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Recent Advances in Industrial Mathematics and Applications for Current Smart Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 2922

Special Issue Editors

Dr. Xiaodong Zheng

E-Mail Website
Guest Editor
School of Electrical Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Interests: operations research, statistical learning, power systems operation
Dr. Cong Zhang

E-Mail Website
Guest Editor
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Interests: Power system optimization, Interval power flow, Voltage control considering interval uncertainty, Interval optimization, Interval Mathematics
Dr. Zhengmao Li

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: optimal planning and operation of multi-energy systems; resilience in multi-energy systems; uncertainties handling in multi-energy systems; stochastic/robust optimization; multi-energy ship; optimization methods
Special Issues, Collections and Topics in MDPI journals
Dr. Tianyang Zhao

E-Mail Website
Guest Editor
Energy and Electric Research Center, Jinan University Zhuhai College, Zhuhai 162687, China
Interests: resilience; operations research; power systems

Special Issue Information

Dear Colleagues,

Greetings! We would like to to bring your attention to our special issue, Recent  Advances in Industrial Mathematics and Applications for Current Smart Energy Systems.

Advanced industrial mathematics has achieved tangible success in ubiquitous energy industry operations, both historically and presently. Inspired by this, this Special Issue focuses on the development and/or use of recent advances in industrial mathematics for the control, operation, and planning of the current energy systems including electric power, thermal, gas, water, and transportation systems or their combinations. Academics, industrial stakeholders, and research groups are invited to bring novel insights into problems related to current multi-energy systems, active distribution systems, smart grids, smart cities, green buildings, etc. This Special Issue provides a platform for our community to present novel and unpublished work in the domain of control theory, operations research, and machine learning that attacks the unsolved or emerging problems. This will contribute to facilitating future research in industrial mathematics related to the energy industry.

Topics of interest include, but are not limited to:

  1. Mathematical models and analytical characteristics of current smart energy systems;
  2. Deterministic reformulation techniques for uncertainty-incorporated mathematical programming problems;
  3. Exact algorithms for general multi-level mixed-integer linear programs with applications to energy systems;
  4. Interval mathematics, including interval analysis and optimization algorithms, with applications to energy systems;
  5. Efficient cutting-plane algorithms for multistage stochastic/robust/distributionally robust planning/scheduling models;
  6. Learning-based smart energy systems operation and control.

Dr. Xiaodong Zheng
Dr. Cong Zhang
Dr. Zhengmao Li
Dr. Tianyang Zhao
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. Energies 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 2600 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

  • industrial mathematics
  • control
  • operation and planning
  • energy systems
  • machine learning

Published Papers (2 papers)

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Research

13 pages, 1105 KiB  
Article
Convex-Optimization-Based Power-Flow Calculation Method for Offshore Wind Systems
by Yuwei Chen, Haifeng Qi, Hongke Li, Han Xu, Qiang Yang and Qing Chen
Energies 2022, 15(20), 7717; https://doi.org/10.3390/en15207717 - 19 Oct 2022
Viewed by 1048
Abstract
Offshore wind farms have boomed worldwide due to the sustainability of wind power and ocean resources. Power grid companies should consider the wind power consumption problem with more power generated. Power-flow calculation is the most fundamental tool in energy management. This paper proposes [...] Read more.
Offshore wind farms have boomed worldwide due to the sustainability of wind power and ocean resources. Power grid companies should consider the wind power consumption problem with more power generated. Power-flow calculation is the most fundamental tool in energy management. This paper proposes the convex-relaxation-based method for offshore wind farms’ power flow. In this method, the traditional equations’ problem solving is transferred into standard convex optimization, which can be solved efficiently with unique optimum. Second-order cone relaxations are imposed to describe the quadratic relationship. The exactness of the relaxation is guaranteed with the special definition of the objective function.The superiority of the proposed method is tested on the case study, for which a computational efficiency improvement is shown. Moreover, the reliability of the power-flow results is verified within the precision tolerance. Full article
(This article belongs to the Special Issue Recent Advances in Industrial Mathematics and Applications for Current Smart Energy Systems)
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19 pages, 6456 KiB  
Article
A Novel Interval Programming Method and Its Application in Power System Optimization Considering Uncertainties in Load Demands and Renewable Power Generation
by Dapeng Wang, Cong Zhang, Wanqing Jia, Qian Liu, Long Cheng, Huaizhi Yang, Yufeng Luo and Na Kuang
Energies 2022, 15(20), 7565; https://doi.org/10.3390/en15207565 - 13 Oct 2022
Cited by 1 | Viewed by 1038
Abstract
This paper expresses the output power of renewable generators and load demand as interval data and develops the interval economic dispatch (IED), as well as interval reactive power optimization (IRPO) models. The two models are generalized into a specific type of linear interval [...] Read more.
This paper expresses the output power of renewable generators and load demand as interval data and develops the interval economic dispatch (IED), as well as interval reactive power optimization (IRPO) models. The two models are generalized into a specific type of linear interval programming (LIP) and nonlinear interval programming (NLIP), respectively. A security limits method (SLM) is proposed to solve LIP and NLIP problems. As for the LIP, the maximum radii of the interval variables are first calculated by the optimizing-scenarios method (OSM) for defining security limits, and the LIP is transformed into deterministic linear programming (LP), for which its constraints are the security limits, which can be solved by the simplex method. As for the NLIP, Monte Carlo simulations were used to obtain the maximum radii of the interval variables, and the average interval ratio of the interval variables is defined to compute the security limits for transforming the NLIP to deterministic nonlinear programming (NLP), which can be solved by using the interior point method. Finally, the IED and IRPO are used to verify the effectiveness and engineering of the proposed SLM. Full article
(This article belongs to the Special Issue Recent Advances in Industrial Mathematics and Applications for Current Smart Energy Systems)
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