Submit to Energies Review for Energies Propose a Special Issue

Journal Browser

Design and Validation of Smart Energy System Concepts and Methods

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: closed (10 January 2022) | Viewed by 12420

Share This Special Issue

Special Issue Editors

Dr. Thomas Strasser

E-Mail Website
Guest Editor

Electric Energy Systems, Center for Energy, AIT Austrian Institute of Technology, Giefinggasse 2, A-1210 Vienna, Austria
Interests: power utility automation; modelling and (real-time) simulation of smart grid systems; ICT for smart grids; validation and testing of smart grid systems; hardware-in-the-loop experiments
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Sebastian Rohjans

E-Mail Website
Guest Editor

Civil Engineering, Geoinformation and Health Technology, Jade University of Applied Sciences, 26122 Oldenburg, Germany
Interests: co-simulation; data modeling; distribution system automation; energy information systems; information and communication technology; interoperability; power systems simulation; smart grid
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Graeme Burt

E-Mail Website1 Website2
Guest Editor

Institute for Energy & Environment, University of Strathclyde, Glasgow, Scotland
Interests: distributed energy and smart grid protection and control; compact power systems for microgrid, aerospace and marine applications; experimental validation; systems testing and power-hardware-in-the-loop; DC distribution; hybrid power systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Energy efficiency and low-carbon technologies are key contributors to curtailing the emission of greenhouse gases that continue to cause global warming. The efforts to reduce greenhouse gas emissions also strongly affect electrical power systems. Renewable sources, storage systems and flexible loads provide new system controls, but power system operators and utilities have to deal with their fluctuating nature, limited storage capabilities and typically higher infrastructure complexity, with a growing number of heterogeneous components. In addition to the technological change of new components, the liberalization of energy markets and new regulatory rules brings contextual change that necessitates the restructuring of the design and operation of future energy systems. Sophisticated component design methods, intelligent information and communication architectures, automation and control concepts, new and advanced markets, as well as proper standards, are necessary, in order to manage the higher complexity of such intelligent power systems that form the smart grid.

Due to the considerably higher complexity of such cyber-physical energy systems, constituting the power system, automation, protection, information and communication technology (ICT), and system services, it is expected that the design and validation of smart grid configurations will play a major role in future technology and system developments. However, an integrated approach for the design and evaluation of smart grid configurations incorporating these diverse constituent parts remains evasive. Validation approaches available today focus mainly on component-oriented methods. In order to guarantee a sustainable, afforable and secure supply of electricity through the transition to a future smart grid with considerably higher complexity and innovation, new design, validation and testing methods appropriate for cyber-physical systems are required. Papers that present results related to the design and validation of smart grid systems are particularly welcome for this Special Issue.

Dr. Thomas Strasser
Prof. Dr. Sebastian Rohjans
Prof. Dr. Graeme Burt
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

design, development and implementation methods for smart grid technologies
modeling and simulation of smart grid systems
co-simulation based assessment methods
validation techniques for innovative smart grid solutions
real-time simulation and hardware-in-the-loop experiments

Published Papers (5 papers)

Download All Papers

Research

13 pages, 262 KiB

Open AccessArticle

Optimal Data Reduction of Training Data in Machine Learning-Based Modelling: A Multidimensional Bin Packing Approach

by Jelke Wibbeke, Payam Teimourzadeh Baboli and Sebastian Rohjans

Energies 2022, 15(9), 3092; https://0-doi-org.brum.beds.ac.uk/10.3390/en15093092 - 23 Apr 2022

Cited by 3 | Viewed by 2407

Abstract

In these days, when complex, IT-controlled systems have found their way into many areas, models and the data on which they are based are playing an increasingly important role. Due to the constantly growing possibilities of collecting data through sensor technology, extensive data sets are created that need to be mastered. In concrete terms, this means extracting the information required for a specific problem from the data in a high quality. For example, in the field of condition monitoring, this includes relevant system states. Especially in the application field of machine learning, the quality of the data is of significant importance. Here, different methods already exist to reduce the size of data sets without reducing the information value. In this paper, the multidimensional binned reduction (MdBR) method is presented as an approach that has a much lower complexity in comparison on the one hand and deals with regression, instead of classification as most other approaches do, on the other. The approach merges discretization approaches with non-parametric numerosity reduction via histograms. MdBR has linear complexity and can be facilitated to reduce large multivariate data sets to smaller subsets, which could be used for model training. The evaluation, based on a dataset from the photovoltaic sector with approximately 92 million samples, aims to train a multilayer perceptron (MLP) model to estimate the output power of the system. The results show that using the approach, the number of samples for training could be reduced by more than

99 %

, while also increasing the model’s performance. It works best with large data sets of low-dimensional data. Although periodic data often include the most redundant samples and thus provide the best reduction capabilities, the presented approach can only handle time-invariant data and not sequences of samples, as often done in time series. Full article

(This article belongs to the Special Issue Design and Validation of Smart Energy System Concepts and Methods)

► Show Figures

Figure 1

30 pages, 7370 KiB

Open AccessArticle

Implementation and Test of an IEC 61850-Based Automation Framework for the Automated Data Model Integration of DES (ADMID) into DSO SCADA

by Shuo Chen, Falko Ebe, Jeromie Morris, Heiko Lorenz, Christoph Kondzialka and Gerd Heilscher

Energies 2022, 15(4), 1552; https://0-doi-org.brum.beds.ac.uk/10.3390/en15041552 - 19 Feb 2022

Cited by 4 | Viewed by 2823

Abstract

As a result of the energy transition, an increasing number of Decentralized Energy Systems (DES) will be installed in the distribution grid in the future. Accordingly, new methods to systematically integrate the growing DES in distribution power systems must be developed utilizing the constantly evolving Information and Communication Technologies (ICT). This paper proposes the Automated Data Model Integration of DES (ADMID) approach for the integration of DES into the ICT environment of the Distribution System Operator (DSO). The proposed ADMID utilizes the data model structure defined by the standard-series IEC 61850 and has been implemented as a Python package. The presented two Use Cases focus on the Supervisory Control and Data Acquisition (SCADA) on the DSO operational level following a four-stage test procedure, while this approach has enormous potential for advanced DSO applications. The test results obtained during simulation or real-time communication to field devices indicate that the utilization of IEC 61850-compliant data models is eligible for the proposed automation approach, and the implemented framework can be a considerable solution for the system integration in future distribution grids with a high share of DES. As a proof-of-concept study, the proposed ADMID approach requires additional development with a focus on the harmonization with the Common Information Model (CIM), which could significantly improve its functional interoperability and help it reach a higher Technology Readiness Level (TRL). Full article

(This article belongs to the Special Issue Design and Validation of Smart Energy System Concepts and Methods)

► Show Figures

Figure 1

22 pages, 46259 KiB

Open AccessArticle

System Level Real-Time Simulation and Hardware-in-the-Loop Testing of MMCs

by Michele Difronzo, Md Multan Biswas, Matthew Milton, Herbert L. Ginn and Andrea Benigni

Energies 2021, 14(11), 3046; https://0-doi-org.brum.beds.ac.uk/10.3390/en14113046 - 24 May 2021

Cited by 3 | Viewed by 2103

Abstract

In this paper we present an approach for real-time simulation and Hardware-in-the-Loop (HIL) testing of Modular Multilevel Converters (MMCs) that rely on switching models while supporting system level analysis. Using the Latency Based Linear Multistep Compound (LB-LMC) approach, we achieved a 50 ns simulation time step for systems composed of several MMC converters and for converters of various complexity. To facilitate system level testing, we introduce the use of a serial communication-based (Aurora) interface for HIL testing of MMC converters and we analyzed the effect that communication latency has on the accuracy of the HIL test. The simulation and HIL results are validated against an MMC laboratory prototype. Full article

(This article belongs to the Special Issue Design and Validation of Smart Energy System Concepts and Methods)

► Show Figures

Figure 1

16 pages, 2643 KiB

Open AccessArticle

Adaptive Multicriteria Thresholding for Cooperative Spectrum Sensing in Cognitive Radio Ad Hoc Smart Grid Networks under Shadowing Effect

by Kanabadee Srisomboon, Yutthna Sroulsrun and Wilaiporn Lee

Energies 2021, 14(8), 2259; https://0-doi-org.brum.beds.ac.uk/10.3390/en14082259 - 17 Apr 2021

Cited by 4 | Viewed by 1295

Abstract

Cognitive radio is expected to be implemented in smart grids since it presents high reliability, high accuracy and low transmission time by utilizing licensed bands opportunistically. Shadowing environment affects the performance of channel availability detection of local spectrum sensing since it occurs occasionally. Therefore, the cooperative spectrum sensing is encouraged to be used for addressing shadowing issues. The principle cooperative spectrum sensing techniques suffer from unreliable local information from secondary users (SUs) who are encountered by the shadowing effect. Then, several alternative methods, adaptive majority rule and improved weight algorithm (IMA) is proposed by taking the SUs reliability into account. However, the unreliable SUs are still considered according to the algorithm. Therefore, in this paper, we propose an adaptive multi-criteria thresholding (AMT) to determine the channel availability according to the SUs reliability. The main contribution of AMT is three-fold. First, the new reliable weight calculation is proposed by utilizing analytic hierarchy process (AHP) under three major criteria. Second, AMT is flexible to the number of SUs since it adapts the decision weight on the optimal number of SUs according to the reliable SUs. Third, the shadowing issue is addressed by taking only reliable SUs into account. Full article

(This article belongs to the Special Issue Design and Validation of Smart Energy System Concepts and Methods)

► Show Figures

Figure 1

30 pages, 3079 KiB

Open AccessArticle

Generic EMT Model for Real-Time Simulation of Large Disturbances in 2 GW Offshore HVAC-HVDC Renewable Energy Hubs

by Saran Ganesh, Arcadio Perilla, Jose Rueda Torres, Peter Palensky, Aleksandra Lekić and Mart van der Meijden

Energies 2021, 14(3), 757; https://0-doi-org.brum.beds.ac.uk/10.3390/en14030757 - 01 Feb 2021

Cited by 3 | Viewed by 2507

Abstract

This paper proposes a Electro-Magnetic Transient (EMT) model of a 2 GW offshore network with the parallel operation of two Modular Multi-level Converter (MMC)—High Voltage Direct Current (HVDC) transmission links connecting four Offshore Wind Farms (OWFs) to two onshore systems, which represent a large scale power system. Additionally, to mitigate the challenges corresponding to voltage and frequency stability issues in large scale offshore networks, a Direct Voltage Control (DVC) strategy is implemented for the Type-4 Wind Generators (WGs), which represent the OWFs in this work. The electrical power system is developed in the power system simulation software RSCAD^TM, that is suitable for performing EMT based simulations. The EMT model of 2 GW offshore network with DVC in Type-4 WGs is successfully designed and it is well-coordinated between the control structures in MMCs and WGs. Full article

(This article belongs to the Special Issue Design and Validation of Smart Energy System Concepts and Methods)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Design and Validation of Smart Energy System Concepts and Methods

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (5 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI