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Digitization, Flexibility and Energy Storage in Power Generation Systems Employing...
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Digitization, Flexibility and Energy Storage in Power Generation Systems Employing Renewable Energy

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: closed (30 August 2024) | Viewed by 1710

Special Issue Editors

Dr. Said Bentouba

E-Mail Website
Guest Editor
Faculty of Engineering and Science, Western Norway University of Applied Sciences, 5063 Bergen, Norway
Interests: thermoelectric power generation; hybrid energy harvesting systems; manufacturing of thermoelectric generators; thermoelectric materials; thermoelectricity
Special Issues, Collections and Topics in MDPI journals
Dr. Peter Breuhaus

E-Mail Website
Guest Editor
International Research Institute of Stavanger, Stavanger, Norway
Interests: thermoelectric power generation; hybrid energy harvesting systems; manufacturing of thermoelectric generators; thermoelectric materials; thermoelectricity
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mahmoud Bourouis

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Universitat Rovira i Virgili, 43007 Tarragona, Spain
Interests: absorption refrigeration and heat pumps; heat and mass transfer intensification; passive cooling; membrane contactors and miniaturization; thermoelectricity; hybrid energy harvesting systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nadjet Zioui

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Quebec at Trois-Rivieres, Trois-Rivières, QC, Canada
Interests: thermoelectric power generation; hybrid energy harvesting systems; manufacturing of thermoelectric generators; thermoelectric materials; thermoelectricity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Aim and Scope of the Special Issue

Since power generation employing renewable energy sources is subject to highly intermittent supplies, solutions to counter this need to be very flexible. The digitization of the power grid is giving rise to the emergence of new applications for energy storage, a key aspect of the power grid and flexibility. Digitization can play a key role in making the energy storage system more flexible, as it allows for real-time monitoring and control of the system, and provides data that can be used to optimize operation. The energy storage system is a crucial part of the power grid. It assists in stabilizing the grid by providing the extra energy required during times of peak demand and stores excess energy during times of low demand. By storing excess energy and releasing it when demand is high, this system evens out those fluctuations in demand and supply and makes the grid more reliable. The benefits of energy storage, whether centralized or decentralized, are many. Indeed, the technology can help to reduce carbon emissions by storing renewable energy that would otherwise be wasted, as well as improving grid security and reliability by providing backup energy in the case of outages. Consumers could reap the benefits of lower prices in their energy bills as the system would suffer less pressure during peak periods. Flexibility is a key feature for achieving benefits, as it represents the ability of energy systems to respond quickly to changes in demand. All of these potential benefits are owed digitization, which allows for real-time monitoring and control of the system as well as forecasting.

The benefits of digitization and flexibility outlined are making energy storage an increasingly attractive option for utilities and other energy providers. With continued advancements in technology, it is expected that energy storage will play an even more important role in future integrated energy grids, enabling more renewable sources of energy access to the grid and improving the efficiency of energy storage systems. Overall, the potential benefits of digitizing the energy system are highly significant. Digitization of the economy is leading to a more dynamic and interconnected world, where the traditional energy system is no longer adequate. A new energy storage system that is responsive to changes in demand and that can take advantage of renewable energy sources is required. Investigations focused on digitalization, renewable energies integration, flexibility and energy storage are welcome.

Scope and Information for authors

Original research and review articles including, but not limited to the following areas of interest are welcome:

  • Digitizing of energy system
  • Flexibility and Management of energy systems
  • Energy storage
  • Power generation systems
  • Multi agent and virtual power systems
  • Distributed energy storage and demand side integration
  • Hydrogen integration models
  • Integration of renewable energies

Prof. Dr. Said Bentouba
Dr. Peter Breuhaus
Prof. Dr. Mahmoud Bourouis
Prof. Dr. Nadjet Zioui
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

  • digitization
  • energy flexibility
  • energy storage
  • green hydrogen
  • hybrid energy system

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Published Papers (2 papers)

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Research

25 pages, 5650 KiB  
Article
Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-Based Meshed Hybrid AC/DC Microgrid Considering the Optimal Reactive Power Dispatch
by Rafael A. Núñez-Rodríguez, Clodomiro Unsihuay-Vila, Johnny Posada and Omar Pinzón-Ardila
Energies 2024, 17(16), 4036; https://doi.org/10.3390/en17164036 - 14 Aug 2024
Viewed by 408
Abstract
Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHMs) present a promising solution to enhance the efficiency of conventional microgrids (MGs) and facilitate higher integration of Distributed Energy Resources (DERs), simultaneously managing active and reactive power dispatch. However, MHMs face challenges in resource management [...] Read more.
Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHMs) present a promising solution to enhance the efficiency of conventional microgrids (MGs) and facilitate higher integration of Distributed Energy Resources (DERs), simultaneously managing active and reactive power dispatch. However, MHMs face challenges in resource management under uncertainty and control of electronic converters linked to the ST and DERs, complicating the pursuit of optimal system performance. This paper introduces a Data-Driven Distributionally Robust Optimization (DDDRO) approach for day-ahead operation planning in ST-based MHMs, focusing on minimizing network losses, voltage deviations, and operational costs by optimizing the reactive power dispatch of DERs. The approach accounts for uncertainties in photovoltaic generator (PVG) output and demand. The Column-and-Constraint Generation (C&CG) algorithm and the Duality-Free Decomposition (DFD) method are employed. The initial mixed-integer non-linear planning problem is also reformulated into a mixed-integer (MI) Second-Order Cone Programming (SOCP) problem using second-order cone relaxation and a positive octagonal constraint method. Simulation results on a connected MHM system validate the model’s efficacy and performance. The study also highlights the advantages of the meshed MG structure and the positive impact of integrating the ST into MHMs, leveraging the multi-stage converter’s flexibility for optimal energy management under uncertain conditions. Full article
(This article belongs to the Special Issue Digitization, Flexibility and Energy Storage in Power Generation Systems Employing Renewable Energy)
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23 pages, 1408 KiB  
Article
Energy Efficiency Assessment and Prediction Based on Indicator System, PSO + AHP − FCE Model and Regression Algorithm
by Yan Bai, Xingyi Ma, Jing Zhang, Lei Zhang and Jing Bai
Energies 2024, 17(8), 1931; https://doi.org/10.3390/en17081931 - 18 Apr 2024
Viewed by 756
Abstract
Energy-intensive enterprises lack a scientific and effective energy efficiency assessment framework and methodology. This lack leads to an inaccurate understanding of energy usage and its benefits. As a result, there is energy wastage and loss. This wastage and loss negatively affect product costs. [...] Read more.
Energy-intensive enterprises lack a scientific and effective energy efficiency assessment framework and methodology. This lack leads to an inaccurate understanding of energy usage and its benefits. As a result, there is energy wastage and loss. This wastage and loss negatively affect product costs. They also present a challenge to effective energy management. To address these issues, this paper introduces a novel, comprehensive energy efficiency evaluation system. This system integrates both qualitative and quantitative measures. It proposes an evaluation model based on the Particle Swarm Optimization (PSO) combined with the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE), wherein PSO is employed to optimize the weights determined by AHP, ensuring that the significance attributed to various indicators is scientific, objective, and rational. The FCE method is utilized to convert diverse factors affecting corporate energy efficiency, across different types and scales, into standardized 0–1 values, enabling a comparative analysis of the impact of each process and indicator on energy efficiency. Furthermore, the paper introduces an energy efficiency prediction model employing a multivariate linear regression algorithm, which demonstrates a good fit, facilitating the transition from retrospective energy efficiency evaluation to proactive improvements. Utilizing data on actual consumption of water, electricity, and steam from an enterprise, along with expert assessments on the implementation levels of new processes, technologies, equipment, personnel scheduling proficiency, steam recovery rates, and adherence to policies and assessments, a simulation experiment of the proposed model was conducted using Python. The evaluation yielded an energy efficiency score of 0.68; this is consistent with the real-world scenario of the studied enterprise. The predicted mean square error of 9.035416039503998 × 10−9 indicates a high model accuracy, validating the practical applicability and effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Digitization, Flexibility and Energy Storage in Power Generation Systems Employing Renewable Energy)
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