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Sustainable Power Systems and Optimization Volume II
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Sustainable Power Systems and Optimization Volume II

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

Deadline for manuscript submissions: closed (13 March 2024) | Viewed by 3869

Special Issue Editors

Prof. Dr. Xiaoqing Bai

E-Mail Website
Guest Editor
Guangxi Key Laboratory of Power System Optimization and Energy‑Saving Technology, Guangxi University, Nanning, China
Interests: power system analysis; optimization theory and application; data-driven; uncertainty
Special Issues, Collections and Topics in MDPI journals
Dr. Chun Wei

E-Mail Website
Guest Editor
College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
Interests: renewable energy; power electronics; wind power generation; intelligent control
Special Issues, Collections and Topics in MDPI journals
Dr. Dongliang Xiao

E-Mail Website
Guest Editor
School of Electric Power, South China University of Technology, Guangzhou, China
Interests: power and energy system optimization; electricity markets; renewable energy; risk management
Special Issues, Collections and Topics in MDPI journals
Dr. Yude Yang

E-Mail Website
Guest Editor
Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China
Interests: optimization for power system operation; transient stability; power system analysis; optimal power flow
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

To resolve global climate warming issues and promote sustainable development, the installed capacity of renewable energy in power systems has increased rapidly during the last two decades. Large numbers of renewable energy resources with intermittent characteristics, such as wind turbines, solar PVs, and electric vehicles, have been used in both power generation and demand, bringing significant challenges to the optimal planning, operation, and control of sustainable power systems. To cope with the uncertainties of sustainable power systems, decision-makers must utilize various flexible energy resources, such as battery storage, demand–response programs, and gas-fired generators. Additionally, coordinating power and other energy resources, such as natural gas, heat, and hydrogen, provides additional flexibility in power transmission and distribution systems.

The significant challenges of sustainable power system optimization are the complexities and uncertainties of both distribution and transmission levels. Under the deregulated power market environment, power system optimization models need to consider intermittent renewable power production and account for volatile electricity prices. As a result, it is necessary to investigate efficient optimization techniques for sustainable power systems, considering parameter uncertainties and system properties to maximize the economic benefits and minimize reliability concerns.

This Special Issue aims to report the latest advancements in sustainable power systems and optimization to solve potential difficulties and challenges. Authors are encouraged to submit their research regarding theoretical, methodological, or practical focuses, such as simulation models, algorithms, and applications concerning sustainable power systems and optimization.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Optimization techniques for sustainable power system planning, operation, and control.
  • Optimization techniques for sustainable power systems assisted by energy storage.
  • Optimization techniques for sustainable power systems with other types of energy, such as gas, heat, and hydrogen.
  • Optimization techniques for sustainable power system planning, operation, and control.
  • Security or stability analysis and correction of sustainable power systems.
  • Demand-side management in sustainable power systems.
  • Renewable energy trading in wholesale or retail electricity markets.
  • Multi-objective optimization techniques for sustainable power systems.
  • Distributed optimization techniques for sustainable power systems.
  • Local energy market mechanisms to accommodate distributed energy resources.
  • Techniques for handling nonlinearities and non-convexities of sustainable power system problems.
  • Heuristics algorithms for solving sustainable power system problems.

We look forward to receiving your contributions.

References

Chu S, Majumdar A. Opportunities and challenges for a sustainable energy future. Nature, 2012, 488(7411): 294-303.

Morales J M, Conejo A J, Madsen H, et al. Integrating renewables in electricity markets: operational problems. Springer Science & Business Media, 2013.

Wei, Z. Shen, D. Xiao, L. Wang, X. Bai, and H. Chen, An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining, Applied Energy, 2021.

Prof. Dr. Xiaoqing Bai
Dr. Chun Wei
Dr. Dongliang Xiao
Dr. Yude Yang
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

  • optimization techniques
  • sustainable power systems
  • renewable energy
  • distributed energy resources
  • demand-side management
  • electricity markets
  • energy storages
  • multi-objective optimization
  • heuristics algorithms
  • security or stability analysis

Published Papers (3 papers)

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Research

21 pages, 8604 KiB  
Article
Application of Comprehensive Evaluation of Line Loss Lean Management Based on Big-Data-Driven Paradigm
by Bin Li, Yuxiang Tan, Qingqing Guo and Weihuan Wang
Sustainability 2023, 15(15), 12074; https://doi.org/10.3390/su151512074 - 7 Aug 2023
Cited by 1 | Viewed by 873
Abstract
Effective line loss management necessitates a model-driven evaluation method to assess its efficiency level thoroughly. This paper introduces a “model-driven + data-driven” approach based on collective intelligence theory to address the limitations of individual evaluation methods in conventional line loss assessments. Initially, eight [...] Read more.
Effective line loss management necessitates a model-driven evaluation method to assess its efficiency level thoroughly. This paper introduces a “model-driven + data-driven” approach based on collective intelligence theory to address the limitations of individual evaluation methods in conventional line loss assessments. Initially, eight different evaluation methods are used to form collective intelligence to evaluate the line loss management of power grid enterprises and generate a comprehensive dataset. Then, the data set is trained and evaluated using the random forest algorithm, with Spearman rank correlation coefficient as the test metric, to assess the power grid enterprise’s line loss management level. Combining model-driven and data-driven methods, this integrated approach efficiently leverages the informational value of indicator data while thoroughly considering the causal and associative attributes within the dataset. Based on data from 61 municipal grid enterprises, both the comparison of multiple AI methods and correlation tests of results verify the superiority of the proposed method. Full article
(This article belongs to the Special Issue Sustainable Power Systems and Optimization Volume II)
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20 pages, 4819 KiB  
Article
Predictive Analysis and Correction Control of CCT for a Power System Based on a Broad Learning System
by Yude Yang, Huayi Fang and Lizhen Yang
Sustainability 2023, 15(12), 9155; https://doi.org/10.3390/su15129155 - 6 Jun 2023
Cited by 1 | Viewed by 922
Abstract
Transient stability is an important factor for the stability of a power system. With improvements in voltage levels, and the expansion of power network scales, the problem of transient stability is particularly prominent. When a power system circuit fails, if the operation time [...] Read more.
Transient stability is an important factor for the stability of a power system. With improvements in voltage levels, and the expansion of power network scales, the problem of transient stability is particularly prominent. When a power system circuit fails, if the operation time of the relay protection device is higher than the critical clearing time (CCT), the relay protection device cannot cut the fault line in a timely manner. It is essential to forecast and adjust the CCT to improve the stability of the system; therefore, a method is proposed in this paper to predict and evaluate the critical clearing time using the broad learning system (BLS). The sensitivity of the critical clearing time can be easily calculated based on the prediction results of the critical clearing time using BLS. Moreover, the critical clearing time can be modified using the BLS correction control model. The proposed method was verified using a 4-machine 11-node system and a 10-machine 39-node system. According to the experimental results, the proposed model can predict, evaluate, and correct the CCT very well. Full article
(This article belongs to the Special Issue Sustainable Power Systems and Optimization Volume II)
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14 pages, 1206 KiB  
Article
A Second-Order Cone Programming Model of Controlled Islanding Strategy Considering Frequency Stability Constraints
by Peijie Li, Di Xu, Hang Su and Zhiyuan Sun
Sustainability 2023, 15(6), 5386; https://doi.org/10.3390/su15065386 - 17 Mar 2023
Cited by 1 | Viewed by 1154
Abstract
Controlled islanding is an important defense mechanism for avoiding blackouts by dividing the system into several stable islands. Sustainable systems that incorporate a high proportion of renewable energy are prone to frequency instability or even severe blackout events due to extreme weather conditions. [...] Read more.
Controlled islanding is an important defense mechanism for avoiding blackouts by dividing the system into several stable islands. Sustainable systems that incorporate a high proportion of renewable energy are prone to frequency instability or even severe blackout events due to extreme weather conditions. Thus, it is critical to investigate controlled islanding considering frequency stability constraints to reduce the risk of a sustainable system collapse in extreme weather conditions. Here, the frequency constraint of islands is derived based on the law of energy conservation, and the island connectivity constraint is proposed based on the idea of network flow. A controlled island second-order cone programming model with frequency stability constraints is proposed for the islanding strategy. The consideration of frequency constraints can help to avoid islands with too low inertia generated by the islanding strategies, ensuring that the frequency nadir of the island remains within a safe range after disturbance. Connectivity constraints can ensure connectivity within the island and no connectivity between different islands. The model also meets the reactive power balance and voltage limits in the system. Simulations of the three test systems show that this island model, which takes frequency stability into account, is effective in reducing the risk of sustainable power system collapse in extreme weather conditions. Full article
(This article belongs to the Special Issue Sustainable Power Systems and Optimization Volume II)
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