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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 (9 August 2023) | Viewed by 13519

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Special Issue Editor

Dr. Vaidyanathan Krishnamurthy

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Guest Editor

Center for Electromechanics, The University of Texas at Austin, Austin, TX, USA
Interests: renewable energy; storage; power system reliability; data science; resilience

Special Issue Information

Dear Colleagues,

The Guest Editor of this Special Issue of Energies is inviting submissions on the subject of “Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence”. Modern power grids have an increasing degree of complexity via intelligence, logistics, and external supply issues, as well as a complex operating environment. They also form the backbone of many other critical infrastructures. This Special Issue seeks to collate, connect, and address uncertainty, resilience, and interdependence within and between infrastructures, with a focus on power grids. Topics of interest include, but are not limited to:

● Inverter-based resources and grid-forming technology;
● Renewables penetration, volatility, and system stability;
● Supply chain and inventory management;
● Extreme events modeling and electromagnetic modeling;
● Structural health estimation and monitoring;
● Multiphysics analysis;
● Multi time scale modeling;
● Supply chain issues for critical components;
● Blockchain technologies for smart grid economics;
● Black start modeling and practices;
● Energy storage and degradation modeling;
● Physics-based data science and machine learning methods.

Dr. Vaidyanathan Krishnamurthy
Guest Editor

Manuscript Submission Information

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Keywords

resilience
uncertainty propagation
interdependence
cascading outages
smart grid complexity

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Published Papers (6 papers)

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Research

13 pages, 1012 KiB

Open AccessArticle

Testing Rogowski Coils with Merging Units for Smart Grids

by Mayada Daboul, Jaroslava Orságová, Viktor Jurák and Matěj Vrtal

Energies 2023, 16(21), 7323; https://doi.org/10.3390/en16217323 - 28 Oct 2023

Cited by 1 | Viewed by 1318

Abstract

As smart grids incorporate renewable energy sources and advanced power electronics, ensuring accurate measurement systems becomes paramount due to the increased complexity and potential sources of disturbances. This article focuses on the laboratory calibration of Rogowski coils (RCs) and merging units (MUs), which are fundamental for measuring, controlling, and monitoring digital power systems. A comprehensive digital calibration system is introduced, utilizing precise, commercially available components such as a fluxgate current transducer and a National Instrument. The system assesses magnitude and phase displacement errors under various operating conditions, including abnormal scenarios. Additionally, the impact of uncertainty sources on the measurement chain analysis is discussed, with test results conforming to established standards. This research contributes to enhancing the accuracy and reliability of measurement systems in the context of evolving smart grids. Full article

(This article belongs to the Special Issue Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence)

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17 pages, 6903 KiB

Open AccessArticle

Efficient Demand Side Management Using a Novel Decentralized Building Automation Algorithm

by Christodoulos Spagkakas, Dimitrios Stimoniaris and Dimitrios Tsiamitros

Energies 2023, 16(19), 6852; https://doi.org/10.3390/en16196852 - 27 Sep 2023

Cited by 2 | Viewed by 1438

Abstract

Given its adaptable and efficient energy consuming devices during peak hours, the residential building sector is urged to take part in demand response (DR) initiatives with the use of a building energy management system (BMS). The residents of buildings with BMS enjoy secure, pleasant, and fully managed lifestyles. Although the BMS helps the building consume less energy and encourages occupant engagement in energy-saving initiatives, unwelcome interruptions and harsh instructions from the system are inconvenient for the inhabitants, which further discourages their participation in DR initiatives. Building automation control is a crucial factor for improving buildings’ energy efficiency and management, as well as improving the electricity grid’s reliability indices. Smart houses that use the right sizing procedure and energy-management techniques can help lower the demand on the entire grid and potentially sell clean energy to the utility. Recently, smart houses have been presented as an alternative to traditional power-system issues including thermal plant emissions and the risk of blackouts brought on by malfunctioning bulk plants or transmission lines. This paper describes the necessary technology requirements and presents the methodology and the decentralized building automation novel algorithm for efficient demand side management in a building management system. Human comfort aspects including thermal comfort and visual comfort were taken into consideration when selecting heating and lighting controls. The suggested BMS relies primarily on a load-shifting technique, which moves controllable loads to low-cost periods to avoid high loading during peak hours. The model aims to minimize the individual household electricity consumption cost while considering customers’ comfort and lifestyle. All these are applied in an experimental university microgrid, and the results are presented in terms of energy saving in kWh, money in €, and working hours. The results demonstrated that the proposed approach might successfully lower energy use during the DR period and enhance occupant comfort. Full article

(This article belongs to the Special Issue Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence)

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21 pages, 3975 KiB

Open AccessArticle

Power Distribution System Outage Management Using Improved Resilience Metrics for Smart Grid Applications

by Arif Fikri Malek, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Jasrul Jamani Jamian, Li Wang and Munir Azam Muhammad

Energies 2023, 16(9), 3953; https://doi.org/10.3390/en16093953 - 8 May 2023

Cited by 10 | Viewed by 2293

Abstract

Smart grid systems play a significant role in improving the resilience of distribution systems (DSs). In this paper, two strategies are proposed for implementation of a smart grid application: (a) a network reconfiguration and (b) a network reconfiguration with mobile emergency generator (MEGs) deployment. An improved set of resilience metrics to quantify and enhance the resiliency of distribution systems (DSs) is developed for the proposed optimization. The metrics aim to determine a suitable strategy and the optimal number and capacity of MEGs to restore the disconnected loads through the development of several microgrids. These metrics are then aggregated with the proposed strategy to develop an automated solution provider. The objective is to maximize system resilience considering the priority loads. The proposed resilience metrics are tested on the IEEE 33-Bus radial DSs. The case studies conducted proved the performance of the proposed power outage management strategy and resilience metrics in maximizing system resiliency for smart grids. Full article

(This article belongs to the Special Issue Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence)

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24 pages, 2350 KiB

Open AccessArticle

Class Thresholds Pre-Definition by Clustering Techniques for Applications of ELECTRE TRI Method

by Flavio Trojan, Pablo Isaias Rojas Fernandez, Marcio Guerreiro, Lucas Biuk, Mohamed A. Mohamed, Pierluigi Siano, Roberto F. Dias Filho, Manoel H. N. Marinho and Hugo Valadares Siqueira

Energies 2023, 16(4), 1936; https://doi.org/10.3390/en16041936 - 15 Feb 2023

Cited by 1 | Viewed by 1814

Abstract

The sorting problem in the Multi-criteria Decision Analysis (MCDA) has been used to address issues whose solutions involve the allocation of alternatives in classes. Traditional multi-criteria methods are commonly used for this task, such as ELECTRE TRI, AHP-Sort, UTADIS, PROMETHEE, GAYA, etc. While using these approaches to perform the sorting procedure, the decision-makers define profiles (thresholds) for classes to compare the alternatives within these profiles. However, most such applications are based on subjective tasks, i.e., decision-makers’ expertise, which sometimes might be imprecise. To fill that gap, in this paper, a comparative analysis using the multi-criteria method ELECTRE TRI and clustering algorithms is performed to obtain an auxiliary procedure to define initial thresholds for the ELECTRE TRI method. In this proposed methodology, K-Means, K-Medoids, Fuzzy C-Means algorithms, and Bio-Inspired metaheuristics such as PSO, Differential Evolution, and Genetic algorithm for clustering are tested considering a dataset from a fundamental problem of sorting in Water Distribution Networks. The computational performances indicate that Fuzzy C-Means was more suitable for achieving the desired response. The practical contributions show a relevant procedure to provide an initial view of boundaries in multi-criteria sorting methods based on the datasets from specific applications. Theoretically, it is a new development to pre-define the initial limits of classes for the sorting problem in multi-criteria approach. Full article

(This article belongs to the Special Issue Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence)

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20 pages, 5971 KiB

Open AccessArticle

Operational Data Analysis of a Battery Energy Storage System to Support Wind Energy Generation

by Luana Pontes, Tatiane Costa, Amanda Souza, Nicolau Dantas, Andrea Vasconcelos, Guilherme Rissi, Roberto Dias, Mohamed A. Mohamed, Pierluigi Siano and Manoel Marinho

Energies 2023, 16(3), 1468; https://doi.org/10.3390/en16031468 - 2 Feb 2023

Cited by 15 | Viewed by 3628

Abstract

The insertion of renewable sources to diversify the energy matrix is one of the alternatives for the energy transition. In this sense, Brazil is one of the largest producers of renewable energy in the world, mainly in wind generation. However, the impact of integrating intermittent sources into the system depends on their penetration level, causing problems in the electrical network. To evaluate this scenario, the present article aims to investigate the power quality problems generated by wind turbines in connection with the electrical system and how battery energy storage systems (BESS) solve or mitigate these disturbances in the network. Knowing the impacts of high generation power variability, the focus of the work is the application of power smoothing. However, results are presented for five applications (factor correction, voltage control, power factor smoothing, frequency control and time shift) that can be carried out at the studied wind farm. This article presents a real BESS, which has a capacity of 1 MW/1.29 MWh, connected in parallel to a group of wind turbines that provides a power of approximately 50.4 MW located in Brazil. In addition to presenting the system simulation in HOMER Pro software, this study validates the effectiveness of this BESS by presenting real operation data for each application. Full article

(This article belongs to the Special Issue Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence)

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17 pages, 3981 KiB

Open AccessArticle

Resilience-Oriented Framework for Microgrid Planning in Distribution Systems

by Eun-Tae Son, In-Su Bae, Sung-Yul Kim and Dong-Min Kim

Energies 2022, 15(6), 2145; https://doi.org/10.3390/en15062145 - 15 Mar 2022

Cited by 6 | Viewed by 2097

Abstract

Recently, it has been suggested that microgrids (MGs) can improve the resilience of distribution systems. However, predictions about future faults are uncertain. This makes calculating the exact value of the benefits of system resilience enhancement close to impossible at the time of MG planning. Therefore, this paper proposes a framework for MG planning, which focuses on resilience estimation. To consider the uncertainties of future failure events, the proposed method for estimating the resilience utilized the Monte Carlo simulation. In addition, an optimal scenario was estimated using a cost–benefit analysis and constraints on the expected value of resilience enhancement. In the case study, an actual MG installation at D-university was evaluated to obtain the optimal MG planning scenario. The results show that the capacity and installation locations of the distributed generators (DGs) impact the resilience enhancement. The proposed method can effectively derive the optimal MG planning scenario by evaluating the possibility of future operations based on the segmentation of both the system configuration and type of DG to improve the resilience of distribution systems. Full article

(This article belongs to the Special Issue Advances in Smart Grid Power Systems: Uncertainty, Resilience, and Interdependence)

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