downstream when it breaks. Given the dynamic and nonlinear characteristics of dam deformation, the traditional dam prediction model has been unable to meet the actual engineering demands. Consequently, this paper advocates for a novel method to solve this issue. The proposed method is based on the optimization of improved chicken swarm (ICSO) and support vector machine (SVM). To begin with, the mean square error is used as the objective function, and then, we apply the improved chicken swarm algorithm to iterate continuously, and finally, the optimal SVM parameters are obtained. Through the modeling and simulation experiments of a nonlinear system, the validity of the improved chicken swarm algorithm to optimize an SVM model has been verified. Based on the horizontal displacement monitoring data of FengMan Dam, this paper analyzed the influencing factors of horizontal displacement. According to the results, three prediction models have been established, respectively: the SVM prediction model optimized by the improved chicken swarm algorithm, the SVM prediction model optimized by the basic chicken swarm algorithm and the BP neural network prediction model optimized by the genetic algorithm. The obtained results from the experiment authenticate the validity and superiority of the proposed method. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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15 pages, 3611 KiB  
Article
Economic Optimization Dispatch Model of a Micro-Network with a Solar-Assisted Compressed Air Energy Storage Hub, with Consideration of Its Operationally Feasible Region
by Libin Yang, Ming Zong, Xiaotao Chen, Yang Si, Laijun Chen, Yongqing Guo and Shengwei Mei
Processes 2022, 10(5), 963; https://doi.org/10.3390/pr10050963 - 11 May 2022
Cited by 14 | Viewed by 1835
Abstract
Using a variety of renewable energy sources can significantly improve energy system flexibility and efficiency. Energy hubs, which have the function of generating, converting, and storing energy in various forms, are vital facilities in micro-energy networks (MENs). In this paper, we present a [...] Read more.
Using a variety of renewable energy sources can significantly improve energy system flexibility and efficiency. Energy hubs, which have the function of generating, converting, and storing energy in various forms, are vital facilities in micro-energy networks (MENs). In this paper, we present a Solar-Assisted Compressed Air Energy Storage (SA-CAES) hub which can accommodate and flexibly supply multi-energy by being connected to a power distribution network (PDN) and a district heating network (DHN). We formulate economic dispatch models of the SA-CAES hub, the PDN, and the DHN, respectively. The economic dispatch model is formulated as a mixed-integer linear programming problem (MILP) that can be solved by commercial solvers. Further, the operationally feasible region of the SA-CAES hub is explored by thermodynamic analysis. The results indicate that the operation costs have been reduced by 4.5% in comparison with conventional MENs. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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17 pages, 4187 KiB  
Article
Technical and Economical Investigation of a Centralized and Decentralized Hybrid Renewable Energy System in Cadaado, Somalia
by Hasan Huseyin Coban, Aysha Rehman and Abdullah Mohamed
Processes 2022, 10(4), 667; https://doi.org/10.3390/pr10040667 - 29 Mar 2022
Cited by 15 | Viewed by 3196
Abstract
The purpose of this paper is to investigate the feasibility of a wind–solar hybrid system on and off-grid power system for electricity generation at a selected location in Somalia using the renewable energy optimization software HOMER. The simulation model was successfully applied to [...] Read more.
The purpose of this paper is to investigate the feasibility of a wind–solar hybrid system on and off-grid power system for electricity generation at a selected location in Somalia using the renewable energy optimization software HOMER. The simulation model was successfully applied to find the best simulation results based on the energy-efficient system for the specific load. The technical and economic performance of an on-grid and stand-alone combination of 25 kW wind power and 60 kW solar photovoltaic was investigated. Since the city of Cadaado has not yet installed its own standard modern electricity grid and due to the great need to reduce energy costs in Somalia, a feasibility study was conducted on how to supply electricity to a sampled residential consumption. Based on the basic characteristics of renewable energy sources in central Somalia, the on-grid wind and solar photovoltaic systems could be economically feasible. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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12 pages, 7749 KiB  
Article
Economic Benefit Evaluation System of Green Building Energy Saving Building Technology Based on Entropy Weight Method
by Hanguang Lu, Xiaojie Sheng and Fei Du
Processes 2022, 10(2), 382; https://doi.org/10.3390/pr10020382 - 17 Feb 2022
Cited by 16 | Viewed by 2879
Abstract
The development of the construction industry has brought great convenience to people’s lives, but the problems of resource shortages and energy consumption are becoming more and more serious. In order to solve the problem of resource shortages and energy consumption, this paper puts [...] Read more.
The development of the construction industry has brought great convenience to people’s lives, but the problems of resource shortages and energy consumption are becoming more and more serious. In order to solve the problem of resource shortages and energy consumption, this paper puts forward an evaluation system of technical and economic benefits of green building energy conservation based on the analytic hierarchy process and entropy weight method. In view of the correlation between building technology and economic benefits, this paper puts forward the economic benefit evaluation system of green building energy-saving technology combined with analytic hierarchy process and entropy weight methods, determines 6 first-class evaluation indexes and 20 s-class evaluation indexes, and takes the dynamic incremental investment payback period and incremental economic benefit ratio as the evaluation indexes, and finally obtains the economic benefit score and star value of green building. Combined with the actual situation of a middle school project, the incremental economic benefits of the four green technologies in energy conservation and resource utilization indicators are 44,256.75 yuan, 1,015,924.2 yuan, 255,490 yuan and 32,871.57 yuan, respectively. The total incremental economic effect and unit incremental effect of the six evaluation indicators are 1,472,113.3 yuan and 1501.99 yuan/m2 respectively. The economic effect of energy-saving and renewable resource utilization technology is the largest. The total score of the project is 0.404902 and it has three stars. Compared with traditional building technology, the application of green building technology and related facilities and equipment proposed in this paper can greatly reduce the consumption of building resources, so as to achieve the purpose of energy conservation and emissions reduction. This method combines objective evaluation with subjective evaluation, complements fair objective evaluation and expert evaluation, makes the best use of all basic information, and ensures the scientific effectiveness of the comprehensive evaluation model. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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17 pages, 8331 KiB  
Article
Study on Mechanical Properties of Cement-Improved Frozen Soil under Uniaxial Compression Based on Discrete Element Method
by Fei Ding, Lei Song and Fengtian Yue
Processes 2022, 10(2), 324; https://doi.org/10.3390/pr10020324 - 8 Feb 2022
Cited by 11 | Viewed by 2130
Abstract
Taking cement-improved frozen soil as the research object, this paper, based on uniaxial unconfined compressive tests of improved-frozen soil under the conditions of different cement contents (6%, 12%, 18%) and curing ages (7 d, 14 d, 28 d), analyzed the results and probed [...] Read more.
Taking cement-improved frozen soil as the research object, this paper, based on uniaxial unconfined compressive tests of improved-frozen soil under the conditions of different cement contents (6%, 12%, 18%) and curing ages (7 d, 14 d, 28 d), analyzed the results and probed the relationship between the strength and elastic modulus of cement-improved frozen soil and cement content and curing age. In combination with laboratory test results, numerical simulations were set with the PFC3D group, building on the samples with 6% and 18% cement content at 14 days of curing, respectively, and the mesoscopic parameter values of the two different amounts were calibrated, which proved the simulation of cement with PFC3D reliable to improve frozen soil, and from the microscopic view, the crack development, stress field, and the particle displacement field of the two samples were analyzed. The result shows that the force is not evenly distributed in the samples; with the main force chain on the cement particles, an increase in particles can lessen the cracks, and the failure of the 6% sample is a tensile plastic failure and that of the 18% sample is a tensile shear failure. Full article
(This article belongs to the Special Issue Modeling and Optimization of Hybrid Energy Systems)
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