Cyber–Physical–Social System for Sustainable Energy

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (15 November 2022) | Viewed by 2054

Special Issue Editors


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Guest Editor
College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Interests: energy Internet; demand response; electricity market

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Guest Editor
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Interests: demand response; demand side management; power information and communication technology; automation of electric power systems
College of Electrical and Information Engineering, Hunan University, Changsha, China
Interests: fault diagnose; power system; power electronics

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Guest Editor
School of Electrical and Computing Engineering, University of Campinas, São Paulo, Brazil
Interests: Electrical Engineering; Power systems; Electromagnetic Transients

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Guest Editor
Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa
Interests: power system economics; green economy; HVDC

Special Issue Information

Dear Colleagues,

With the development of Internet of Things (IoT) technology, energy systems and information networks have been mutually coupled and deeply interact with each other in both academia and industry, which makes the application of a cyber-physical system (CPS) in an energy system a research hotspot. On the other hand, the IoT technology strengthens the connection between people and things more in-depth; hence, the concept of a cyber–physical–social system (CPSS) has been put forward. Based on CPS, CPSS further incorporates social information and artificial system information into virtual space, extending the research scope to social network systems. Considering the global decarbonization of energy systems, the impacts of macroscopic social policies and microscopic subject behaviors on the planning, development, operation control, trading and sharing of energy systems cannot be ignored. Therefore, CPSS research in the field of energy has a positive impact on the development of future energy systems. However, integrating social, physical and information layers together can be big challenges in developing CPSS for energy systems. Creative views and technologies are needed in this area.

This Special Issue encourages the submission of state-of-the-art research in CPSSs for sustainable energy systems. Topics of interest include (but are not limited to) the following subject categories:

  • Awareness for future energy system from CPSS view;
  • Cyber–physical–social interaction mechanism for energy system;
  • Data processing and mining in CPSS
  • Optimal planning, operation of energy systems;
  • Macroscopic policies for sustainable energy systems;
  • Microscopic behavior analysis for planners, operators, users and market players in energy systems;
  • IoT techniques for energy systems;
  • Risk assessment for energy system and energy transactions;
  • Cyber–physical–social modeling and simulation of energy systems;
  • Cyber security techniques for energy systems;
  • Multi-agent simulation for energy markets;
  • Energy sharing and transactive community on the demand side;
  • Practical construction and operation for CPS/CPSS in energy systems.

Dr. Haochen Hua
Prof. Dr. Yi Sun
Dr. Xu Chu
Prof. Dr. Maria Cristina Tavares
Prof. Dr. Pathmanathan (Pat) Naidoo
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. Information 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 1600 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

  • cyber–physical–social system
  • energy system
  • cyber security
  • risk assessment
  • behavior analysis

Published Papers (1 paper)

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Research

17 pages, 2208 KiB  
Article
A Time-Varying Incentive Optimization for Interactive Demand Response Based on Two-Step Clustering
by Fei Li, Bo Gao, Lun Shi, Hongtao Shen, Peng Tao, Hongxi Wang, Yehua Mao and Yiyi Zhao
Information 2022, 13(9), 421; https://doi.org/10.3390/info13090421 - 7 Sep 2022
Cited by 1 | Viewed by 1349
Abstract
With the increasing marketization of electricity, residential users are gradually participating in various businesses of power utility companies, and there are more and more interactive adjustments between load, source, and grid. However, the participation of large-scale users has also brought challenges to the [...] Read more.
With the increasing marketization of electricity, residential users are gradually participating in various businesses of power utility companies, and there are more and more interactive adjustments between load, source, and grid. However, the participation of large-scale users has also brought challenges to the grid companies in carrying out demand-side dispatching work. The user load response is uneven, and users’ behavioral characteristics are highly differentiated. It is necessary to consider the differences in users’ electricity consumption demand in the design of the peak–valley load time-sharing incentives, and to adopt a more flexible incentive form. In this context, this paper first establishes a comprehensive clustering method integrating k-means and self-organizing networks (SONs) for the two-step clustering and a BP neural network for reverse adjustment and correction. Then, a time-varying incentive optimization for interactive demand response based on two-step clustering is introduced. Furthermore, based on the different clustering results of customers, the peak–valley load time-sharing incentives are formulated. The proposed method is validated through case studies, where the results indicate that our method can effectively improve the users’ load characteristics and reduce the users’ electricity costs compared to the existing methods. Full article
(This article belongs to the Special Issue Cyber–Physical–Social System for Sustainable Energy)
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