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Special Issue "Theories and Applications of Sustainable Energy Systems and Smart Power Grids"

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Guest Editor

School of Electrical and Information Engineering, Tianjin University, Tianjin, China
Interests: deep learning; image processing; power electronics applications

Dr. Yuenan Li

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Guest Editor

School of Electrical and Information Engineering, Tianjin University, Tianjin, China
Interests: signal processing; machine learning; deep neural network

Dr. Leijiao Ge

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Guest Editor

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: distribution smart grid; cloud computing; big data
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Special Issue Information

Dear Colleagues,

The world is facing increasingly serious energy and environmental crises. Sustainable energy systems and smart grids play vital roles in solving the non-renewable problem of traditional fossil energy and protecting the environment, as well as improving the efficiency of resource utilization. Research on the theories and applications of sustainable energy systems and smart power grids has attracted considerable attention. The Special Issue covers both new developments, recent advances, emerging trends, and the state-of-the-art technologies in related fields.

The main topics include 1) fundamentals, modeling, control, optimization, and simulation aspects of sustainable energy systems and smart grids; 2) grid integration of renewables; 3) micro-grids; 4) distribution networks; 5) low-inertia power systems; 6) planning and operation of smart grids; 7) energy storage technologies; 8) technologies and applications of superconductivity; and 9) intelligent operation and maintenance. Since sustainable energy resource and smart grid facilities are quite different in different countries and regions, a wide range of contributions are invited from all over the world.

Dr. Xinshan Zhu
Dr. Yuenan Li
Dr. Leijiao Ge
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 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.

Keywords

smart grid
power system
renewable
solar
wind
energy storage
superconductivity
maintenance
data driven
deep learning

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Research

Open AccessArticle

Multi-Source Information Fusion Technology and Its Application in Smart Distribution Power System

and

Sustainability 2023, 15(7), 6170; https://doi.org/10.3390/su15076170 - 03 Apr 2023

Viewed by 743

Abstract

Compared to traditional measurement devices, the micro-synchrophasor measurement unit (D-PMU or μPMU) in the distribution power system has great differences in data acquisition frequency, data format, data dimension, time-stamped information, etc. Hence, it is imperative to research the integration mechanism of heterogeneous data from multiple sources. Based on the analysis of the current technology of multi-source information fusion, this paper proposes a novel approach, which considers two aspects: the interoperability of multi-source data and the real-time processing of large-scale streaming data. To solve the problem of data interoperability, we have modified the model of D-PMU data and established a unified information model. Meanwhile, an advanced distributed processing technology has been deployed to solve the problem of real-time processing of streaming data. Based on this approach, a smart distribution power system wide-area measurement and control station can be established, and the correctness and practicality of the proposed method are verified by an on-field project. Full article

(This article belongs to the Special Issue Theories and Applications of Sustainable Energy Systems and Smart Power Grids)

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Open AccessArticle

Two-Stage Robust Optimal Scheduling of Flexible Distribution Networks Based on Pairwise Convex Hull

and

Sustainability 2023, 15(7), 6093; https://doi.org/10.3390/su15076093 - 31 Mar 2023

Viewed by 430

Abstract

With distributed generation (DG) being continuously connected into distribution networks, the stochastic and fluctuating nature of its power generation brings ever more problems than before, such as increasing operating costs and frequent voltage violations. However, existing robust scheduling methods of flexible resources tend to make rather conservative decisions, resulting in high operation costs. In view of this, a two-stage robust optimal scheduling method for flexible distribution networks is proposed in this paper, based on the pairwise convex hull (PWCH) uncertainty set. A two-stage robust scheduling model is first formulated considering coordination among on-load tap changers, energy storage systems and flexible distribution switches. In the first stage, the temporal correlated OLTCs and energy storage systems are globally scheduled using day-ahead forecasted DG outputs. In the second stage, FDSs are scheduled in real time in each time period based on the first-stage decisions and accurate short-term forecasted DG outputs. The spatial correlation and uncertainties of the outputs of multiple DGs are modeled based on the PWCH, such that the decision conservativeness can be reduced by cutting regions in the box with low probability of occurrence. The improved column-and-constraint generation algorithm is then used to solve the robust optimization model. Through alternating iterations of auxiliary variables and dual variables, the nonconvex bilinear terms induced by the PWCH are eliminated, and the subproblem is significantly accelerated. Test results on the 33-bus distribution system and a realistic 104-bus distribution system validate that the proposed PWCH-based method can obtain much less conservative scheduling schemes than using the box uncertainty set. Full article

(This article belongs to the Special Issue Theories and Applications of Sustainable Energy Systems and Smart Power Grids)

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Special Issue "Theories and Applications of Sustainable Energy Systems and Smart Power Grids"

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