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Energies
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Sizing and Allocation Strategies of Renewable Distributed Generations
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Sizing and Allocation Strategies of Renewable Distributed Generations

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

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 6461

Special Issue Editor

Prof. Dr. Ali M Eltamaly

E-Mail Website
Guest Editor
Department of Electrical engineering, Sustainable Energy Technologies Center, College of Engineering, King Saud University, Riyadh P.O. Box 800, Saudi Arabia
Interests: Photovoltaic MPPT; renewable energy; distributed generation; smart grid
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the excessive increase in electric energy all over the world and with limited conventional energy sources, there is a need for renewable energy resources to support the electricity sector. One of the best options to support the existing power systems is using distributed generation sources from renewable energy sources and other types of resources. The distributed generation can substantially improve the performance of the existing power systems by increasing their power capacity, reduce the power losses, increase the reliability of the systems, and improve their power quality. The distributed generation and other types of FACTS can play a significant role in the improvement of the performance of power systems, and it is counted as the future trend in modern power systems. This Special Issue is introduced to participate in this important and critical issue. The proposed Special Issue welcomes any studies on the different topics of distributed generation, especially on the different methodologies used for sizing and allocation of the distributed generation units, the use of different storage systems to support the power system during any abnormal conditions, the use of distributed generation to improve the power quality of the power systems, the modern optimization techniques used for designing and sizing of the distributed generation and FACTS units, and the use of smart grid concepts to improve the reliability and cost of generating electricity in the new and existing power systems via distributed generation.

Topics of interest include, but are not limited to:

  • Sizing and allocation of distributed generation units in both new and existing power systems.
  • The sizing and allocation of FACTS units to improve the power quality of the power systems.
  • The modern optimization techniques used to handle the designing methodologies of the distributed generation.
  • The use of smart grid concepts such as modern demand response strategies to improve the reliability and power quality of the power systems.
  • The use of different energy storage units to support the power systems against abnormal operations.
  • The improvement technologies of renewable energy integration with existing power systems.
  • Studying the opportunities to use different renewable energy resources as a distributed generation of power systems.
  • The protection requirements for power system with the use of distributed generation.
  • Studying the stability of power system incorporated with distributed generation units against abnormal operations and fault occurrence.

Prof. Dr. Ali M Eltamaly
Guest Editor

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

  • distributed generation
  • sizing and allocation
  • renewable energy resources
  • optimization techniques
  • facts
  • power quality

Published Papers (4 papers)

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Research

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19 pages, 3389 KiB  
Article
Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm
by Elham Mahdavi, Seifollah Asadpour, Leonardo H. Macedo and Rubén Romero
Energies 2023, 16(12), 4560; https://0-doi-org.brum.beds.ac.uk/10.3390/en16124560 - 07 Jun 2023
Cited by 5 | Viewed by 1198
Abstract
The economic interest in power loss minimization and regulatory requirements regarding voltage levels in distribution systems are considered. In this paper, a computational technique to assist in the optimization of the power losses and voltage characteristic in the steady state through distribution network [...] Read more.
The economic interest in power loss minimization and regulatory requirements regarding voltage levels in distribution systems are considered. In this paper, a computational technique to assist in the optimization of the power losses and voltage characteristic in the steady state through distribution network reconfiguration and the location and size of the distributed generators is addressed. The whale optimization algorithm (WOA) is chosen to perform this task since it can explore the sizeable combinatorial search space of the problem, which is also nonlinear and nonconvex. The purpose of this study is to mitigate power losses; voltage ranges are borne in mind as the problem restrictions. The proposals for solving the issue are evaluated using a specialized power flow algorithm. The algorithm is implemented in MATLAB and the 33-bus and 69-bus grids are employed to assess the performance of the approach. The results indicate that the WOA method outperforms regarding power loss reduction and voltage characteristic improvement in the concurrent integration of distribution network reconfiguration and distributed generators compared with the four metaheuristics shown in the results section. Full article
(This article belongs to the Special Issue Sizing and Allocation Strategies of Renewable Distributed Generations)
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27 pages, 4885 KiB  
Article
Upgrading Conventional Power System for Accommodating Electric Vehicle through Demand Side Management and V2G Concepts
by Majed A. Alotaibi and Ali M. Eltamaly
Energies 2022, 15(18), 6541; https://0-doi-org.brum.beds.ac.uk/10.3390/en15186541 - 07 Sep 2022
Cited by 10 | Viewed by 1532
Abstract
The continually increasing fossil fuel prices, the dwindling of these fuels, and the bad environmental effects which mainly contribute to global warming phenomena are the main motives to replace conventional transportation means to electric. Charging electric vehicles (EVs) from renewable energy systems (RES) [...] Read more.
The continually increasing fossil fuel prices, the dwindling of these fuels, and the bad environmental effects which mainly contribute to global warming phenomena are the main motives to replace conventional transportation means to electric. Charging electric vehicles (EVs) from renewable energy systems (RES) substantially avoids the side effects of using fossil fuels. The higher the increase in the number of EVs the greater the challenge to the reliability of the conventional power system. Increasing charging connections for EVs to the power system may cause serious problems to the power system, such as voltage fluctuations, contingencies in transmission lines, and loss increases. This paper introduces a novel strategy to not only replace the drawbacks of the EV charging stations on the power system’s stability and reliability, but also to enhance the power system’s performance. This improvement can be achieved using a smart demand side management (DSM) strategy and vehicle to grid (V2G) concepts. The use of DSM increases the correlation between the loads and the available generation from the RES. Besides this, the use of DSM, and the use of V2G concepts, also helps in adding a backup for the power system by consuming surplus power during the high generation period and supplying stored energy to the power system during shortage in generation. The IEEE 30 bus system was used as an example of an existing power system where each load busbar was connected to a smart EV charging station (SEVCS). The performance of the system with and without the novel DSM and V2G concepts was compared to validate the superiority of the concepts in improving the performance of the power system. The use of modified particle swarm optimization in optimal sizing and optimal load flow reduced the cost of energy and the losses of the power system. The use of the smart DSM and V2G concepts substantially improved the voltage profile, the transmission line losses, the fuel cost of conventional power systems, and the stability of the power system. Full article
(This article belongs to the Special Issue Sizing and Allocation Strategies of Renewable Distributed Generations)
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26 pages, 4410 KiB  
Article
The Compound Inverse Rayleigh as an Extreme Wind Speed Distribution and Its Bayes Estimation
by Elio Chiodo, Maurizio Fantauzzi and Giovanni Mazzanti
Energies 2022, 15(3), 861; https://0-doi-org.brum.beds.ac.uk/10.3390/en15030861 - 25 Jan 2022
Cited by 4 | Viewed by 1840
Abstract
This paper proposes the Compound Inverse Rayleigh distribution as a proper model for the characterization of the probability distribution of extreme values of wind-speed. This topic is gaining interest in the field of renewable generation, from the viewpoint of assessing both wind power [...] Read more.
This paper proposes the Compound Inverse Rayleigh distribution as a proper model for the characterization of the probability distribution of extreme values of wind-speed. This topic is gaining interest in the field of renewable generation, from the viewpoint of assessing both wind power production and wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity for interpreting different field data is illustrated resorting to real wind speed data. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. The results of a large set of numerical simulations—using typical values of wind-speed parameters—are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information. Full article
(This article belongs to the Special Issue Sizing and Allocation Strategies of Renewable Distributed Generations)
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Review

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20 pages, 698 KiB  
Review
A Review on Wind Speed Extreme Values Modeling and Bayes Estimation for Wind Power Plant Design and Construction
by Elio Chiodo, Bassel Diban, Giovanni Mazzanti and Fabio De Angelis
Energies 2023, 16(14), 5456; https://0-doi-org.brum.beds.ac.uk/10.3390/en16145456 - 18 Jul 2023
Cited by 2 | Viewed by 1086
Abstract
Rapid growth of the use of wind energy calls for a more careful representation of wind speed probability distribution, both for identification and estimation purposes. In particular, a key point of the above identification and estimation aspects is representing the extreme values of [...] Read more.
Rapid growth of the use of wind energy calls for a more careful representation of wind speed probability distribution, both for identification and estimation purposes. In particular, a key point of the above identification and estimation aspects is representing the extreme values of wind speed probability distributions, which are of great interest both for wind energy applications and structural tower reliability analysis. The paper reviews the most adopted probability distribution models and estimation methods. In particular, for reasons which are properly discussed, attention is focused on the evaluation of an opportune “safety index” related to extreme values of wind speeds or gusts. This topic has gained increasing attention in recent years in both wind energy generation assessment and also in risk and structural reliability and safety analysis. With regard to wind energy generation, there is great sensitivity in the relationship between wind speed extreme upper quantiles and the corresponding wind energy quantiles. Concerning the risk and reliability analysis of structures, extreme wind speed value characterization is useful for a proper understanding of the destructive wind forces that may affect structural tower reliability analysis and, consequently, the proper choice of the cut off wind speed value; therefore, the above two kinds of analyses are somewhat related to each other. The focus is on the applications of the Bayesian inference technique for estimating the above safety index due to its effectiveness and usefulness. Full article
(This article belongs to the Special Issue Sizing and Allocation Strategies of Renewable Distributed Generations)
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