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Modeling, Optimization, Control and Demand Response of Electric 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 (29 February 2024) | Viewed by 21336

Special Issue Editors


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Guest Editor
School of Engineering and Computer Science, University of the Pacific, Stockton, CA 95211, USA
Interests: energy efficiency; sustainable precision agriculture; autonomous unmanned vehicle systems; digitally transformative techniques and controls

Special Issue Information

Dear Colleagues,

Energy is one of the most important never-ending needs that human beings have. Due to the exponential growth in power consumption and energy demand in the era of technology-driven societies, the necessity for more stable and efficient power system with zero-emission models is in desperate need. However, the complexity of such power systems has pushed the traditional models to the limit. Existing and emerging solutions are becoming difficult to implement due to the growing complications pertaining to on- and off-grid situations. Interests regarding the modelling of robust and resilient electric power and energy systems, with optimization scheme for existing resource utilization, and efficient control strategies, are burgeoning among researchers to meet the increasing demand of the energy. Applications to cars, storage devices, or robots are also welcomed.

The purpose of this Special Issue is to solve these problems together, collect collaborative research in various spectra, and contribute to the research globally in relation to power generation, transmission, or distribution systems modelling, optimization, and control. The bottom line of this Special Issue is to establish more reliable, sustainable, and intelligent power system and energy models to solve a complex power system. The research in this Special Issue thus includes, but is not limited to:

  1. Energy demand, uncertainties, challenges, and stability issues
  2. Novel energy and power system models
  3. Dynamic and steady-state responses in power systems
  4. Quality and stable energy based on modelling and control methodologies
  5. Generation, transmission, distribution, and energy storage
  6. On-/off-grids with clean Renewable energy sources and reduction in gas emissions
  7. Modelling of various control strategies for robust and resilient grid systems
  8. Power system automation, optimization, artificial intelligence, or sustainability
  9. Alternative energy and power system solutions
  10. Application to electric (hybrid) cars, robots, flying vehicles or their batteries

Prof. Dr. Don Lee
Prof. Dr. Eklas Hossain
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

  • Power Systems
  • Energy Systems
  • Renewable Energy
  • Microgrid
  • Smart Grid
  • Modelling
  • Power Electronics
  • Control Systems
  • Automation
  • Steady-state and Dynamic Response
  • Grid Stability
  • Optimization
  • Energy Storage
  • Solar Photovoltaic
  • Wind Turbine
  • Geothermal Energy
  • Fuel Cell
  • Hydrogen
  • Biofuels
  • Sustainability
  • Grid Resilience and Reliability
  • Predictive Algorithms
  • Artificial Intelligence
  • Machine Learning
  • Efficiency
  • Micro-energy
  • Energy-efficient
  • Low-power
  • Self-powered Robots
  • Solid-state Battery
  • Data Analytics
  • Numerical Solutions
  • Security
  • Demand Response

Published Papers (9 papers)

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Research

17 pages, 3750 KiB  
Article
Optimal Observer-Based Power Imbalance Allocation for Frequency Regulation in Shipboard Microgrids
by Gianmario Rinaldi, Devika K. Baby and Prathyush P. Menon
Energies 2024, 17(7), 1703; https://doi.org/10.3390/en17071703 - 02 Apr 2024
Viewed by 460
Abstract
This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite [...] Read more.
This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite time. This estimate is then passed to an online high-level optimal control framework to periodically determine the optimal sequence of power reference values for each energy storage device (ESS), minimising the operational cost of the SMG. The online optimised power reference values are interpolated and passed to the low-level STA control strategy to control the output power of each ESS. The efficacy of the proposed methods is demonstrated through numerical simulations conducted on a prototypical model of an SMG equipped with two ESSs, namely batteries and fuel cells with associated hydrogen storage. Full article
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19 pages, 4493 KiB  
Article
A Novel Analytical Formulation of SiC-MOSFET Losses to Size High-Efficiency Three-Phase Inverters
by Pedro Costa, Sónia Pinto and José Fernando Silva
Energies 2023, 16(2), 818; https://doi.org/10.3390/en16020818 - 11 Jan 2023
Cited by 6 | Viewed by 1743
Abstract
This paper presents a novel analytical loss formulation to predict the efficiency of three-phase inverters using silicon carbide (SiC) metal—oxide—semiconductor field-effect transistors (MOSFETs). The proposed analytical formulation accounts for the influence of the output current harmonic distortion on the conduction losses as well [...] Read more.
This paper presents a novel analytical loss formulation to predict the efficiency of three-phase inverters using silicon carbide (SiC) metal—oxide—semiconductor field-effect transistors (MOSFETs). The proposed analytical formulation accounts for the influence of the output current harmonic distortion on the conduction losses as well as the impact of the output parasitic capacitances and the deadtime on the switching losses. The losses are formulated in balanced conditions to select suitable SiC MOFETs for the desired target efficiency. To validate the proposed methodology, a 3-phase inverter is designed to present full load efficiency in excess of 99% when built using SiC MOSFETs antiparalleled with SiC Schottky diodes selected for the specified full load efficiency. Experimental assessment of the designed inverter efficiency is compared with the expected values from the proposed analytical formulation and shown to match or exceed the predicted results for loads ranging from 40% to 100% of full load. Full article
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17 pages, 505 KiB  
Article
Bilateral Contracting and Price-Based Demand Response in Multi-Agent Electricity Markets: A Study on Time-of-Use Tariffs
by Hugo Algarvio and Fernando Lopes
Energies 2023, 16(2), 645; https://doi.org/10.3390/en16020645 - 05 Jan 2023
Cited by 3 | Viewed by 1796
Abstract
Electrical energy can be traded in liberalized organized markets or by negotiating private bilateral contracts. Competitive markets are central systems where market players can purchase and sell electrical energy. Bilateral contracting consists typically in a private negotiation of power over several months or [...] Read more.
Electrical energy can be traded in liberalized organized markets or by negotiating private bilateral contracts. Competitive markets are central systems where market players can purchase and sell electrical energy. Bilateral contracting consists typically in a private negotiation of power over several months or years between two parties. Price-based demand response considers the active participation of consumers in electricity markets. Consumers adopt demand response programs when responding to market prices or tariffs, as they change over time. Those tariffs can be proposed by retailers by considering their load shape goals, influencing consumers to change their behavior. Consumers may adopt strategies from two different groups, namely by curtailing energy at times of high prices (e.g., peak and intermediate periods) and rescheduling energy away from those times to other times (shifting). This article considers bilateral contracting in electricity markets with demand response. It investigates how curtailment and shifting affect the energy quantity and energy cost of consumers that adopt a time-of-use tariff involving three block periods (i.e., base, intermediate and peak periods). The results indicate that consumers respond to changes in energy price according to their consumption flexibility, while retailers do not always change energy price in response to consumers’ efforts to change their consumption patterns. On average, by considering a 5% consumption reduction in the intermediate and peak periods by a consumer agent, a retailer agent reduces the energy price only by 1.5%. Full article
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18 pages, 5170 KiB  
Article
An Evaluation of Co-Simulation for Modeling Coupled Natural Gas and Electricity Networks
by Brian Sergi and Kwabena Pambour
Energies 2022, 15(14), 5277; https://doi.org/10.3390/en15145277 - 21 Jul 2022
Cited by 2 | Viewed by 1538
Abstract
Reliance on natural gas for power generation has increased the coupling between gas and power networks. While this coupling can bring operational and economic benefits, it can also yield challenges, as the constraints in one system can impact the other. Co-simulation can capture [...] Read more.
Reliance on natural gas for power generation has increased the coupling between gas and power networks. While this coupling can bring operational and economic benefits, it can also yield challenges, as the constraints in one system can impact the other. Co-simulation can capture the constraints and interactions between these systems, but so far, there has been limited comparison of co-simulation results to those of an integrated model. In this work, we develop a new co-simulation framework using the HELICS platform and the SAInt tool for modeling transient gas and AC optimal power flow. We evaluate this co-simulation framework against a fully integrated version of the SAInt power and gas simulators, thus providing a benchmarking of the co-simulation approach. We compare results across the two approaches for two test networks and a network representing the Belgian power and gas networks, testing both normal operating conditions and cases with compressor disruptions. In each of the cases tested, we find nearly identical results from the two approaches across various metrics of interest, such as nodal pressure, gas flow rates, and active power generation. This alignment suggests that co-simulation can yield comparable results to fully integrated models for modeling coupled gas and electricity networks. Full article
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20 pages, 6927 KiB  
Article
Thermoeconomic Optimization of Steam Pressure of Heat Recovery Steam Generator in Combined Cycle Gas Turbine under Different Operation Strategies
by Zhen Wang and Liqiang Duan
Energies 2021, 14(16), 4991; https://doi.org/10.3390/en14164991 - 14 Aug 2021
Cited by 6 | Viewed by 2152
Abstract
The optimization of the steam parameters of the heat recovery steam generators (HRSG) of Combined Cycle Gas Turbines (CCGT) has become one of the important means to reduce the power generation cost of combined cycle units. Based on the structural theory of thermoeconomics, [...] Read more.
The optimization of the steam parameters of the heat recovery steam generators (HRSG) of Combined Cycle Gas Turbines (CCGT) has become one of the important means to reduce the power generation cost of combined cycle units. Based on the structural theory of thermoeconomics, a thermoeconomic optimization model for a triple pressure reheat HRSG is established. Taking the minimization of the power generation cost of the combined cycle system as the optimization objective, an optimization algorithm based on three factors and six levels of orthogonal experimental samples to determine the optimal solution for the high, intermediate and low pressure steam pressures under different gas turbine (GT) operation strategies. The variation law and influencing factors of the system power generation cost with the steam pressure level under all operation strategies are analyzed. The research results show that the system power generation cost decreases as the GT load rate increases, T4 plays a dominant role in the selection of the optimal pressure level for high pressure (HP) steam and, in order to obtain the optimum power generation cost, the IGV T3-650-F mode should be adopted to keep the T4 at a high level under different GT load rates. Full article
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24 pages, 1268 KiB  
Article
Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey
by Seyed Mahdi Miraftabzadeh, Michela Longo, Federica Foiadelli, Marco Pasetti and Raul Igual
Energies 2021, 14(16), 4776; https://doi.org/10.3390/en14164776 - 06 Aug 2021
Cited by 46 | Viewed by 3438
Abstract
The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. [...] Read more.
The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models. Full article
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34 pages, 36443 KiB  
Article
A New Decentralized Control Strategy of Microgrids in the Internet of Energy Paradigm
by Bilal Naji Alhasnawi, Basil H. Jasim, Bishoy E. Sedhom, Eklas Hossain and Josep M. Guerrero
Energies 2021, 14(8), 2183; https://doi.org/10.3390/en14082183 - 14 Apr 2021
Cited by 44 | Viewed by 3047
Abstract
The Energy Internet paradigm is the evolution of the Internet of Things concept in the power system. Microgrids (MGs), as the essential element in an Energy Internet, are expected to be controlled in a corporative and flexible manner. This paper proposes a novel [...] Read more.
The Energy Internet paradigm is the evolution of the Internet of Things concept in the power system. Microgrids (MGs), as the essential element in an Energy Internet, are expected to be controlled in a corporative and flexible manner. This paper proposes a novel decentralized robust control strategy for multi-agent systems (MASs) governed MGs in future Energy Internet. The proposed controller is based on a consensus algorithm applied with the connected distributed generators (DGs) in the MGs in the energy internet paradigm. The proposed controller’s objectives are the frequency/voltage regulation and proportional reactive/active power-sharing for the hybrid DGs connected MGs. A proposed two-level communication system is implemented to explain the data exchange between the MG system and the cloud server. The local communication level utilizes the transmission control protocol (TCP)/ internet protocol (IP) and the message queuing telemetry transport (MQTT) is used as the protocol for the global communication level. The proposed control strategy has been verified using a hypothetical hybrid DGs connected MG such as photovoltaic or wind turbines in MATLAB Simulink environment. Several scenarios based on the system load types are implemented using residential buildings and small commercial outlets. The simulation results have verified the feasibility and effectiveness of the introduced strategy for the MGs’ various operating conditions. Full article
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14 pages, 4468 KiB  
Article
Regional Pole Placers of Power Systems under Random Failures/Repair Markov Jumps
by Farag Ali El-Sheikhi, Hisham M. Soliman, Razzaqul Ahshan and Eklas Hossain
Energies 2021, 14(7), 1989; https://doi.org/10.3390/en14071989 - 03 Apr 2021
Cited by 8 | Viewed by 1409
Abstract
This paper deals with a discrete-time stochastic control model design for random failure prone and maintenance in a single machine infinite bus (SMIB) system. This model includes the practical values of failure/repair rate of transmission lines and transformers. The probability matrix is, therefore, [...] Read more.
This paper deals with a discrete-time stochastic control model design for random failure prone and maintenance in a single machine infinite bus (SMIB) system. This model includes the practical values of failure/repair rate of transmission lines and transformers. The probability matrix is, therefore, calculated accordingly. The model considers two extreme modes of operations: the most reliable mode and the least reliable contingency case. This allows the control design which stochastically stabilizes the system under jump Markov disturbances. For adequate transient response, the proposed state feedback power system stabilizer (PSS) achieves a desired settling time and damping ratio by placing the closed-loop poles in a desired region. The control target should also be satisfied for load variations in either mode of operation. A sufficient condition is developed to achieve the control objectives via solving a set of linear matrix inequalities (LMI). Using simulation, the performance of the designed controller is tested for the system that prone to random failure/maintenance under various loading conditions. Simulation results reveal that the closed-loop poles reside within the desired region satisfying the required settling time and damping ratio under the aforementioned disturbances. The contributions of the paper are summarized as follows: (1) modeling of transition probability matrix under Markov Jumps using practical data, (2) designing a controller by compelling the closed poles into the desired region to achieve adequate dynamic performance under different load varying conditions. Full article
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25 pages, 3107 KiB  
Article
Modelling and Control of a Grid-Connected RES-Hydrogen Hybrid Microgrid
by Jonny Esteban Villa Londono, Andrea Mazza, Enrico Pons, Harm Lok and Ettore Bompard
Energies 2021, 14(6), 1540; https://doi.org/10.3390/en14061540 - 11 Mar 2021
Cited by 15 | Viewed by 3553
Abstract
This paper proposes a Hybrid Microgrid (HμG) model including distributed generation (DG) and a hydrogen-based storage system, controlled through a tailored control strategy. The HμG is composed of three DG units, two of them supplied by solar and wind [...] Read more.
This paper proposes a Hybrid Microgrid (HμG) model including distributed generation (DG) and a hydrogen-based storage system, controlled through a tailored control strategy. The HμG is composed of three DG units, two of them supplied by solar and wind sources, and the latter one based on the exploitation of theProton Exchange Membrane (PEM) technology. Furthermore, the system includes an alkaline electrolyser, which is used as a responsive load to balance the excess of Variable Renewable Energy Sources (VRES) production, and to produce the hydrogen that will be stored into the hydrogen tank and that will be used to supply the fuel cell in case of lack of generation. The main objectives of this work are to present a validated dynamic model for every component of the HμG and to provide a strategy to reduce as much as possible the power absorption from the grid by exploiting the VRES production. The alkaline electrolyser and PEM fuel cell models are validated through real measurements. The State of Charge (SoC) of the hydrogen tank is adjusted through an adaptive scheme. Furthermore, the designed supervisor power control allows reducing the power exchange and improving the system stability. Finally, a case, considering a summer load profile measured in an electrical substation of Politecnico di Torino, is presented. The results demonstrates the advantages of a hydrogen-based micro-grid, where the hydrogen is used as medium to store the energy produced by photovoltaic and wind systems, with the aim to improve the self-sufficiency of the system. Full article
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