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Sustainable Power System Optimization: Operation, Distribution and Application

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 7785

Special Issue Editors

School of Electrical Engineering, Southeast University, Nanjing 210096, China
Interests: renewable energy; smart grid; power conversion; stability analysis; power quality
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
Interests: alternative fuels; energy conversion & storage; hydrogen economy; thermal energy engineering
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Guest Editor
Department of Electrical and Computer Engineering, University of Texas at San Antonio (UTSA), San Antonio, TX 78249, USA
Interests: AI in radiation detection and nuclear security; AI in radiation sensor networks
Special Issues, Collections and Topics in MDPI journals
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Interests: modular multilevel converters; motor driven; fault diagnosis

Special Issue Information

Dear Colleagues,

The reduction of fossil fuel and climate change have made the world gradually focus on the development of renewable energy. Renewable energy systems are replacing traditional energy sources at a rapid rate, represented by photovoltaics, wind power, and others. Subsequently, how to generate and use renewable energy more efficiently has gradually become a great challenge. There are many topics worth exploring in all stages of the renewable energy system, including generation, distribution and end-use applications. For example, the key technologies involved include modeling of complex renewable energy systems, reliability analysis, typical applications, system optimization design, energy markets and policies, etc. Solving these outstanding issues, especially how to use it efficiently, has significant implications for the development of renewable energy technologies and applications.

This Special Issue seeks high-quality contributions in the field of renewable energy generation, distribution, applications, etc., covering topics including but not limited to the following: renewable energy system optimization, power conversion, energy storage systems, stability analysis and optimal design for power electronic-based system, energy policy and markets, renewable energy generation, electric vehicle applications, microgrids, reliability of complex systems, modeling of complex systems, etc. All prospective authors with novel ideas are invited to submit original contributions or survey papers for review for publication.

Dr. Kangli Liu
Dr. Yiji Lu
Dr. Miltiadis (Miltos) Alamaniotis
Dr. Na Chai
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. Sustainability 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 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

  • renewable energy system optimization
  • power electronics for renewable energy system
  • stability and reliability
  • system modelling
  • energy policy and markets
  • renewable energy generation
  • electric vehicle
  • microgrids
  • energy storage system

Published Papers (7 papers)

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Research

23 pages, 3820 KiB  
Article
Optimal Allocation of Capacitor Banks and Distributed Generation: A Comparison of Recently Developed Metaheuristic Optimization Techniques on the Real Distribution Networks of ALG-AB-Hassi Sida, Algeria
by Khaled Fettah, Talal Guia, Ahmed Salhi, Souhil Mouassa, Alessandro Bosisio and Rouzbeh Shirvani
Sustainability 2024, 16(11), 4419; https://doi.org/10.3390/su16114419 - 23 May 2024
Viewed by 411
Abstract
Recent advancements in renewable energy technologies, alongside changes in utility infrastructure and progressive government policies, have bolstered the integration of renewable-based distributed generation units within distribution systems. This paper introduces the Energy Valley Optimizer, a novel tool designed for the strategic placement of [...] Read more.
Recent advancements in renewable energy technologies, alongside changes in utility infrastructure and progressive government policies, have bolstered the integration of renewable-based distributed generation units within distribution systems. This paper introduces the Energy Valley Optimizer, a novel tool designed for the strategic placement of distributed generation units and capacitor banks. This placement is crucial not only for optimizing energy loss and enhancing bus voltage stability but also for promoting sustainable energy use and reducing environmental impact over the long term. By minimizing energy loss and voltage fluctuations, the optimizer contributes to a more sustainable and resilient energy system. It achieves this through the optimal allocation of resources across various load patterns within a 24 h period and is tested on the ALG-AB-Hassi-Sida 157-bus distribution network in South Algeria. Comparative analysis with existing algorithms—such as the Liver Cancer Algorithm, Walrus Optimization Algorithm, and Zebra Optimization Algorithm—demonstrates the superior performance of the Energy Valley Optimizer. It not only enhances technical and economic efficiencies but also significantly lowers the total cost of energy over 24 years, thus supporting sustainable development goals in energy management. Full article
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28 pages, 1282 KiB  
Article
Unit Commitment Considering Electric Vehicles and Renewable Energy Integration—A CMAES Approach
by Qun Niu, Lipeng Tang, Litao Yu, Han Wang and Zhile Yang
Sustainability 2024, 16(3), 1019; https://doi.org/10.3390/su16031019 - 25 Jan 2024
Cited by 2 | Viewed by 1098
Abstract
Global fossil fuel consumption and associated emissions are continuing to increase amid the 2022 energy crisis and environmental pollution and climate change issues are becoming even severer. Aiming at energy saving and emission reduction, in this paper, a new unit commitment model considering [...] Read more.
Global fossil fuel consumption and associated emissions are continuing to increase amid the 2022 energy crisis and environmental pollution and climate change issues are becoming even severer. Aiming at energy saving and emission reduction, in this paper, a new unit commitment model considering electric vehicles and renewable energy integration is established, taking into account the prediction errors of emissions from thermal units and renewable power generations. Furthermore, a new binary CMAES, dubbed BCMAES, which uses a signal function to map sampled individuals is proposed and compared with eight other mapping functions. The proposed model and the BCMAES algorithm are then applied in simulation studies on IEEE 10- and IEEE 118-bus systems, and compared with other popular algorithms such as BPSO, NSGAII, and HS. The results confirm that the proposed BCMAES algorithm outperforms other algorithms for large-scale mixed integer optimization problems with over 1000 dimensions, achieving a more than 1% cost reduction. It is further shown that the use of V2G energy transfer and the integration of renewable energy can significantly reduce both the operation costs and emissions by 5.57% and 13.71%, respectively. Full article
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16 pages, 2430 KiB  
Article
Resilience-Driven Optimal Sizing of Energy Storage Systems in Remote Microgrids
by Irina Picioroaga, Madalina Luca, Andrei Tudose, Dorian Sidea, Mircea Eremia and Constantin Bulac
Sustainability 2023, 15(22), 16002; https://doi.org/10.3390/su152216002 - 16 Nov 2023
Cited by 2 | Viewed by 917
Abstract
As climate changes intensify the frequency of severe outages, the resilience of electricity supply systems becomes a major concern. In order to simultaneously combat the climate problems and ensure electricity supply in isolated areas, renewable energy sources (RES) have been widely implemented in [...] Read more.
As climate changes intensify the frequency of severe outages, the resilience of electricity supply systems becomes a major concern. In order to simultaneously combat the climate problems and ensure electricity supply in isolated areas, renewable energy sources (RES) have been widely implemented in recent years. However, without the use of energy storage, they show low reliability due to their intermittent output. Therefore, this article proposes a methodology to achieve the optimal sizing of an energy storage system (ESS) to ensure predefined periods of safe operation for an ensemble consisting of multiple loads, renewable energy sources and controllable generators, located in a remote microgrid. In this regard, a mixed integer linear programming (MILP) model has been proposed to reduce the outages impact of critical loads by calculating the optimal ESS capacity and defining the proper resources management within the off-grid microgrid, while ensuring a cost-effective operation of its components. Full article
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17 pages, 1774 KiB  
Article
An Optimization Ensemble for Integrated Energy System Configuration Strategy Incorporating Demand–Supply Coordination
by Chenhao Sun, Xiwei Jiang, Zhiwei Jia, Kun Yu, Sheng Xiang and Jianhong Su
Sustainability 2023, 15(21), 15248; https://doi.org/10.3390/su152115248 - 25 Oct 2023
Viewed by 723
Abstract
As one representative smart energy infrastructure in smart cities, an integrated energy system (IES) consists of several types of energy sources, thus making more complicated coupling connections between the supply and demand sides than a power grid. This will impact when allocating different [...] Read more.
As one representative smart energy infrastructure in smart cities, an integrated energy system (IES) consists of several types of energy sources, thus making more complicated coupling connections between the supply and demand sides than a power grid. This will impact when allocating different energy sources to ensure the appropriate energy utilization in the IES. With this motivation, an IES energy configuration optimization strategy based on a multi-model ensemble is proposed in this paper. Firstly, one coupling model is constructed to assess the underlying collaborative relationships between two sides for a renewable-energy-connected IES. Next, the independent component analysis (ICA) method is implemented for noise reduction in massive heterogeneous input databases, which can effectively improve the computing efficiency under such high-dimensional data conditions. Also, the self-adaptive quantum genetic model (SAQGM) is built for subsequent configuration optimization. Specifically, the quantum bit representation is incorporated to reduce computation complexity in multi-states scenarios, the double-chain formation of chromosomes is deployed to diminish the uncertainty when encoding, and the dynamic adaptation quantum gate is established to successively amend parameters. Finally, an empirical case study is conducted which can demonstrate the benefits of this strategy in terms of feasibility, efficiency, and economy. Full article
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21 pages, 5089 KiB  
Article
Two-Stage Grid-Connected Frequency Regulation Control Strategy Based on Photovoltaic Power Prediction
by Shuzheng Wang, Haiming Zhu and Shaowen Zhang
Sustainability 2023, 15(11), 8929; https://doi.org/10.3390/su15118929 - 1 Jun 2023
Cited by 4 | Viewed by 1305
Abstract
The large number of photovoltaics connected to the distribution network via power electronic converters squeezes the functional space of traditional synchronous generators in the power system and reduces the inertia of the network itself. However, due to the random and fluctuating nature of [...] Read more.
The large number of photovoltaics connected to the distribution network via power electronic converters squeezes the functional space of traditional synchronous generators in the power system and reduces the inertia of the network itself. However, due to the random and fluctuating nature of PV power generation, different types of meteorological conditions can also affect the inertia support capability of PV output power. Therefore, this paper proposes a frequency regulation control strategy based on the dynamic characteristics of the grid-side DC capacitor. Firstly, the control strategy of the grid-side inverter is improved and the mechanism of the frequency dynamic response model under PV penetration is analysed. Secondly, data from different weather types are correlated and analysed to predict PV power, and wireless sensor technology is used to introduce the data signals into the control link. Finally, a simulation model of a two-stage PV power generation system is developed and the fast-response capability of the system under different control parameters when the load is increased or decreased is analysed. The results show that under the proposed frequency regulation strategy, the larger the regulation coefficient and virtual inertia time constant, the greater the virtual inertia provided by the PV power generation, which improves the stability of the distribution network. Full article
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29 pages, 16009 KiB  
Article
Mitigating Low-Frequency Oscillations and Enhancing the Dynamic Stability of Power System Using Optimal Coordination of Power System Stabilizer and Unified Power Flow Controller
by Endeshaw Solomon, Baseem Khan, Ilyes Boulkaibet, Bilel Neji, Nadhira Khezami, Ahmed Ali, Om Prakash Mahela and Alina Eugenia Pascual Barrera
Sustainability 2023, 15(8), 6980; https://doi.org/10.3390/su15086980 - 21 Apr 2023
Cited by 2 | Viewed by 1226
Abstract
The integration of a flexible alternating current transmission system (FACTS) and a power system stabilizer (PSS) can increase dynamic stability. This paper presents the enhancement of power system dynamic stability through the optimal design of a power system stabilizer and UPFC using an [...] Read more.
The integration of a flexible alternating current transmission system (FACTS) and a power system stabilizer (PSS) can increase dynamic stability. This paper presents the enhancement of power system dynamic stability through the optimal design of a power system stabilizer and UPFC using an ant lion optimization (ALO) technique to enhance transmission line capacity. The gained damping ratio, eigenvalue and time domain results of the suggested ALO technique were compared with a base case system, ALO-based PSS and ALO-based PSS-UPFC to test the effectiveness of the proposed system in different loading cases. Eigenvalues gained from an ant lion approach-based UPFC with a PSS and a base case system are compared to examine the robustness of the ALO method for various loading conditions. Thus, this paper addresses the mechanism regarding the power system dynamic stability of transmission lines by integrating the optimal size of a PSS and UPFC into the power system. Therefore, the main contribution of this manuscript is the optimal coordination of a power system stabilizer, power oscillation damper and unified power flow using ant lion optimization for the mitigation of low-frequency oscillation. Full article
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16 pages, 3339 KiB  
Article
Capacity Allocation Method Based on Historical Data-Driven Search Algorithm for Integrated PV and Energy Storage Charging Station
by Xiaogang Pan, Kangli Liu, Jianhua Wang, Yutao Hu and Jianfeng Zhao
Sustainability 2023, 15(6), 5480; https://doi.org/10.3390/su15065480 - 20 Mar 2023
Cited by 5 | Viewed by 1263
Abstract
The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy [...] Read more.
The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations. Full article
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