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Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021

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A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 44436

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Prof. Dr. Nicu Bizon

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Faculty of Electronics, Communication and Computers, University of Pitesti, 110040 Pitesti, Romania
Interests: electrical engineering; power electronics; power converters; inverters; renewable energy; energy efficiency; energy storage; fuel cell; hybrid power systems; control; optimization; MATLAB simulation
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Dear Colleagues,

The generation of distributed electricity using micro- and nano-grids is an obvious opportunity to reduce CO₂ emissions if hydrogen energy technology is used in addition to renewable energy potential. It is expected that these hybrid microgrids will play an important role in the implementation of the scenario of limiting global warming to 2⁰ C by replacing fossil fuels with renewables.

Thus, to highlight the latest solutions and paradigms in hybrid microgrids, such as vehicle-to-everything (V2X), power-following control, grid-responsive strategies, and global optimization strategies, this Special Issue, titled “Advanced Modeling and Research in Hybrid Microgrid Control and Optimization”, is proposed for Mathematics from MDPI, which is an international peer-reviewed open access covered by many databased such WOS (SCIE Impact Factor 1.747 (2019), Q1) and SCOPUS (Elsevier). The present Special Issue aims to collect innovative solutions and experimental research supported by appropriate modeling and design, as well as state-of-the-art studies, in the following topics:

Hybrid nano- and micro-grids;
Hybrid power systems (HPSs);
Renewable energy sources (RESs);
Fuel Cell (FC) systems;
Hybrid energy storage systems (HESSs);
Smart contracts based on IoT blockchain technology;
Cyber-security, reliability, maintenance, resilience, and safety in the operation of FC/RES hybrid microgrids;
Energy management and optimization strategies for FC/RES HPS;
Control, optimization, and energy management strategies for hybrid/FC/electrical vehicles;
Vehicle-to-everything (V2X) architectures;
Communication architectures for microgrids.

Prof. Dr. Nicu Bizon
Guest Editor

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Keywords

Hybrid nano- and micro-grids
Hybrid power systems (HPSs)
Renewable energy sources (RESs)
Fuel cell (FC) systems
FC RES hybrid microgrids
Energy management strategies (EMSs)
Blockchain technology
Smart contracts
Hybrid energy storage systems (HESSs)
Fuel cell vehicles (FCVs)
Vehicle-to-everything (V2X)
Vehicle-to-building (V2B)
Vehicle-to-grid (V2G)
Optimization strategies
Energy management strategies
System modeling and design
Cyber-security
Communication
Reliability, maintenance, resilience, and safety in operation.

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15 pages, 4158 KiB

Open AccessArticle

Optimized Power Supply Rejection Ratio Modeling Technique for Simulation of Automotive Low-Dropout Linear Voltage Regulators

by Ionuț-Constantin Guran, Adriana Florescu and Lucian Andrei Perișoară

Mathematics 2022, 10(7), 1150; https://doi.org/10.3390/math10071150 - 2 Apr 2022

Cited by 2 | Viewed by 2831

Abstract

In the automotive domain, the vast majority of testing is performed through simulations, which can validate a system design before the actual implementation and can emphasize eventual faults in the design process. Hence, the simulation is of utmost importance. Behavioral models are necessary for the creation of each electronic device desired in the system, and some of the components have very complex behavior: low-dropout linear voltage regulators (LDOs), gate drivers, and switching regulators. In the automotive industry, LDOs are essential components because they power all the other subsystems and very accurate behavior is needed to make sure that the system behaves as in reality. LDO models are already commercially available and most of their intrinsic characteristics are modeled (dropout voltage, line regulation, load regulation, etc.). However, one characteristic that is extremely useful, yet the hardest to model, is the power supply rejection ratio (PSRR). This paper proposes a new PSRR modeling technique for automotive low-dropout voltage regulators. The new PSRR characteristic was modeled for an automotive LDO product in a Texas Instruments portfolio, which has a commercially available model, and was simulated using the PSpice Allegro simulator and the OrCAD Capture CIS environment. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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19 pages, 4434 KiB

Open AccessArticle

Smart Campus Microgrids towards a Sustainable Energy Transition—The Case Study of the Hellenic Mediterranean University in Crete

by Alexandros Paspatis, Konstantinos Fiorentzis, Yiannis Katsigiannis and Emmanuel Karapidakis

Mathematics 2022, 10(7), 1065; https://doi.org/10.3390/math10071065 - 25 Mar 2022

Cited by 14 | Viewed by 2792

Abstract

Smart campus microgrids are considered in this paper, with the aim of highlighting their applicability in the framework of the sustainable energy transition. In particular, the campus of the Hellenic Mediterranean University (HMU) in Heraklion, Crete, Greece, is selected as a case study to highlight the multiple campus microgrids’ advantages. Crete represents an interesting insular power system case, due to the high renewable energy sources capacity and the large summer tourism industry. There is also a high density of university and research campuses, making the campus microgrid concept a promising solution for the energy transition and decarbonization of the island. In this sense, policy directions that could facilitate the development of the smart campus microgrid are also given, to motivate areas with similar characteristics. For the performed case study, the HMU microgrid is assumed to consist of PV systems, wind turbines, battery energy storage systems and EV chargers. The analysis explores the financial feasibility and environmental impact of such an investment through the optimal sizing of the systems under investigation, while a sensitivity analysis regarding the battery system cost is also performed. Apart from the financial benefits of the investment, it is evident that the main grid experiences a significant load reduction, with the microgrid acting as a RES producer for many hours, hence improving system adequacy. Moreover, it is shown that the location of HMU makes the investment more sustainable compared to other locations in northern Europe, such as Stockholm and London. The methodology and the derived results are expected to motivate such investments, especially in areas with high RES capacity and a high density of university and research campuses. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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17 pages, 16642 KiB

Open AccessArticle

Optimal Management of Energy Consumption in an Autonomous Power System Considering Alternative Energy Sources

by Vadim Manusov, Svetlana Beryozkina, Muso Nazarov, Murodbek Safaraliev, Inga Zicmane, Pavel Matrenin and Anvari Ghulomzoda

Mathematics 2022, 10(3), 525; https://doi.org/10.3390/math10030525 - 8 Feb 2022

Cited by 30 | Viewed by 3082

Abstract

This work aims to analyze and manage the optimal power consumption of the autonomous power system within the Pamir region of Republic of Tajikistan, based on renewable energy sources. The task is solved through linear programming methods, production rules and mathematical modeling of power consumption modes by generating consumers. It is assumed that power consumers in the considered region have an opportunity to independently cover energy shortage by installing additional generating energy sources. The objective function is to minimize the financial expenses for own power consumption, and to maximize them from both the export and redistribution of power flows. In this study, the optimal ratio of power generation by alternative sources from daily power consumption for winter was established to be hydroelectric power plants (94.8%), wind power plant (3.8%), solar photovoltaic power plant (0.5%) and energy storage (0.8%); while it is not required in summer due to the ability to ensure the balance of energy by hydroelectric power plants. As a result, each generating consumer can independently minimize their power consumption and maximize profit from the energy exchange with other consumers, depending on the selected energy sources, thus becoming a good example of carbon-free energy usage at the micro- and mini-grid level. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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25 pages, 3085 KiB

Open AccessArticle

On Active Vibration Absorption in Motion Control of a Quadrotor UAV

by Francisco Beltran-Carbajal, Hugo Yañez-Badillo, Ruben Tapia-Olvera, Antonio Favela-Contreras, Antonio Valderrabano-Gonzalez and Irvin Lopez-Garcia

Mathematics 2022, 10(2), 235; https://doi.org/10.3390/math10020235 - 13 Jan 2022

Cited by 6 | Viewed by 2604

Abstract

Conventional dynamic vibration absorbers are physical control devices designed to be coupled to flexible mechanical structures to be protected against undesirable forced vibrations. In this article, an approach to extend the capabilities of forced vibration suppression of the dynamic vibration absorbers into desired motion trajectory tracking control algorithms for a four-rotor unmanned aerial vehicle (UAV) is introduced. Nevertheless, additional physical control devices for mechanical vibration absorption are unnecessary in the proposed motion profile reference tracking control design perspective. A new dynamic control design approach for efficient tracking of desired motion profiles as well as for simultaneous active harmonic vibration absorption for a quadrotor helicopter is then proposed. In contrast to other control design methods, the presented motion tracking control scheme is based on the synthesis of multiple virtual (nonphysical) dynamic vibration absorbers. The mathematical structure of these physical mechanical devices, known as dynamic vibration absorbers, is properly exploited and extended for control synthesis for underactuated multiple-input multiple-output four-rotor nonlinear aerial dynamic systems. In this fashion, additional capabilities of active suppression of vibrating forces and torques can be achieved in specified motion directions on four-rotor helicopters. Moreover, since the dynamic vibration absorbers are designed to be virtual, these can be directly tuned for diverse operating conditions. In the present study, it is thus demonstrated that the mathematical structure of physical mechanical vibration absorbers can be extended for the design of active vibration control schemes for desired motion trajectory tracking tasks on four-rotor aerial vehicles subjected to adverse harmonic disturbances. The effectiveness of the presented novel design perspective of virtual dynamic vibration absorption schemes is proved by analytical and numerical results. Several operating case studies to stress the advantages to extend the undesirable vibration attenuation capabilities of the dynamic vibration absorbers into trajectory tracking control algorithms for nonlinear four-rotor helicopter systems are presented. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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24 pages, 1315 KiB

Open AccessArticle

Optimising Energy Management in Hybrid Microgrids

by Javier Bilbao, Eugenio Bravo, Olatz García, Carolina Rebollar and Concepción Varela

Mathematics 2022, 10(2), 214; https://doi.org/10.3390/math10020214 - 11 Jan 2022

Cited by 4 | Viewed by 2327

Abstract

This article deals with the optimization of the operation of hybrid microgrids. Both the problem of controlling the management of load sharing between the different generators and energy storage and possible solutions for the integration of the microgrid into the electricity market will be discussed. Solar and wind energy as well as hybrid storage with hydrogen, as renewable sources, will be considered, which allows management of the energy balance on different time scales. The Machine Learning method of Decision Trees, combined with ensemble methods, will also be introduced to study the optimization of microgrids. The conclusions obtained indicate that the development of suitable controllers can facilitate a competitive participation of renewable energies and the integration of microgrids in the electricity system. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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17 pages, 1877 KiB

Open AccessArticle

Differential Evolution Based Algorithm for Optimal Current Ripple Cancelation in an Unequal Interleaved Power Converter

by Julio C. Rosas-Caro, Pedro M. García-Vite, Alma Rodríguez, Abraham Mendoza, Avelina Alejo-Reyes, Erik Cuevas and Francisco Beltran-Carbajal

Mathematics 2021, 9(21), 2755; https://doi.org/10.3390/math9212755 - 29 Oct 2021

Cited by 4 | Viewed by 1845

Abstract

This paper proposes an optimal methodology based on the Differential Evolution algorithm for obtaining the set of duty cycles of a recently proposed power electronics converter with input current ripple cancelation capability. The converter understudy was recently introduced to the state-of-the-art as the interleaved connection of two unequal converters to achieve low input current ripple. A latter contribution proposed a so-called proportional strategy. The strategy can be described as the equations to relate the duty cycles of the unequal power stages. This article proposes a third switching strategy that provides a lower input current ripple than the proportional strategy. This is made by considering duty cycles independently of each other instead of proportionally. The proposed method uses the Differential Evolution algorithm to determine the optimal switching pattern that allows high quality at the input current side, given the reactive components, the switching frequency, and power levels. The mathematical model of the converter is analyzed, and thus, the decision variables and the optimization problem are well set. The proposed methodology is validated through numerical experimentation, which shows that the proposed method achieves lower input current ripples than the proportional strategy. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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23 pages, 46601 KiB

Open AccessArticle

A Fast-Tracking Hybrid MPPT Based on Surface-Based Polynomial Fitting and P&O Methods for Solar PV under Partial Shaded Conditions

by Catalina González-Castaño, Carlos Restrepo, Javier Revelo-Fuelagán, Leandro L. Lorente-Leyva and Diego H. Peluffo-Ordóñez

Mathematics 2021, 9(21), 2732; https://doi.org/10.3390/math9212732 - 28 Oct 2021

Cited by 8 | Viewed by 2520

Abstract

The efficiency of photovoltaic (PV) systems depends directly on solar irradiation, so drastic variations in solar exposure will undoubtedly move its maximum power point (MPP). Furthermore, the presence of partial shading conditions (PSCs) generates local maximum power points (LMPPs) and one global maximum power point (GMPP) in the P-V characteristic curve. Therefore, a proper maximum power point tracking (MPPT) technique is crucial to increase PV system efficiency. There are classical, intelligent, optimal, and hybrid MPPT techniques; this paper presents a novel hybrid MPPT technique that combines Surface-Based Polynomial Fitting (SPF) and Perturbation and Observation (P&O) for solar PV generation under PSCs. The development of the experimental PV system has two stages: (i) Modeling the PV array with the DC-DC boost converter using a real-time and high-speed simulator (PLECS RT Box), (ii) and implementing the proposed GMPPT algorithm with the double-loop controller of the DC-DC boost converter in a commercial low-priced digital signal controller (DSC). According to the simulation and the experimental results, the suggested hybrid algorithm is effective at tracking the GMPP under both uniform and nonuniform irradiance conditions in six scenarios: (i) system start-up, (ii) uniform irradiance variations, (iii) sharp change of the (PSCs), (iv) multiple peaks in the P-V characteristic, (v) dark cloud passing, and (vi) light cloud passing. Finally, the experimental results—through the standard errors and the mean power tracked and tracking factor scores—proved that the proposed hybrid SPF-P&O MPPT technique reaches the convergence to GMPP faster than benchmark approaches when dealing with PSCs. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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19 pages, 1512 KiB

Open AccessArticle

A Hybrid MCDM Approach in Third-Party Logistics (3PL) Provider Selection

by Stefan Jovčić and Petr Průša

Mathematics 2021, 9(21), 2729; https://doi.org/10.3390/math9212729 - 27 Oct 2021

Cited by 20 | Viewed by 3235

Abstract

Third-party logistics (3PL) is becoming more and more popular because of globalization, e-commerce development, and increasing customer demand. More and more companies are trying to move away from their own account transportation to third-party accounts. One reason for using 3PLs is that the company can focus more on its core activities, while the 3PL service provider can provide distribution activities in a more professional way, save costs and time, and increase the level of customer satisfaction. An emerging issue for companies in the logistics industry is how they can decide on the 3PL evaluation and selection process for outsourcing activities. For the first time, the entropy and the criteria importance through intercriteria correlation (CRITIC) methods were coupled in order to obtain hybrid criteria weights that are of huge importance to decide on the 3PL provider evaluation and selection process. The obtained criteria weights were further utilized within the additive ratio assessment (ARAS) method to rank the alternatives from the best to the worst. The introduced hybrid–ARAS approach can be highly beneficial, since combining two methods gives more robust solutions on one hand, while on the other hand eliminating subjectivity. Comparative and sensitivity analyses showed the high reliability of the proposed hybrid–ARAS method. A hypothetical case study is presented to illustrate the potentials and applicability of the hybrid–ARAS method. The results showed that 3PL-2 was the best possible solution for our case. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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24 pages, 7253 KiB

Open AccessArticle

Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles

by Piyush Dhawankar, Prashant Agrawal, Bilal Abderezzak, Omprakash Kaiwartya, Krishna Busawon and Maria Simona Raboacă

Mathematics 2021, 9(14), 1696; https://doi.org/10.3390/math9141696 - 19 Jul 2021

Cited by 9 | Viewed by 4229

Abstract

This paper is concerned with designing and numerically implementing a V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) control system architecture for a platoon of autonomous vehicles. The V2X control architecture integrates the well-known Intelligent Driver Model (IDM) for a platoon of Autonomous Driving Vehicles (ADVs) with Vehicle-to-Infrastructure (V2I) Communication. The main aim is to address practical implementation issues of such a system as well as the safety and security concerns for traffic environments. To this end, we first investigated a channel estimation model for V2I communication. We employed the IEEE 802.11p vehicular standard and calculated path loss, Packet Error Rate (PER), Signal-to-Noise Ratio (SNR), and throughput between transmitter and receiver end. Next, we carried out several case studies to evaluate the performance of the proposed control system with respect to its response to: (i) the communication infrastructure; (ii) its sensitivity to an emergency, inter-vehicular gap, and significant perturbation; and (iii) its performance under the loss of communication and changing driving environment. Simulation results show the effectiveness of the proposed control model. The model is collision-free for an infinite length of platoon string on a single lane road-driving environment. It also shows that it can work during a lack of communication, where the platoon vehicles can make their decision with the help of their own sensors. V2X Enabled Intelligent Driver Model (VX-IDM) performance is assessed and compared with the state-of-the-art models considering standard parameter settings and metrics. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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22 pages, 1894 KiB

Open AccessArticle

An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems

by Sunil Kumar Mishra, Amitkumar V. Jha, Vijay Kumar Verma, Bhargav Appasani, Almoataz Y. Abdelaziz and Nicu Bizon

Mathematics 2021, 9(11), 1262; https://doi.org/10.3390/math9111262 - 31 May 2021

Cited by 9 | Viewed by 2990

Abstract

This paper presents an optimized algorithm for event-triggered control (ETC) of networked control systems (NCS). Initially, the traditional backstepping controller is designed for a generalized nonlinear plant in strict-feedback form that is subsequently extended to the ETC. In the NCS, the controller and the plant communicate with each other using a communication network. In order to minimize the bandwidth required, the number of samples to be sent over the communication channel should be reduced. This can be achieved using the non-uniform sampling of data. However, the implementation of non-uniform sampling without a proper event triggering rule might lead the closed-loop system towards instability. Therefore, an optimized event triggering algorithm has been designed such that the system states are always forced to remain in stable trajectory. Additionally, the effect of ETC on the stability of backstepping control has been analyzed using the Lyapunov stability theory. Two case studies on an inverted pendulum system and single-link robot system have been carried out to demonstrate the effectiveness of the proposed ETC in terms of system states, control effort and inter-event execution time. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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19 pages, 7710 KiB

Open AccessArticle

Optimal Parameter Estimation Methodology of Solid Oxide Fuel Cell Using Modern Optimization

by Hesham Alhumade, Ahmed Fathy, Abdulrahim Al-Zahrani, Muhyaddin Jamal Rawa and Hegazy Rezk

Mathematics 2021, 9(9), 1066; https://doi.org/10.3390/math9091066 - 10 May 2021

Cited by 15 | Viewed by 2580

Abstract

An optimal parameter estimation methodology of solid oxide fuel cell (SOFC) using modern optimization is proposed in this paper. An equilibrium optimizer (EO) has been used to identify the unidentified parameters of the SOFC equivalent circuit with the assistance of experimental results. This is presented via formulating the modeling process as an optimization problem considering the sum mean squared error (SMSE) between the observed and computed voltages as the target. Two modes of the SOFC-based model are investigated under variable operating conditions, namely, the steady-state and the dynamic-state based models. The proposed EO results are compared to those obtained via the Archimedes optimization algorithm (AOA), Heap-based optimizer (HBO), Seagull Optimization Algorithm (SOA), Student Psychology Based Optimization Algorithm (SPBO), Marine predator algorithm (MPA), Manta ray foraging optimization (MRFO), and comprehensive learning dynamic multi-swarm marine predators algorithm. The minimum fitness function at the steady-state model is obtained via the proposed EO with value of 1.5527 × 10⁻⁶ at 1173 K. In the dynamic based model, the minimum SMSE is 1.0406. The obtained results confirmed the reliability and superiority of the proposed EO in constructing a reliable model of SOFC. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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23 pages, 8838 KiB

Open AccessArticle

Dynamic Stability Performance of Autonomous Microgrid Involving High Penetration Level of Constant Power Loads

by Mohamed A. Hassan, Muhammed Y. Worku, Abdelfattah A. Eladl and Mohammed A. Abido

Mathematics 2021, 9(9), 922; https://doi.org/10.3390/math9090922 - 21 Apr 2021

Cited by 6 | Viewed by 2257

Abstract

Nowadays, behaving as constant power loads (CPLs), rectifiers and voltage regulators are extensively used in microgrids (MGs). The MG dynamic behavior challenges both stability and control effectiveness in the presence of CPLs. CPLs characteristics such as negative incremental resistance, synchronization, and control loop dynamic with similar frequency range of the inverter disturb severely the MG stability. Additionally, the MG stability problem will be more sophisticated with a high penetration level of CPLs in MGs. The stability analysis becomes more essential especially with high-penetrated CPLs. In this paper, the dynamic stability performance of an MG involving a high penetration level of CPLs is analyzed and investigated. An autonomous MG engaging a number of CPLs and inverter distributed generations (DGs) is modeled and designed using MATLAB. Voltage, current, and power controllers are optimally designed, controlling the inverter DGs output. A power droop controller is implemented to share the output DGs powers. Meanwhile, the current and voltage controllers are employed to control the output voltage and current of all DGs. A phase-locked loop (PLL) is essentially utilized to synchronize the CPLs with the MG. The controller gains of the inverters, CPLs, power sharing control, and PLL are optimally devised using particle swarm optimization (PSO). As a weighted objective function, the error in the DC voltage of the CPL and active power of the DG is minimized in the optimal problem based on the time-domain simulation. Under the presence of high penetrated CPLs, all controllers are coordinately tuned to ensure an enhanced dynamic stability of the MG. The impact of the highly penetrated CPLs on the MG dynamic stability is investigated. To confirm the effectiveness of the proposed technique, different disturbances are applied. The analysis shows that the MG system experiences the instability challenges due to the high penetrated CPLs. The simulation results confirm the effectiveness of the proposed method to improve the MG dynamic stability performance. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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23 pages, 777 KiB

Open AccessReview

Islanding Detection Methods for Microgrids: A Comprehensive Review

by Muhammed Y. Worku, Mohamed A. Hassan, Luqman S. Maraaba and Mohammad A. Abido

Mathematics 2021, 9(24), 3174; https://doi.org/10.3390/math9243174 - 9 Dec 2021

Cited by 33 | Viewed by 8831

Abstract

Microgrids that are integrated with distributed energy resources (DERs) provide many benefits, including high power quality, energy efficiency and low carbon emissions, to the power grid. Microgrids are operated either in grid-connected or island modes running on different strategies. However, one of the major technical issues in a microgrid is unintentional islanding, where failure to trip the microgrid may lead to serious consequences in terms of protection, security, voltage and frequency stability, and safety. Therefore, fast and efficient islanding detection is necessary for reliable microgrid operations. This paper provides an overview of microgrid islanding detection methods, which are classified as local and remote. Various detection methods in each class are studied, and the advantages and disadvantages of each method are discussed based on performance evaluation indices such as non-detection zone (NDZ), detection time, error detection ratio, power quality and effectiveness in multiple inverter cases. Recent modifications on islanding methods using signal processing techniques and intelligent classifiers are also discussed. Modified passive methods with signal processing and intelligent classifiers are addressing the drawbacks of passive methods and are getting more attention in the recently published works. This comprehensive review of islanding methods will provide power utilities and researchers a reference and guideline to select the best islanding detection method based on their effectiveness and economic feasibility. Full article

(This article belongs to the Special Issue Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021)

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