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Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (20 December 2021) | Viewed by 85626

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Prof. Dr. Pierluigi Siano

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Department of Management and Innovation Systems, University of Salerno, 84084 Salerno, Italy
Interests: smart grids; energy management; power systems; demand response
Special Issues, Collections and Topics in MDPI journals

Dr. Hassan Haes Alhelou

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Guest Editor

School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland
Interests: smart grids; power system control; power system dynamics and stability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We would like to invite submissions to a Special Issue of Applied Sciences on the subject of smart grids and microgrids entitled “Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security.”

Due to environment concerns, energy security risks, and fossil fuel problems, many countries around the world decided to increase the penetration level of renewable energy resources (RERs) in their energy networks. Beside this, many countries are moving toward implementation of a smart grid concept, including microgrid and deregulation in their power systems to achieve reliable and secure operation of their power systems with high penetration level of renewable energy resources. In future smart grids, keeping the operation in stable modes will require new techniques and technologies for better control and security assessment in such systems. Likewise, stability and security, which are the main issues in smart grids, should be well studied and analyzed. Moreover, new protection schemes are in demand in order to face any unexpected operation problems and contingencies in the smart grid environment.

In order to cope with ever-increasing operation and control complexity and security in modern and future smart grids, new architectures, concepts, algorithms, and procedures are essential. This Special Issue aims to encourage researchers to address the technical issues and research gaps in smart grid and microgrid systems.

The topics of interest of this Special Issue include but are not limited to:

Smart grids and microgrids
The design, modeling, and management of smart grids and microgrids
Smart grid and microgrid reliability, sustainability, flexibility, and resiliency
Smart grid and microgrid dynamics, stability, protection and security
Methodologies and applications of modern methods for the operation and control of smart grids
Intelligent systems, solving methods, optimization, and advanced heuristics
The modeling, planning, and operating of renewable energy resources
Business models for different electricity market players
Demand side management and demand response
The sizing, placement, and operation of energy storage systems and electric vehicles
Smart homes and building energy management
Electricity market, electrical power, and energy systems
The modeling, forecasting, and management of uncertainty in smart grids
Microgrids and islanded networks
Smart cities, smart energy, and IoT
Modern power systems and renewable energy resources

Prof. Dr. Pierluigi Siano
Dr. Hassan Haes Alhelou
Guest Editor

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Published Papers (10 papers)

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Research

29 pages, 7010 KiB

Open AccessArticle

A Multi-Layer Security Scheme for Mitigating Smart Grid Vulnerability against Faults and Cyber-Attacks

by Jian Chen, Mohamed A. Mohamed, Udaya Dampage, Mostafa Rezaei, Saleh H. Salmen, Sami Al Obaid and Andres Annuk

Appl. Sci. 2021, 11(21), 9972; https://doi.org/10.3390/app11219972 - 25 Oct 2021

Cited by 30 | Viewed by 3499

Abstract

To comply with electric power grid automation strategies, new cyber-security protocols and protection are required. What we now experience is a new type of protection against new disturbances namely cyber-attacks. In the same vein, the impact of disturbances arising from faults or cyber-attacks should be surveyed by network vulnerability criteria alone. It is clear that the diagnosis of vulnerable points protects the power grid against disturbances that would inhibit outages such as blackouts. So, the first step is determining the network vulnerable points, and then proposing a support method to deal with these outages. This research proposes a comprehensive approach to deal with outages by determining network vulnerable points due to physical faults and cyber-attacks. The first point, the network vulnerable points against network faults are covered by microgrids. As the second one, a new cyber-security protocol named multi-layer security is proposed in order to prevent targeted cyber-attacks. The first layer is a cyber-security-based blockchain method that plays a general role. The second layer is a cyber-security-based reinforcement-learning method, which supports the vulnerable points by monitoring data. On the other hand, the trend of solving problems becomes routine when no ambiguity arises in different sections of the smart grid, while it is far from a big network’s realities. Hence, the impact of uncertainty parameters on the proposed framework needs to be considered. Accordingly, the unscented transform method is modeled in this research. The simulation results illustrate that applying such a comprehensive approach can greatly pull down the probability of blackouts. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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33 pages, 14834 KiB

Open AccessArticle

Smart Grid Data Management in a Heterogeneous Environment with a Hybrid Load Forecasting Model

by Ammar Albayati, Nor Fadzilah Abdullah, Asma Abu-Samah, Ammar Hussein Mutlag and Rosdiadee Nordin

Appl. Sci. 2021, 11(20), 9600; https://doi.org/10.3390/app11209600 - 15 Oct 2021

Cited by 4 | Viewed by 2480

Abstract

The power consumption model can be represented in multiple dimensions, and it is proliferating to include structured and unstructured data. Dealing with such heterogeneous data and analyzing it in real-time is an ongoing challenge in the energy sector. Moreover, converting these data into useful information remains an open research area. This study focuses on modeling realistic and efficient power consumption data management in the heterogeneous environment for the Iraq energy sector and suggested a novel hybrid load forecasting model. The proposed system is named the Power Consumption Information and Analytics System (PIAS), which can perform various roles such as data acquisition from mechanical and smart meters, data federation, data management, data visualization, data analysis, and load forecasting. The proposed system has a four-tier framework (Data, Analytics, Application, and Presentation). Each layer is discussed in detail in this study to overcome the anticipated challenges. Furthermore, this study discusses the proposed system by applying two case studies. The first case study discusses power consumption data management, while the second introduces a novel hybrid load forecasting model using Fuzzy C-Means clustering, Auto Regressive Integrated Moving Average (ARIMA), and Gradient Boosted Tree Learner. The dataset used in this forecasting is based on a 1-year duration dated 1 January 2019 to 31 December 2019, on an hourly basis (365 * 24) for the Baghdad governorate. The results showed high accuracy in load forecasting with improved error rates (MAPE, MAE, and RMSE) achievements in comparison with other evaluated models such as standalone ARIMA and Gradient Boosted Trees methods. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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27 pages, 5386 KiB

Open AccessFeature PaperArticle

Short-Term Power Forecasting Framework for Microgrids Using Combined Baseline and Regression Models

by Antonio Parejo, Stefano Bracco, Enrique Personal, Diego Francisco Larios, Federico Delfino and Carlos León

Appl. Sci. 2021, 11(14), 6420; https://doi.org/10.3390/app11146420 - 12 Jul 2021

Cited by 2 | Viewed by 2479

Abstract

Short-term electric power forecasting is a tool of great interest for power systems, where the presence of renewable and distributed generation sources is constantly growing. Specifically, this type of forecasting is essential for energy management systems in buildings, industries and microgrids for optimizing the operation of their distributed energy resources under different criteria based on their expected daily energy balance (the consumption–generation relationship). Under this situation, this paper proposes a complete framework for the short-term multistep forecasting of electric power consumption and generation in smart grids and microgrids. One advantage of the proposed framework is its capability of evaluating numerous combinations of inputs, making it possible to identify the best technique and the best set of inputs in each case. Therefore, even in cases with insufficient input information, the framework can always provide good forecasting results. Particularly, in this paper, the developed framework is used to compare a whole set of rule-based and machine learning techniques (artificial neural networks and random forests) to perform day-ahead forecasting. Moreover, the paper presents and a new approach consisting of the use of baseline models as inputs for machine learning models, and compares it with others. Our results show that this approach can significantly improve upon the compared techniques, achieving an accuracy improvement of up to 62% over that of a persistence model, which is the best of the compared algorithms across all application cases. These results are obtained from the application of the proposed methodology to forecasting five different load and generation power variables for the Savona Campus at the University of Genova in Italy. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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12 pages, 6916 KiB

Open AccessArticle

Novel Coordinated Control Strategy of BESS and PMSG-WTG for Fast Frequency Response

by Hyunwook Kim, Junghun Lee, Jaehyeong Lee and Gilsoo Jang

Appl. Sci. 2021, 11(9), 3874; https://doi.org/10.3390/app11093874 - 25 Apr 2021

Cited by 8 | Viewed by 2145

Abstract

An increase in inverter-based resources (IBRs) can lower the inertia of a power system, which may adversely affect the power system by causing changes such as a frequency nadir reduction or an increased initial rate of change of frequency (RoCoF). To prevent this, an ancillary service called fast frequency response (FFR) helps the inertia response by using IBRs. The main resources used in FFR are variable-speed wind turbine generators (VSWTGs) or energy storage systems (ESSs), which can respond quickly through converter control. The control is applied to the frequency regulation service faster than the primary frequency response, so the second frequency nadir may fall below the first frequency nadir. This study proposed a novel coordinated control strategy to efficiently utilize energy to improve the frequency nadir through coordinated control of wind turbines based on permanent magnetic synchronous generators (PMSGs) and battery energy storage systems (BESSs). The simulation results confirmed that the two-bus test system was composed of PSCAD/EMTDC, and the frequency nadir increased by utilizing the same amount of energy as in traditional control systems. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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14 pages, 3459 KiB

Open AccessArticle

Research on Energy Storage Optimization Operation Schedule in an Island System

by Yu-Tung Chen, Cheng-Chien Kuo and Jia-Zhang Jhan

Appl. Sci. 2021, 11(8), 3690; https://doi.org/10.3390/app11083690 - 19 Apr 2021

Cited by 2 | Viewed by 2207

Abstract

This paper proposes a 24-h ahead unit commitment for a diesel-photovoltaic (PV)-battery system using mixed-integer linear programming (MILP) to minimize the operating cost which includes the power storage system (PSS) in the reserve capacity. Considering the Kinmen island’s winter peak load case of 20 MW, and summer peak load case of 60 MW, a 24-h schedule for the diesel-PV-battery system island system for these two scenarios was optimized that allows the PSS to perform both as an additional reserve capacity and peak-shaving auxiliary device. The results show that the addition of PSS in the dispatch decision can allow the flexibility of the systems, especially in the reserve allocation, to up to twice the value of the PSS capacity. In this way, the PSS reduces the early startup and late shutdown of high-cost units while maintaining the system reserve, thereby, reducing the operating cost of the system. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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17 pages, 6529 KiB

Open AccessArticle

Integrated Control and Protection Architecture for Islanded PV-Battery DC Microgrids: Design, Analysis and Experimental Verification

by Ali Abdali, Kazem Mazlumi and Josep M. Guerrero

Appl. Sci. 2020, 10(24), 8847; https://doi.org/10.3390/app10248847 - 10 Dec 2020

Cited by 20 | Viewed by 55985

Abstract

Direct current (dc) microgrids have gained significant interest in research due to dc generation/storage technologies—such as photovoltaics (PV) and batteries—increasing performance and reducing in cost. However, proper protection and control systems are critical in order to make dc microgrids feasible. This paper aims to propose a novel integrated control and protection scheme by using the state-dependent Riccati equation (SDRE) method for PV-battery based islanded dc microgrids. The dc microgrid under study consists of photovoltaic (PV) generation, a battery energy storage system (BESS), a capacitor bank and a dc load. The aims of this study are fast fault detection and voltage control of the dc load bus. To do so, the SDRE observer-controller—a nonlinear mathematical model—is employed to model the operation of the dc microgrid. Simulation results show that the proposed SDRE method is effective for fault detection and robust against external disturbances, resulting in it being capable of controlling the dc load bus voltage during disturbances. Finally, the dc microgrid and its proposed protection scheme are implemented in an experimental testbed prototype to verify the fault detection algorithm feasibility. The experimental results indicate that the SDRE scheme can effectively detect faults in a few milliseconds. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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13 pages, 7408 KiB

Open AccessFeature PaperArticle

Dispatchable Substation for Operation and Control of Renewable Energy Resources

by Yeuntae Yoo, Seungmin Jung, Sungwoo Kang, Sungyoon Song, Jaehyeong Lee, Changhee Han and Gilsoo Jang

Appl. Sci. 2020, 10(21), 7938; https://doi.org/10.3390/app10217938 - 9 Nov 2020

Cited by 8 | Viewed by 3195

Abstract

Renewable generation in power systems has proved to be challenging for system operators owing to the increasing levels of penetration. The operation of power systems currently requires additional flexibility and reserves due to the intermittency and unpredictability of renewable generators. However, it is difficult to precisely predict and control the stochastic nature of renewable sources; nevertheless, its capacity continues to increase. To monitor and control renewable generators efficiently, the entire system needs to be established in a hierarchical order. This study proposed the concept of a substation that is uniquely designed for renewable interconnection. The purpose of this substation is simple: to make the renewable generators dispatchable to operators such that each group of renewable generators is sufficiently stable to be considered as conventional generators. For this purpose, methods for sizing and controlling energy storage system are proposed based on forecasts and error distributions. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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23 pages, 784 KiB

Open AccessFeature PaperArticle

Analyzing Six Indices for Online Short-Term Voltage Stability Monitoring in Power Systems

by Milad Aslanian, Mohammad Esmaeil Hamedani-Golshan, Hassan Haes Alhelou and Pierluigi Siano

Appl. Sci. 2020, 10(12), 4200; https://doi.org/10.3390/app10124200 - 18 Jun 2020

Cited by 7 | Viewed by 2471

Abstract

In recent years, the importance of online monitoring short-term voltage stability has been considerably increased. Unstable cases due to response of fast dynamic loads such as induction motors to the serious disturbances can be avoided by online monitoring of voltage transients and activating fast and appropriate controls to encounter deep and prolonged voltage drop. In this paper, a set of indices based on the phasor measurement unit (PMU) measurements are introduced and compared for short-term voltage stability. To increase efficiency of the indices, a special algorithm for each index is proposed by using the investigation of the results of applying them to six disturbances’ scenarios simulated on the IEEE 39 bus system. The disturbance scenarios are representative of different cases of stable, unstable, and deep and prolonged voltage drop associated with short-term voltage transients. The performance of these indices are studied in terms of the time and accuracy required for determining the short-term voltage stability/instability cases. It is shown that the proposed method has better performance in comparison with other techniques that can be applied to power systems in reality. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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24 pages, 5891 KiB

Open AccessArticle

Resilient Self-Triggered Control for Voltage Restoration and Reactive Power Sharing in Islanded Microgrids under Denial-of-Service Attacks

by Gang Xu and Liang Ma

Appl. Sci. 2020, 10(11), 3780; https://doi.org/10.3390/app10113780 - 29 May 2020

Cited by 12 | Viewed by 2642

Abstract

This paper addresses the problem of voltage restoration and reactive power sharing of inverter-based distributed generations (DGs) in an islanded microgrid subject to denial-of-service (DoS) attacks. Note that DoS attacks may block information exchange among DGs by jamming the communication network in the secondary control level of a microgrid. A two-layer distributed secondary control framework is presented, in which a state observer employing the multiagent system (MAS)-based ternary self-triggered control is implemented for discovering the average information of voltage and reactive power in a fully distributed manner while highly reducing communication burden than that the periodic communication way. The compensation for the reference signal to the primary control is acquired according to the average estimates to achieve voltage restoration while properly sharing reactive power among DGs. An improved ternary self-triggered control strategy integrating an acknowledgment (ACK)-based monitoring mechanism is established, where DoS attacks are modeled by repeated cycles of jamming and sleeping. A new triggering condition is developed to guarantee the successful information exchange between DGs when the sleep period of DoS attacks is detected. Using the Lyapunov approach, it is proved that the proposed algorithm allows agents to reach consensus regardless of the frequency of the DoS attacks, which maintains the accurate estimation of average information and the implementation of the secondary control objectives. The performance of the proposed control scheme is evaluated under simulation and experimental conditions. The results show that the proposed secondary control scheme can highly reduce the inter-agent communication as well as improve the robustness of the system to resist DoS attacks. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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22 pages, 1462 KiB

Open AccessArticle

A Protection Scheme for a Power System with Solar Energy Penetration

by Sheesh Ram Ola, Amit Saraswat, Sunil Kumar Goyal, S. K. Jhajharia, Baseem Khan, Om Prakash Mahela, Hassan Haes Alhelou and Pierluigi Siano

Appl. Sci. 2020, 10(4), 1516; https://doi.org/10.3390/app10041516 - 23 Feb 2020

Cited by 57 | Viewed by 6075

Abstract

As renewable energy (RE) penetration has a continuously increasing trend, the protection of RE integrated power systems is a critical issue. Recently, power networks developed for grid integration of solar energy (SE) have been designed with the help of multi-tapped lines to integrate small- and medium-sized SE plants and simultaneously supplying power to the loads. These tapped lines create protection challenges. This paper introduces an algorithm for the recognition of faults in the grid to which a solar photovoltaic (PV) system is integrated. A fault index (FI) was introduced to identify faults. This FI was calculated by multiplying the Wigner distribution (WD) index and Alienation (ALN) index. The WD-index was based on the energy density of the current signal evaluated using Wigner distribution function. The ALN-index was evaluated using sample-based alienation coefficients of the current signal. The performance of the algorithm was validated for various scenarios with different fault types at various locations, different fault incident angles, fault impedances, sampling frequencies, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, different types of transformer windings and the presence of noise. Two phase faults with and without the involvement of ground were differentiated using the ground fault index based on the zero sequence current. This study was performed on the IEEE-13 nodes test network to which a solar PV plant with a capacity of 1 MW was integrated. The performance of the algorithm was also tested on the western part of utility grid in the Rajasthan State in India where solar PV energy integration is high. The performance of the algorithm was effectively established by comparing it with the discrete Wavelet transform (DWT), Wavelet packet transform (WPT) and Stockwell transform-based methods. Full article

(This article belongs to the Special Issue Advances and Trends in Smart Grids and Microgrids: Operation, Control, Protection, and Security)

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