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Energies
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Control and Optimization of Electrical Power and Energy Systems
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Control and Optimization of Electrical Power and Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: closed (5 January 2023) | Viewed by 5372

Special Issue Editors

Dr. Karthikeyan Shanmugam Prabhakar

E-Mail Website
Guest Editor
Department of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, India
Interests: electric vehicle modelling/scheduling; data analytics in power systems; deregulation/restructured power systems; power system optimization; home energy management systems
Dr. Kuppan Ravi

E-Mail Website
Guest Editor
Department of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, India
Interests: power system; power electronics applications in power system; smart grid; renewable energy; microgrid
Prof. Dr. Jacob Raglend

E-Mail Website
Guest Editor
Department of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, India
Interests: power quality; application of soft computing techniques; renewable energy systems integration and IOT devices; power system restructuring; reliability engineering

Special Issue Information

Dear Colleagues,

The business of energy generation, transmission and distribution has become smarter and more efficient, resilient and economical with the use of modern computational/optimization techniques. The field of power systems operation and planning has evolved into a multidisciplinary domain relying on experts with knowledge and skills in a multitude of areas.

The aim of this Special Issue is to bring together all the research works associated with power and energy systems that can be used to improve the operation of power systems and management practices. 

Dr. Karthikeyan Shanmugam Prabhakar
Dr. Kuppan Ravi
Prof. Dr. Jacob Raglend
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

  • transmission network planning
  • distribution system automation
  • power system protection, operation and control
  • power system security, reliability and planning
  • application of optimization algorithms in power systems
  • energy management system
  • V2G/G2V modelling and its impact on power systems
  • renewable energy penetration and grid integration—challenges and benefits
  • IoT application in a power system to enhance its security and control
  • power system stability and power quality issues
  • restructured electricity market—modelling, regulation, risk management, etc
  • peer-to-peer energy transactions
  • wide area monitoring system—challenges and benefits
  • data analytics in power systems

Published Papers (3 papers)

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Research

17 pages, 5058 KiB  
Article
Flexible Power Point Tracking Using a Neural Network for Power Reserve Control in a Grid-Connected PV System
by Jishu Mary Gomez and Prabhakar Karthikeyan Shanmugam
Energies 2022, 15(21), 8234; https://doi.org/10.3390/en15218234 - 04 Nov 2022
Cited by 4 | Viewed by 1574
Abstract
Renewable energy penetration in the global energy sector is in a state of steady growth. A major criterion imposed by the regulatory boards in the wake of electronic-driven power systems is frequency regulation capability. As more rooftop PV systems are under installation, the [...] Read more.
Renewable energy penetration in the global energy sector is in a state of steady growth. A major criterion imposed by the regulatory boards in the wake of electronic-driven power systems is frequency regulation capability. As more rooftop PV systems are under installation, the inertia response of the power utility system is descending. The PV systems are not equipped inherently with inertial or governor control for unseen frequency deviation scenarios. In the proposed method, inertial and droop frequency control is implemented by creating the necessary power reserve by the derated operation of the PV system. While, traditionally, PV systems operate in normal MPPT mode, a derated PV system follows a flexible power point tracking (FPPT) algorithm for creating virtual energy storage. The point of operation for the FPPT of the PV is determined by using a neural network block set available in MATLAB. For the verification of the controller, it is applied to a PV array in a modified IEEE-13 bus system modeled in the MATLAB/Simulink platform. The simulation results prove that when the proposed control is applied to the test network with renewable energy penetration, there is an improved system inertia response. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems)
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17 pages, 3902 KiB  
Article
Short-Term Load Forecasting with a Novel Wavelet-Based Ensemble Method
by V. Y. Kondaiah and B. Saravanan
Energies 2022, 15(14), 5299; https://doi.org/10.3390/en15145299 - 21 Jul 2022
Cited by 5 | Viewed by 1516
Abstract
“Short-term load forecasting (STLF)” is increasingly significant because of the extensive use of distributed energy resources, the incorporation of intermitted RES, and the implementation of DSM. This paper provides a novel ensemble forecasting model with wavelet transform for the STLF depending on the [...] Read more.
“Short-term load forecasting (STLF)” is increasingly significant because of the extensive use of distributed energy resources, the incorporation of intermitted RES, and the implementation of DSM. This paper provides a novel ensemble forecasting model with wavelet transform for the STLF depending on the decomposition principle of load profiles. The model can effectively capture the portion of daily load profiles caused by seasonal variations. The results indicate that it is possible to improve STLF accuracy with the proposed method. The proposed approach is tested with the data taken from Ontario’s electricity market in Canada. The results show that the proposed technique performs well in-terms of prediction when compared to existing traditional and cutting-edge methods. The performance of the model was validated with different datasets. Moreover, this approach can provide accurate load forecasting using ensemble models. Therefore, utilities and smart grid operators can use this approach as an additional decision-making tool to improve their real-time decisions. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems)
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24 pages, 4002 KiB  
Article
Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm
by Senthil Prabu Ramalingam and Prabhakar Karthikeyan Shanmugam
Energies 2022, 15(14), 5008; https://doi.org/10.3390/en15145008 - 08 Jul 2022
Cited by 5 | Viewed by 1417
Abstract
A remodeled sperm swarm optimization (RMSSO) algorithm for a home energy management (HEM) system is proposed, and its real-time efficacy was evaluated using a hardware experimental model. This home environment comprised sixteen residential loads, a smart meter and a Raspberry Pi controller to [...] Read more.
A remodeled sperm swarm optimization (RMSSO) algorithm for a home energy management (HEM) system is proposed, and its real-time efficacy was evaluated using a hardware experimental model. This home environment comprised sixteen residential loads, a smart meter and a Raspberry Pi controller to optimize the energy consumption cost (ECC) in response to the Indian day-ahead pricing (DAP) scheme. A wired/wireless communication network was considered to communicate with the smart meter and controller. To address this optimization problem, the sperm swarm optimization (SSO) algorithm’s constriction coefficient was remodeled to improve its global searching capability and proposed as RMSSO. For the first time, salp swarm optimization (SSA), SSO, and RMSSO algorithms were employed to schedule home appliances in the Indian scenario. To validate the proposed technique’s outcome, the results were compared to those of the conventional SSO and SSA algorithms. This problem was solved using the Python/GUROBI optimizer tool. As a consequence, consumers can use this control strategy in real-time to reduce energy consumption costs. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems)
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