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Special Issue "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: 30 September 2023 | Viewed by 500

Special Issue Editors

School of Electrical Engineering, Southeast University, Nanjing 210096, China
Interests: renewable energy; smart grid; power conversion; stability analysis; power quality
Department of Electrical and Computer Engineering, University of Texas at San Antonio (UTSA), San Antonio, TX 78249, USA
Interests: applied artificial intelligence; smart power; intelligent systems; forecasting; intelligent data analytics
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 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 2200 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.


  • 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 (1 paper)

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Capacity Allocation Method Based on Historical Data-Driven Search Algorithm for Integrated PV and Energy Storage Charging Station
Sustainability 2023, 15(6), 5480; - 20 Mar 2023
Viewed by 279
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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