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Smart Power Grid Low Carbon Energy Systems: Current Trends and New Perspectives

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (30 July 2022) | Viewed by 7026

Special Issue Editors

Dr. Zhengyu Lin

E-Mail Website
Guest Editor
School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: power electronics; motor drives; renewable energy; microgrid; low carbon energy systems
Dr. Hui Guo

E-Mail Website
Guest Editor
Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China
Interests: distributed energy; smart grid; multi-energy system
Dr. Fulong Li

E-Mail Website
Guest Editor
School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: control and design of DC/DC power converters; renewable energy; battery storage; DC microgrids; energy management system design

Special Issue Information

Dear Colleagues,

It is our pleasure to invite you to submit your paper for consideration in an upcoming Special Issue, entitled “Smart Power Grid Low Carbon Energy Systems: Current Trends and New Perspectives”. This Special Issue will focus on novel energy solutions in smart power grids to achieve a low carbon and sustainable energy system and reach ambitious carbon-neutrality targets.

Renewable energies, energy storage and electrical vehicles are among the key low carbon technologies in addressing the global climate change. However, with the increasing penetration of renewable energy sources and energy storage in the power grid, it is necessary to develop efficient and reliable energy system solutions to effectively integrate those low carbon technologies in the power grid. In a smart power grid, multi-way power flow and information flow are monitored or controlled by widespread and advanced equipment, including smart meters, smart transformers, distributed power electronics converters, etc. These trends enable novel low carbon energy system solutions, but have also raised concerns about the safety, stability, and economy of the smart power grid. Accordingly, the technologies of advanced measurement, stability analysis, protection, data-driven approaches, intelligent control, power flow optimization, power trading, and so on, have drawn great attention.

The purpose of this Special Issue is to invite authors from both industry and academia to discuss challenges, new trends, and novel solutions in the low carbon energy system of smart power grids.

Dr. Zhengyu Lin
Dr. Hui Guo
Dr. Fulong Li
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

  •  low carbon energy system
  •  energy storage system
  •  energy management
  •  smart grid
  •  microgrids
  •  power electronics
  •  energy router
  •  safety
  •  stability
  •  power quality
  •  modeling
  •  optimal control
  •  sustainable
  •  carbon trading
  •  power trading
  •  protection
  •  fault analysis

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Published Papers (4 papers)

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Research

18 pages, 3784 KiB  
Article
Robust Multi-Objective H2/H∞ Load Frequency Control of Multi-Area Interconnected Power Systems Using TS Fuzzy Modeling by Considering Delay and Uncertainty
by Naser Azim Mohseni and Navid Bayati
Energies 2022, 15(15), 5525; https://doi.org/10.3390/en15155525 - 29 Jul 2022
Cited by 13 | Viewed by 1707
Abstract
The main objective of this paper is to design a robust multi-objective H2/H∞ delayed feedback controller for load frequency control of a multi-area interconnected power system by taking into account all theoretical and practical constraints. To achieve more precise [...] Read more.
The main objective of this paper is to design a robust multi-objective H2/H∞ delayed feedback controller for load frequency control of a multi-area interconnected power system by taking into account all theoretical and practical constraints. To achieve more precise modelling and analysis, the limitation of valve position, governor, and transmission delay are considered to guarantee of LFC system’s stability in practical applications. The nonlinear delayed system is approximated by the Takagi–Sugeno fuzzy model. Then, a parallel distributed compensation scheme is utilized for designing the control system of the overall system. The proposed multi-objective and robust H2/H∞ controller simultaneously minimizes the H2 and H∞ control performance indexes. Finally, simulation results verify the robustness and effectiveness of the proposed scheme in dealing with the impact of load disturbances, model uncertainties, transmission time delays, and nonlinearities in the model. Full article
(This article belongs to the Special Issue Smart Power Grid Low Carbon Energy Systems: Current Trends and New Perspectives)
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18 pages, 2147 KiB  
Article
Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing
by Hui Guo, Dandan Gong, Lijun Zhang, Wenke Mo, Feng Ding and Fei Wang
Energies 2022, 15(15), 5382; https://doi.org/10.3390/en15155382 - 25 Jul 2022
Cited by 1 | Viewed by 1270
Abstract
The growing popularity of renewable energy and hydrogen-powered vehicles (HVs) will facilitate the coordinated optimization of energy and transportation systems for economic and environmental benefits. However, little research attention has been paid to dynamic hydrogen pricing and its impact on the optimal performance [...] Read more.
The growing popularity of renewable energy and hydrogen-powered vehicles (HVs) will facilitate the coordinated optimization of energy and transportation systems for economic and environmental benefits. However, little research attention has been paid to dynamic hydrogen pricing and its impact on the optimal performance of energy and transportation systems. To reduce the dependency on centralized controllers and protect information privacy, a time-decoupling layered optimization strategy is put forward to realize the low-carbon and economic operation of energy and transportation systems under dynamic hydrogen pricing. First, a dynamic hydrogen pricing mechanism was formulated on the basis of the share of renewable power in the energy supply and introduced into the optimization of distributed energy stations (DESs), which will promote hydrogen production using renewable power and minimize the DES construction and operation cost. On the basis of the dynamic hydrogen price optimized by DESs and the traffic conditions on roads, the raised user-centric routing optimization method can select a minimum cost route for HVs to purchase fuels from a DES with low-cost and/or low-carbon hydrogen. Finally, the effectiveness of the proposed optimization strategy was verified by simulations. Full article
(This article belongs to the Special Issue Smart Power Grid Low Carbon Energy Systems: Current Trends and New Perspectives)
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19 pages, 9028 KiB  
Article
Modeling and Analysis of the Harmonic Interaction between Grid-Connected Inverter Clusters and the Utility Grid
by Lintao Ren, Hui Guo, Zhenlan Dou, Fei Wang and Lijun Zhang
Energies 2022, 15(10), 3490; https://doi.org/10.3390/en15103490 - 10 May 2022
Cited by 5 | Viewed by 1837
Abstract
The virtual synchronous generator (VSG) is a promising technology for future utility grids, since it can mimic the output characteristics of a synchronous generator, which provides the necessary inertia to a utility grid. However, the large-scale application of VSGs is limited due to [...] Read more.
The virtual synchronous generator (VSG) is a promising technology for future utility grids, since it can mimic the output characteristics of a synchronous generator, which provides the necessary inertia to a utility grid. However, the large-scale application of VSGs is limited due to the harmonic interaction between VSGs and the utility grid. Therefore, in order to investigate the stability issue as well as improve the practical application for large-scale power stations, the harmonic interaction mechanism between the VSG cluster and the utility grid is addressed. Firstly, the output impedance model of a single VSG is established, and it is found that the resonance frequency is related to parameters including the output filter, controller, and grid impedance. On this basis, the capacitor current control for a grid-connected inverter based on a VSG is proposed to enhance the resonance suppression. Furthermore, the output impedance of the VSG cluster is established, which reveals the harmonic interaction characteristics between the VSG cluster and the utility grid. In addition, in order to suppress the resonance and improve the stability, an inner-loop control strategy of VSG is introduced. Finally, the simulation and experimental results verified the correctness of the established modeling and analysis of the harmonic interaction between the clustered VSGs and the utility grid. The results show that the proposed impedance model is correct and can predict the resonant point accuracy (which is around 2.3 kHz in the simulation and experimental cases). The total harmonic distortion (THD) can be reduced to 3.2% which meets the requirements of IEEE standard 519. Full article
(This article belongs to the Special Issue Smart Power Grid Low Carbon Energy Systems: Current Trends and New Perspectives)
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17 pages, 4068 KiB  
Article
Active Exploration by Chance-Constrained Optimization for Voltage Regulation with Reinforcement Learning
by Zhenhuan Ding, Xiaoge Huang and Zhao Liu
Energies 2022, 15(2), 614; https://doi.org/10.3390/en15020614 - 16 Jan 2022
Cited by 2 | Viewed by 1582
Abstract
Voltage regulation in distribution networks encounters a challenge of handling uncertainties caused by the high penetration of photovoltaics (PV). This research proposes an active exploration (AE) method based on reinforcement learning (RL) to respond to the uncertainties by regulating the voltage of a [...] Read more.
Voltage regulation in distribution networks encounters a challenge of handling uncertainties caused by the high penetration of photovoltaics (PV). This research proposes an active exploration (AE) method based on reinforcement learning (RL) to respond to the uncertainties by regulating the voltage of a distribution network with battery energy storage systems (BESS). The proposed method integrates engineering knowledge to accelerate the training process of RL. The engineering knowledge is the chance-constrained optimization. We formulate the problem in a chance-constrained optimization with a linear load flow approximation. The optimization results are used to guide the action selection of the exploration for improving training efficiency and reducing the conserveness characteristic. The comparison of methods focuses on how BESSs are used, training efficiency, and robustness under varying uncertainties and BESS sizes. We implement the proposed algorithm, a chance-constrained optimization, and a traditional Q-learning in the IEEE 13 Node Test Feeder. Our evaluation shows that the proposed AE method has a better response to the training efficiency compared to traditional Q-learning. Meanwhile, the proposed method has advantages in BESS usage in conserveness compared to the chance-constrained optimization. Full article
(This article belongs to the Special Issue Smart Power Grid Low Carbon Energy Systems: Current Trends and New Perspectives)
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