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Advances in Multi-Energy Systems and Smart Grids

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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 (31 December 2023) | Viewed by 13902

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Special Issue Editors

Prof. Dr. Hongjie Jia

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Guest Editor

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: integrated energy system; power system stability assessment; smart grid; renewable energy integration

Prof. Dr. Tao Jiang

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Guest Editor

Department of Electrical Engineering, Northeast Electric Power University, Jilin, China
Interests: power system stability and control; renewable energy integration; integrated energy systems

Dr. Yukun Hu

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Guest Editor

Department of Civil, Environment and Geomatic Engineering, University College London, London WC1E 6BT, UK
Interests: industrial internet of things; hydrogen infrastructure deployment; future energy scenarios in the built environment; multi-energy complementary systems toward demand side resilience; CCUS
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Dr. Gen Li

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Guest Editor

School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
Interests: protection and control of HVDC and MVDC technologies; power electronics; renewable energy integration; stability and control of hybrid AC/DC grids; reliability modeling and evaluation of power electronics systems for different applications
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Dr. Xiandong Xu

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Guest Editor

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Interests: modelling and flexible control of integrated energy system; design and optimal operation of offshore multi-energy systems
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Special Issue Information

Dear Colleagues,

To mitigate climate change, traditional power and energy systems whose sectors are operated separately are transforming to increase renewable energy penetration while ensuring that a resilient energy supply is maintained. Electricity, heat, cooling, hydrogen and fuel systems, along with other sectors such as transport, buildings and industries, are coordinated at various levels (community, campus, urban, etc.) to improve the technical, economic and environmental performance of energy supply systems. This has contributed to the advances in planning technologies, modelling tools, and the control and management of current power and energy systems. Additionally, the deployment of renewable energy is moving from onshore to offshore resources due to the higher energy yields and fewer space limitations, leading to the development of offshore multi-energy systems. New approaches and tools are needed to properly capture the costs and benefits of offshore instalment and operating conditions.

This Special Issue aims to present and disseminate a state-of-the-art collection of the advances related to multi-energy systems and smart grids in design and planning, flexible management and control, energy trading, modelling and simulation, novel technologies, applications in community/campus/urban/offshore energy systems, interactions with building/industry/transportation systems, as well as the development experience of tools and projects.

Topics of interest for publication include, but are not limited to:

Applications of novel technologies, such as distributed intelligence, collective intelligence, swarm intelligence, multi-agent systems, network theory, etc., in multi-energy systems and smart grids
Climate change resilience of multi-energy systems and smart grids
Low-carbon design and planning of local energy systems
Flexible management and control of multi-energy flows
Integrating the utilization of offshore energy systems such as wind power, solar power, power, gas, hydrogen, wave energy, geothermal energy, etc.
Modelling and optimization technologies to support the flexibility deployment of buildings, industries, communities, etc.

Prof. Dr. Hongjie Jia
Prof. Dr. Tao Jiang
Dr. Yukun Hu
Dr. Gen Li
Dr. Xiandong Xu
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.

Published Papers (10 papers)

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Research

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19 pages, 3562 KiB

Open AccessFeature PaperArticle

Surrogate-Assisted Multi-Objective Optimisation of Transcritical Carbon Dioxide Scroll Expander Flank Clearance Based on Computational Fluid Dynamics

by Yuheng Du, Shuang Li, Michael Pekris, Wei Li and Guohong Tian

Energies 2023, 16(14), 5580; https://doi.org/10.3390/en16145580 - 24 Jul 2023

Viewed by 824

Abstract

Transcritical carbon dioxide waste heat recovery systems and the construction of scroll expanders have recently been hot topics. The flank clearance, located between the orbiting and fixed scroll, has a vital impact on the scroll expander performance. This paper estimates the effect of the flank clearance on the expander’s thermodynamic performance (first-law efficiency) based on computational fluid dynamics (CFD) simulations. The manufacturing cost of different flank clearances is also considered to enhance the feasibility of the machinery design. The computational cost for different flank clearance cases is significantly reduced with a surrogate-assisted multi-objective optimisation algorithm (SAMOA), which also supports modelling the trade-off relationship between manufacturing cost and machinery efficiency. The results indicated that an increasing flank clearance negatively affects the first-law thermal efficiency. The efficiency decreased from 87.41% to 44.83% moving from 20 to 200 μm flank clearances. The SAMOA successfully reduced the computational cost of the dynamic mesh CFD model from 90 h to 15 s with 0.6% discrepancy. The final Pareto solutions presented a clear trade-off relationship between the first-law efficiency and manufacturing cost and promised a diversity of optimum solutions. The “knee points” for the relationship were 25, 55, and 127 μm, which provided flexible clearance choices based on the importance of either machinery efficiency or manufacturing cost. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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16 pages, 12120 KiB

Open AccessArticle

A Frequency Support Approach for Hybrid Energy Systems Considering Energy Storage

by Dahu Li, Hongyu Zhou, Yuan Chen, Yue Zhou, Yuze Rao and Wei Yao

Energies 2023, 16(10), 4252; https://doi.org/10.3390/en16104252 - 22 May 2023

Viewed by 1013

Abstract

In hybrid energy systems, the intermittent and fluctuating nature of new energy sources poses major challenges for the regulation and control of power systems. To mitigate these challenges, energy storage devices have gained attention for their ability to rapidly charge and discharge. Collaborating with wind power (WP), energy storage (ES) can participate in the frequency control of regional power grids. This approach has garnered extensive interest from scholars worldwide. This paper proposes a two-region load frequency control model that accounts for thermal power, hydropower, ES, and WP. To address complex, nonlinear optimization problems, the dingo optimization algorithm (DOA) is employed to quickly obtain optimal power dispatching commands under different power disturbances. The DOA algorithm’s effectiveness is verified through the simulation of the two-region model. Furthermore, to further validate the proposed method’s optimization effect, the DOA algorithm’s optimization results are compared with those of the genetic algorithm (GA) and proportion method (PROP). Simulation results show that the optimization effect of DOA is more significant than the other methods. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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27 pages, 11624 KiB

Open AccessArticle

Distributed Energy Systems: Constraints and Opportunities in Urban Environments

by Paola Marrone, Federico Fiume, Antonino Laudani, Ilaria Montella, Martina Palermo and Francesco Riganti Fulginei

Energies 2023, 16(6), 2718; https://doi.org/10.3390/en16062718 - 14 Mar 2023

Cited by 2 | Viewed by 1459

Abstract

Cities need to make themselves energy self-sufficient by exploiting renewable sources and, above all, to evaluate the potential and constraints that each city can express by virtue of its own characteristics. This study focused on how the realisation of a renewable energy community could be approached in urbanised contexts. The methodology involved the selection of three case studies in Rome analysing the feasibility, programming and design scale, and the implications of planning RECs. Through simulation at three levels of detail, this study identifies elements to assess the feasibility of RECs and to elaborate scenarios to support their planning and dimensioning. The practical importance is to identify a possible methodological path and relevant factors which public or private stakeholders can consider at different levels in setting up RECs in an urban context. The research conclusions of these simulations point out that the specificities of a context affect many factors, among which an important role is played by the facilities and spaces for public use, as they are synergetic to a shared use of energy between residential and non-residential functions, but above all, because they are also available to accommodate services for the energy community. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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17 pages, 5416 KiB

Open AccessArticle

RAC-GAN-Based Scenario Generation for Newly Built Wind Farm

by Jian Tang, Jianfei Liu, Jinghan Wu, Guofeng Jin, Heran Kang, Zhao Zhang and Nantian Huang

Energies 2023, 16(5), 2447; https://doi.org/10.3390/en16052447 - 03 Mar 2023

Cited by 3 | Viewed by 1286

Abstract

Due to the lack of historical output data of new wind farms, there are difficulties in the scheduling and planning of power grid and wind power output scenario generation. The randomness and uncertainty of meteorological factors lead to the results of traditional scenario generation methods not having the ability to accurately reflect their uncertainty. This article proposes a RAC-GAN-based scenario generation method for a new wind farm output. First, the Pearson coefficient is adopted in this method to screen the meteorological factors and obtain the ones that have larger impact on wind power output; Second, based on the obtained meteorological factors, the Grey Relation Analysis (GRA) is used to analyze the meteorological correlation between multiple wind farms with sufficient output data and new wind farms (target power stations), so that the wind farm with high meteorological correlation is selected as the source power station. Then, the K-means method is adopted to cluster the meteorological data of the source power station, thus generating the target power station scenario in which the cluster information serves as the label of the robust auxiliary classifier generative adversarial network (RAC-GAN) model and the output data of the source power station is considered as the basis. Finally, the actual wind farm output and meteorological data of a region in northeast China are employed for arithmetic analysis to verify the effectiveness of the proposed method. It is proved that the proposed method can effectively reflect the characteristics of wind power output and solve the problem of insufficient historical data of new wind farm output. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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15 pages, 2537 KiB

Open AccessArticle

Dynamic Interactions between Local Energy Systems Coupled by Power and Gas Distribution Networks

by Yajing Hu, Jing Liu and Xiandong Xu

Energies 2022, 15(22), 8420; https://doi.org/10.3390/en15228420 - 10 Nov 2022

Cited by 3 | Viewed by 904

Abstract

Supplied with electricity and natural gas, local energy systems (LESs) with gas-fired generations increase the operational flexibility of urban energy supply. However, the increasing usage of these LESs may lead to adverse impacts on the urban energy system supply via power and/or gas distribution networks. Dynamic interactions between the LESs, electricity, and gas networks subject to different disturbances need to be investigated due to the complexity of the problem. To address this issue, this paper first presents the topology and operating mode of the LESs as well as the relationship with power and gas networks. Second, an extended microturbine model is developed to reflect the nonlinear dynamic propagation of disturbances between the two networks. A general model of the interconnected LESs is developed to analyze the mutual impacts between gas and electricity networks under different modes. Finally, an iterative method is proposed to simulate the mechanism of disturbance propagation between the electricity network, gas network, and LESs, incorporating the impacts of loads and renewables. Case studies reveal that simultaneous regulation of multiple gas-fired generators would reduce the minimum pressure to 50% of the steady-state value. The resulted pressure drop is even lower than the case with higher total gas demand but only one gas-fired generator regulated. Moreover, it is shown that state fluctuations of the gas system last 20 times longer than the electricity system within the LESs. The electrical link between LESs, such as soft opening point with shorter response time, could smooth the fluctuations. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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14 pages, 4021 KiB

Open AccessArticle

Research on Flexible Virtual Inertia Control Method Based on the Small Signal Model of DC Microgrid

by Shengyang Lu, Tongwei Yu, Huiwen Liu, Wuyang Zhang, Yuqiu Sui, Junyou Yang, Li Zhang, Jiaxu Zhou and Haixin Wang

Energies 2022, 15(22), 8360; https://doi.org/10.3390/en15228360 - 09 Nov 2022

Cited by 4 | Viewed by 1046

Abstract

Renewable energy is usually connected to the DC micro-grid by a large number of power electronic devices, which have the advantages of a fast system response, but the disadvantage to reduce the inertia of the system, which makes the stability of the system worse. It is necessary to increase the inertia of DC micro-grid so that it can recover and stabilize well when it receives a disturbance. In this paper, a small-signal model of DC micro-grid with constant power load (CPL) is established, and a flexible virtual inertial (FVI) control method based on DC bus voltage real-time variation is proposed, by controlling the DC/DC converter of the energy storage system, the problem of system oscillation caused by introducing voltage differential link to the system is solved. Compared with the droop control method, the FVI control method can increase the inertia of DC micro-grid system, reduce the influence of small disturbances, and improve the stability of the system. Finally, the validity of the FVI control method based on small signal model is verified in dSPACE. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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14 pages, 7948 KiB

Open AccessEditor’s ChoiceArticle

Tensor-Based Harmonic Analysis of Distribution Systems

by Muhammad Ramzan, Ali Othman and Neville R. Watson

Energies 2022, 15(20), 7521; https://doi.org/10.3390/en15207521 - 12 Oct 2022

Cited by 3 | Viewed by 1273

Abstract

Over the past few decades, there have been rapid advances in solid-state technology as well as a reduction in cost. This, coupled with the functionality and efficiency improvements they afford, has resulted in a massive increase in the use of electronic devices. Where traditionally, there were a few well-known nonlinear loads that needed to be considered, now there are numerous low-power devices. Although individually insignificant, collectively, they are very significant. This paper presents a tensor-based harmonic analysis approach that is capable of capturing important interactions while being computationally efficient enough to model a large distribution system. Numerical experiments are used to highlight the advantages of the tensor framework. Numerous papers have investigated the tensor parametrisation or its mathematical equivalent—harmonically coupled admittance matrices (also known as frequency coupling matrices). However, this paper, for the first time, demonstrates how these models can be applied to perform harmonic modelling of a complete low voltage (LV) distribution system. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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17 pages, 5001 KiB

Open AccessFeature PaperArticle

Small-Signal Stability Research of Grid-Connected Virtual Synchronous Generators

by Shengyang Lu, Yu Zhu, Lihu Dong, Guangyu Na, Yan Hao, Guanfeng Zhang, Wuyang Zhang, Shanshan Cheng, Junyou Yang and Yuqiu Sui

Energies 2022, 15(19), 7158; https://doi.org/10.3390/en15197158 - 28 Sep 2022

Cited by 7 | Viewed by 1554

Abstract

The virtual synchronous generator (VSG) technique is used to simulate the external characteristics of a synchronous generator (SG) to provide certain damping and inertia to power systems. However, it may easily cause low-frequency oscillation of the power system. We studied the small-signal stability of a grid-connected virtual synchronous generator. Firstly, the small-signal models of single-VSG and multi-VSG grid-connected systems were established. Subsequently, the system eigenvalues were obtained by solving the state matrix, and the system oscillation modes were analyzed. The eigenvalue analysis method was used to analyze the impacts of parameter changes, such as virtual moment of inertia, virtual damping coefficient, line resistance, and line inductance, on system stability. Finally, our conclusions were verified by numerous simulation models. Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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Review

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24 pages, 1487 KiB

Open AccessReview

A Review on a Data-Driven Microgrid Management System Integrating an Active Distribution Network: Challenges, Issues, and New Trends

by Lilia Tightiz and Joon Yoo

Energies 2022, 15(22), 8739; https://doi.org/10.3390/en15228739 - 21 Nov 2022

Cited by 9 | Viewed by 1996

Abstract

The advent of renewable energy sources (RESs) in the power industry has revolutionized the management of these systems due to the necessity of controlling their stochastic nature. Deploying RESs in the microgrid (MG) as a subset of the utility grid is a beneficial way to achieve their countless merits in addition to controlling their random nature. Since a MG contains elements with different characteristics, its management requires multiple applications, such as demand response (DR), outage management, energy management, etc. The MG management can be optimized using machine learning (ML) techniques applied to the applications. This objective first calls for the microgrid management system (MGMS)’s required application recognition and then the optimization of interactions among the applications. Hence, this paper highlights significant research on applying ML techniques in the MGMS according to optimization function requirements. The relevant studies have been classified based on their objectives, methods, and implementation tools to find the best optimization and accurate methodologies. We mainly focus on the deep reinforcement learning (DRL) methods of ML since they satisfy the high-dimensional characteristics of MGs. Therefore, we investigated challenges and new trends in the utilization of DRL in a MGMS, especially as part of the active power distribution network (ADN). Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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19 pages, 2161 KiB

Open AccessReview

Integration Opportunities of Power-to-Gas and Internet-of-Things Technical Advancements: A Systematic Literature Review

by József Magyari, Krisztina Hegedüs and Botond Sinóros-Szabó

Energies 2022, 15(19), 6999; https://doi.org/10.3390/en15196999 - 23 Sep 2022

Cited by 4 | Viewed by 1487

Abstract

As renewable electricity integration generates grid-balancing challenges for network operators, new ways of grid resilience receive significant attention from the energy research community. Power-to-gas (P2G) applications could produce and use green hydrogen. Thus, they enable the integration of more renewable energy into the energy system. Meanwhile, Internet-of-things (IoT) solutions could optimize renewable energy applications in decentralized systems. Despite the strategic importance of both technologies in renewable-rich grid developments, opportunities for P2G advancements based on IoT and related solutions have not come to the forefront of renewable energy research. To fill in this research gap, this study presents a hybrid (thematic and critical) systematic literature review to explore how strategic co-specialization opportunities appear in recent publications. Findings suggest that P2G and IoT could be fundamentally linked within the proposed frameworks of multi-energy systems and energy internet, but further empirical research is needed regarding their operative and strategic integration (e.g., cost reduction, risk management and policy incentives). Full article

(This article belongs to the Special Issue Advances in Multi-Energy Systems and Smart Grids)

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