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• The cloud-pipe-edge-end operation and communication architecture: aiming at the data privacy problems caused by multi-subject operation in the district integrated energy system, the cloud-pipe-edge-end operation and communication architecture is introduced into the district integrated energy system, which not only protects the data privacy, but also solves the problem that the terminal device information data is large and difficult to collect in real-time, and improves the efficiency of real-time collection, calculation and transmission of multi-energy data information in the system. • Waste heat recovery of energy coupling equipment: aiming at the problem that further reuse of internal waste energy that is not considered in the hierarchical optimization process of district integrated energy system, this paper recycles the heat generated by the combined heat and power and the power to gas during operation, and finds that when 1 kWh of electric energy is used, the heat that can be recycled is 0.1187 kWh, which improves the utilization rate of energy. • A two-layer distributed scheduling model of the district integrated energy system: aiming at the problem that the hierarchical optimization of district integrated energy system, only the economy is considered, and the low-carbon nature of the system and the multi-energy interaction between subsystems are not considered. A two-layer distributed scheduling model of the district integrated energy system is established based on a laddered carbon trading mechanism, which reduces carbon emissions, and maximizes benefits for all parties. • ATC algorithm: aiming at the problem that the optimized sub-objectives in the two-layer model are strongly coupled and cannot be solved quickly and accurately, a two-layer model solving method based on ATC is proposed, which decouples the upper and lower layers by adding augmented Lagrange penalty function, which is very suitable for the decentralized computational architecture of this paper, and realizes the energy mutualization and the balance of interests among multiple subjects while taking into account the data privacy protection. The district integrated energy system has the characteristics of multi-layer and multi-subjects. Aiming at the problems of data privacy, conflict of interest, and mismatch of interaction power among these multi-subjects, a hierarchical distributed optimal scheduling decision-making method for district integrated energy system based on analysis target cascade is proposed. Firstly, the operational communication architecture of the district integrated energy system based on the cloud-pipe-edge-end is constructed to solve the problems of data transmission, data computation, and data privacy. Secondly, a two-layer distributed scheduling model of district integrated energy system considering waste heat recovery is established based on a laddered carbon trading mechanism. At the upper level, an optimal scheduling model targeting low-carbon and economic performance is developed by considering the participation of district integrated energy system in demand response and the purchase and sale of electricity. At the lower level, an optimal scheduling model considering waste heat recovery for subsystem energy-coupled equipment is developed. Then, the analytical target cascade is used to realize the decoupling of the two-layer model, and the efficient solution is achieved in the process of multiple iterations. Finally, by analyzing the arithmetic examples, it is verified that the proposed method can improve the economy of system operation by 4.38% and the absorption capacity of wind power by 9.89%, while protecting the privacy and interest claims of multiple parties. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper presents a model-less centralized control approach for coordinating Renewable Energy Sources and multiterminal DC links in low-voltage distribution networks. The controller is based on the Online Feedback Optimization technique which is adequate for this part of the power system, characterized by a lack of precise model and real-time information. The paper includes the complete mathematical formulation of the optimization problem and its solution applying the presented strategy. The performance of the proposed centralized controller is evaluated through simulations in the European LV distribution network proposed by the CIGRE Task Force C06.04.02. The results show the benefits that DC links may bring to LV networks due to the release of their radial operation. In particular, the proposed strategy achieves a 7.4 % daily energy loss reduction with respect to the base case. The centralized controller, which operates without a detailed network model and reduced real-time information, enables the use of this technology in LV networks which maximizes the penetration of renewable energy sources. • Optimal RES and DC links operation in LV networks without precise network information. • The proposed method reduces the RES curtailment while minimizing the system losses. • The method is able to managing any controllable resource regardless of their type. [ABSTRACT FROM AUTHOR]

Power system reliability evaluation has been conducted based on steady-state analysis approaches such as optimal power flow calculations with minimum load curtailments. These approaches assume that a power system would return to a stable operating state after a contingency (faults, short circuits, etc.), i.e., power system dynamics are not considered. Although this assumption has been widely accepted for conventional power systems, microgrids are more vulnerable to large disturbances than conventional power systems are. In other words, the likelihood of an unstable transition from pre-event to post-event conditions is higher in the case of microgrids than in the case of conventional power grids. Therefore, it has become important to consider both generation adequacy and transient stability in microgrid reliability evaluation. This paper develops an integrated transient stability and reliability assessment approach for microgrids to capture both inadequacy and instability conditions. A Lyapunov function-based approach is developed to determine the stability region for each contingency in calculating the reliability indices. Also, a linearized AC optimal power flow model is developed for composite system reliability evaluation. This paper also provides a set of indices to quantify the impact of transient instability on the reliability of microgrids. The proposed approach is applied to the IEEE 33-bus system in the islanded mode using sedumi and YALMIP optimizers in MATLAB. The results show that 29.19% of the contingencies for which the microgrid is deemed reliable based on steady-state analyses causes unstable conditions, which justifies the need for integrating steady-state and transient conditions in microgrid reliability evaluation. • Integrated framework for microgrid reliability and transient stability assessment. • New transient energy function for large-scale microgrid stability assessment. • Introduced stability-reliability indices for microgrid analysis. [ABSTRACT FROM AUTHOR]

• To counteract the impact of FDIAs, two units for cyberattack detection and mitigation are proposed. • A braided Lyapunov- based state observer is proposed to estimate current and voltage signals for DGUs. • The proposed braided system eliminates the need for extra sensors. • The CMPN adaptive controller outperforms the tuned traditional PI and LMF controllers. • Robustness of the braided Lyapunov-based observer for cyberattack mitigation strategy is validated. The transferred data in microgrids is susceptible to cyberattacks. This paper presents a primary and secondary control loops integrated with units for detecting and mitigating cyberattacks for each distributed generator in a DC microgrid. Most of the literature focused on mitigating cyberattacks using supervised learning techniques. On the contrary, this paper introduces reliable state observer-based mitigation units for voltage and current cyberattacks. A braided Lyapunov-based state observer is proposed to generate accurate estimate of terminal voltage and current, simultaneously, without the need for external measurements. Afterwards, cyberattack mitigation controller is triggered to develop the appropriate corrective actions. Fast control action is essential for effective mitigation of cyberattacks, along with precise state estimation. Therefore, two adaptive PI controllers are introduced in the cyberattack mitigation units. Different case studies are provided to assess the performance of the suggested sensorless cyberattack detection and mitigation strategy. To prove the superiority of the proposed strategy, comparative studies are carried out with the scheme of mitigating cyberattacks based on artificial neural networks (ANNs). The Lyapunov based state observer showed a lower settling time of 0.4 s, lower voltage maximum peak overshoot of 0.16 %, almost zero voltage and current sharing errors, when compared to ANNs. [ABSTRACT FROM AUTHOR]

This paper presents a model for optimizing the management of a Li-Ion battery in a microgrid, considering the presence of nonlinear losses during the charging and discharging processes. The paper examines the nature of these losses and proposes updated nonlinear expressions that depend on the state of charge and on the charging or discharging power. The piecewise linear approximations of the losses bivariate functions are implemented using the novel integer zig-zag (ZZI) formulation. The corresponding ZZI constraints are integrated into an optimization model to determine the optimal schedule for a residential isolated microgrid comprising a solar panel, a diesel generator, and a Li-Ion battery. The case study compares different triangulation strategies regarding their impact on the quality of the obtained solution and the computational burden. • New battery loss expressions for use in an Energy Management System • Considering non-linear losses in battery charging and discharging processes. • Applying the Integer Zig-Zag (ZZI) method for linear approximations in bivariate losses • Evaluated model in a residential microgrid with solar, diesel, and Li-Ion battery • Analyzed triangulation strategies' impact on solution quality and computational load [ABSTRACT FROM AUTHOR]

This paper presents a novel microgrid secondary control method based on distributed sliding mode control, addressing the issue of reactive power sharing in islanded microgrids. Acknowledging the complications posed by feeder impedance mismatch, the traditional droop control mechanism fails to facilitate efficient reactive power sharing. Utilizing a distributed framework, this paper initially introduces a reactive power ratio observer, enabling the observation of global average reactive power without the need for precise reactive power calculation as required in a conventional centralized control setup. Subsequently, employing the devised reactive power ratio observer, sliding mode control is integrated to achieve effective reactive power sharing. Furthermore, this paper broadens its scope to encompass both reactive power sharing and voltage restoration, resulting in the design of a comprehensive controller. Notably, the proposed distributed sliding mode controller not only achieves accurate reactive power sharing but also exhibits significant resilience in the face of load disturbances. The simulation results conducted under various scenarios effectively validate the efficacy of the proposed distributed sliding mode control strategy. • A distributed sliding mode control for microgrid secondary voltage control. • Reactive power ratio observer for global reactive power calculation. • Comprehensively consider average voltage restoration and reactive power sharing. [ABSTRACT FROM AUTHOR]

• Provide an overview of NMG as a cyber-physical system and power balance methods. • Comprehensive review of hierarchical EMS for NMG and bidirectional PX scenarios. • Discuss the future hierarchical EMS trends for NMGs. A networked microgrid (NMG) is a novel cyber-physical system that provides power to urban and rural communities. The benefits of NMG that coupled with hierarchical energy management system (EMS) include increased renewable energy utilization, reliability, system efficiency, and flexibility in inter-microgrid (MG) power exchange (PX). Nevertheless, achieving secure and optimal NMG operation would require hierarchical EMS strategies that can manage uncertainties such as renewable generation fluctuations, load variation, energy prices, and flexible bidirectional PX. This paper outlines the NMG concept and various power balance methods. Subsequently, a comprehensive review of hierarchical EMS designs for NMG is presented. Four NMG models are introduced, and a comparison of various EMS strategies based on objectives, constraints, and optimization methods is also elaborated. Additionally, this paper addresses flexible bidirectional power flow between multiple MGs and the utility grid (UG) within three PX scenarios (MG-to-MG, MG-to-UG, and UG-to-MG). The advantages and challenges of hierarchical EMS for NMG with bidirectional power flow are also discussed considering grid stability, economic viability, and environmental impact. Finally, future research directions for enhancing the NMG model for optimal inter-MG PX are established. It highlights the efficient hierarchical EMS strategies and optimization algorithms for more reliable, affordable, and sustainable NMG operation. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper addresses a comprehensive review on various adaptive grid-following inverter control schemes developed for enhancing the power quality in renewable energy generation systems (REGS). The grid interfacing inverter with various adaptive control schemes has been well researched in recent years and their performance has been found with better characteristics compared to the conventional control schemes. Better fundamental component separation (FCS), dc offset rejection, grid synchronization, amplitude tracking, frequency tracking, phase angle estimation, and low complexity are the few silent features of the adaptive-based control schemes. This survey is very useful for researchers who are working on power quality, AC and DC Microgrid, grid-connected inverter control, multilevel inverter, power electronics, and other related research areas to select the suitable controller for grid interfacing inverter. This paper also focuses the power quality issues, basic standards, power quality monitoring schemes, and solutions. Moreover, power quality improvement techniques by using the power quality conditioners with adaptive control schemes are discussed in the paper. Finally, an extensive comparative study of the recently developed control techniques is performed to select a suitable controller in terms of better FCS, dc offset rejection, grid synchronization, amplitude tracking, frequency tracking, phase angle estimation, and low complexity for grid-following inverter in REGS applications. [ABSTRACT FROM AUTHOR]

Power system protection is crucial for maintaining the stability and reliability of the electricity grids and preventing costly disruptions. Conventional protection devices operate on pre-defined fixed settings and are no longer sufficient to ensure system stability and reliability in today's dynamic and complex electricity grids. With the rise of distributed renewable energy sources and the ability to reconfigure network topologies, an adaptive protection scheme has become necessary to quickly respond to changes in network configuration. This paper provides a state-of-the-art review of research efforts in the field of adaptive protection schemes, including the use of the IEC 61,850 protocol to incorporate automation opportunities. The IEC 61,850 protocol provides a standardized approach for communication between protection devices and the overall control system, enabling more efficient data sharing and reducing the need for manual intervention. This review paper is helpful for researchers, engineers, and policymakers involved in the development and implementation of adaptive protection schemes, enabling them to make informed decisions about the most effective strategies for ensuring the stability and reliability of modern power systems. [ABSTRACT FROM AUTHOR]

• Importance and challenges of relay coordination in Microgrid. • Overview of different adaptive schemes opted for relay coordination. • Different optimization techniques which have been used for the calculation of relay settings. • Evolvement of algorithms from conventional to Hybrid methods which combines two different metaheuristic methods to solve a complex, non- linear optimization problem in an efficient way for optimized relay coordination. • Future directions of research for further modifications possible in Algorithms are stated at the end. Concept of microgrids (MGs) have gained significant attention in order to enhance the resilience and efficiency of modern Power Systems. MG offers bi-directional power flow so an effective protection and control becomes a vital requirement to ensure the reliable operation of MGs. Relay coordination being an integral part of the protection system, plays a critical role in prevention of power disturbances and equipment damage due to the presence of bi-directional power flow. This review paper focuses on the optimization of relay coordination in MGs, and highlights the importance of adaptive and intelligent approaches involved for the efficacy of MG operation. This paper overviews different schemes used to adapt while determining the DOCRs settings with different contingencies considered. The paper depicts the key challenges associated with relay coordination in MGs; varying fault currents, and bidirectional power flows. To overcome these challenges, recent researches have explored advanced techniques that includes intelligent algorithms to operate on collected real-time data. Additionally, the impact of communication technologies for relay coordination in real-time has been discussed for Grid connected and Islanded mode of operation. This review covers a wide range of optimization methods such as; Traditional, Meta-Heuristic, and Hybrid algorithms, which allows adaptive and reliable protection schemes during different modes of MG operations. [ABSTRACT FROM AUTHOR]

• A new control method for DER is suggested. • The proposed control method balances the load between feeders. • DER connects to feeder through SST. • DER-controlled circuit shared the load between two feeders like ring connection. • Voltage profiles are improved. The multi-purpose use of distributed energy resources (DER) can bring a lot of income to its owners. For example, the load imbalance of the radial feeders in the distribution network is an old problem that occurs due to the simple structure of the radial topology and the unidirectional power flow in traditional networks. With emerging DERs and the development of power electronic technology, previous concepts are changing continuously. This paper aims to balance the load between two feeders whilst, it yields better voltage profiles and more appropriate utilization of distribution feeders. This paper proposes a new control method for DERs (including PV panels plus battery storage) that makes the radial system pretends a ring topology properties. It is done with the help of a solid-state transformer (SST). The relationships of the DER current controller are formulated based on current passes through the ring connection. Case studies are carried out on improved IEEE 33-node and 13-node systems with DERs and SSTs. The results show that the suggested control method can simulate the real ring topology and operating objective namely, load balancing is reached. [ABSTRACT FROM AUTHOR]

• Detailed modeling of CIGRE-14 bus standard test system along with inverter control scheme (with and without grid code) and protection system is done in PSCAD environment. • The performance of directional relaying schemes (32Q and 67pos,67neg,67zero) are evaluated in the presence of inverter-interfaced renewable energy resources. A comparative study on the performance of the relays is done in the presence of inverter-interfaced renewable energy resources for different fault types and fault resistances. • The interdependencies between the inverter control scheme used and performance of relaying schemes have been analyzed through mathematical analysis and circuit realization of the inverter-interfaced renewable energy resources. • Based on the mathematical analysis and circuit realization, the probable causes of relay failures in the presence of inverter-interfaced renewable energy resources are detailed. • The impact analysis of the dynamic response of the controller on the protective relay settings from the perspective of protection operation time-frame has been attempted. The potential impacts of the inverter-interfaced renewable energy resources (IIRERs) on the performance of sequence-based directional relaying schemes (SBDRS) have been investigated in this paper. The directional overcurrent relays such as 67 POS , 67 NEG , 67 ZERO and 32Q have been considered for the investigation. CIGRE-14 bus system with IIRERs along with detailed modeling of inverter control scheme (with and without grid codes) and SBDRS have been done in the PSCAD environment. The mathematical analysis and circuit realization of the IIRERs have been attempted in the paper. The exclusive fault characteristics exhibited by IIRERs cause the conventional SBDRS to mal-operate. Significant change in levels of sequence currents and angular relationships between sequence voltages and currents during faults contributes to relay's unpredictable behavior. The comparative study based on different fault types, fault resistances and interconnecting transformer connections have also been done. The study reveals the impact of non-generalized angular differences between positive sequence voltage and current at the inverter terminal on performance of 67 POS. It is found that 67 NEG and 32Q mal-operated for all types of unbalanced faults while the 67 ZERO can be utilized for grounded fault with delta-star grounded connection of interconnecting transformer. [ABSTRACT FROM AUTHOR]

• This paper introduces an advanced H∞ frequency control method for MGs, addressing uncertainties in secondary frequency control resources. By integrating parametric cyber uncertainties, it effectively counteracts unknown cyber-attack impacts, ensuring stable dynamic performance during cyber-attacks without requiring additional isolation or detection methods, simplifying MG control. • This study assesses cyber threats, incorporating physical uncertainties and RES/load fluctuations. It models key cyber threats (FDI, DoS, controller hijacking) and designs robust controls treating cyber-attacks and RES/load fluctuations as bounded uncertainties and disturbances. • The proposed H∞ control surpasses classical H∞ , optimal PI, and traditional frequency control in enhancing MG security, control, and functionality. It enables proactive control across diverse scenarios, ensuring cyber robustness, resilience, and uninterrupted performance against potential disruptions. • The application of the proposed robust control can be extended to the interconnected MG operations, significantly improving overall robust performance, even when the robust control is implemented in just one area during multiple cyber-attack events. A microgrid (MG) is a smart grid cyber-physical system, with component coordination relying on cyber resilience. Weak communications, protocols, and tools make the MG's secondary frequency control vulnerable to various cyber-attacks, posing new challenges and stability risks. In response to this challenge, this paper introduces the enhanced robust H ∞ technique considering the dynamic impacts of cyber-attacks on secondary frequency control to develop a secondary frequency control loop, improving the regulation performance and cyber resiliency of the MG frequency. The secondary control cyber-attack strategies mainly rely on false data injection (FDI), denial of service (DoS), and controller hijacking. These attack techniques are simultaneously considered in formulating the H∞ problem and control synthesis as unstructured parametric uncertainty, attenuating the concurrent cyber impacts. The study extends a load frequency control model to illustrate how cyber-attacks can be represented mathematically and physically in the MG. The results reveal that cyber-attacks affect secondary frequency control elements differently depending on the type of cyber threats used. By implementing an enhanced H∞ controller, the MG can effectively maintain stable frequency levels even when faced with malicious attacks and disruptions caused by renewable energy sources and loads. [ABSTRACT FROM AUTHOR]

• Study of PV power plant with quasi-Z-source cascaded H-bridge multilevel inverter under failure. • Control system to provide a suitable DC voltage at the input of the VSI and ensure the grid power delivery. • Control tested from simulation results under different operating conditions and HIL experimental results. • Correct response of the developed control strategy with failure in qZSI module. To ensure the reliability of microgrids (MGs), this paper presents a multi-fault tolerant control for a three-phase energy storage quasi-impedance multilevel-cascaded H-bridge inverter (ES-qZS-CHBMLI) with a photovoltaic (PV) power generation-based MG. In this paper, a battery energy storage system (BESS) is implemented to smooth out the PV generation fluctuations. In the event of a fault, most studies propose the injection of a fundamental zero sequence (FZS) to balance the system after a fault. However, the FZS based-method increases the modulation and it is limited by the converter operation range. The state-of-charge (SOC) unbalanced problem has traditionally been solved by balancing the BESSs as a single unit. This paper introduces an energy management system (EMS) based on the SOC proportional power distribution to balance the power injected into the grid. When one bridge faults, it is bypassed, and the remaining bridges in that phase change their operating conditions according to the references set by the EMS. Individual phase control allows multi-fault issues to be addressed. The simulation results of a three-phase grid-connected ES-qZS-CHBMLI PV-based MG implemented in MATLAB/Simulink validate the proposed multi-fault control and EMS. In addition, an experimental validation (based on OPAL RT4520 and dSPACE MicroLabBox units) confirm these results. [ABSTRACT FROM AUTHOR]

• The impedance models of power loop, voltage and current loop with different time scales are considered. • The generalized Nyquist curve criterion is applicable to multi-inverter systems. • The source-load division and stability of loads and multi converters are researched. • A novel strategy is proposed for high-frequency oscillation in multi-inverter systems. • The hardware in the loop experiment is designed for verification. In the context of the energy crisis and environmental pollution, microgrid technology has developed rapidly. There are grid-forming micro-sources and loads in the islanded microgrid, whose interaction can easily lead to the instability of the microgrid, and the inverter, as the power electronic interface device of the power generation unit, plays an important role in the reliable operation of the microgrid. The micro-sources, made up of three grid-forming inverters, are used as the research object in this paper. The small signal dq impedance modeling method is used to construct the full band impedance model based on the droop control inverter, whose model covers the power loop, voltage loop, and current loop at different time scales. A source-load partitioning method suitable for multi-inverter is designed. The relationship between parameter sensitivity and stability of the multi-inverter parallel operation system is analyzed from the perspective of impedance, and the parameter adjustment method for system stability is obtained. Based on the harmonic instability causes obtained by the impedance model, a novel impedance reshaping high-frequency oscillation suppression strategy is proposed that enhances the stability margin of microgrid islanding operations. Finally, the correctness of the theory in this paper is verified through simulation and experiments. [ABSTRACT FROM AUTHOR]

The large number of power electronic converters in hybrid DC ship microgrids (SMGs), with increasingly complex control strategies, has led to highly complicated stability analysis and parameter adjustments after system instability. In response to these challenges, this paper developed a system-level impedance model, including an asynchronous generator in the hybrid DC SMG. Subsequently, a variance-based Sobol parameter sensitivity analysis method was employed to quantitatively assess the impact of both system circuit parameters and control parameters on the system's stability, and the dominant parameters that exert the most significant influence on stability have been analyzed. Furthermore, the interaction among the dominant parameters is further discussed by varying these parameters and observing the evolution pattern of the system impedance ratio Nyquist curve, leading to the identification of 2-D and 3-D stable regions for the dominant parameters. Finally, the simulation results and hardware-in-the-loop experiments demonstrate that applying impedance modeling and stability analysis to the system and utilizing Sobol sensitivity analysis to optimize dominant parameters can expand the stability margin of the hybrid DC SMG. • A system-level impedance model of the hybrid DC ship microgrid, including an asynchronous generator, is established. • Using variance-based Sobol parameter sensitivity analysis method to quantify the influence of parameters on system stability. • The stable region of the system's dominant parameter operation is obtained through the evolution law of the impedance ratio Nyquist curve. • The parameter optimization steps in this paper can also be extended to other types of microgrids. [ABSTRACT FROM AUTHOR]

• Precise forecasts are vital for microgrid operation. • Optimal AI techniques affect microgrids. • AI methods comparison in microgrids. Forecasting renewable energy efficiency significantly impacts system management and operation because more precise forecasts mean reduced risk and improved stability and reliability of the network. There are several methods for forecasting and estimating energy production and demand. This paper discusses the significance of artificial neural network (ANN), machine learning (ML), and Deep Learning (DL) techniques in predicting renewable energy and load demand in various time horizons, including ultra-short-term, short-term, medium-term, and long-term. The purpose of this study is to comprehensively review the methodologies and applications that utilize the latest developments in ANN, ML, and DL for the purpose of forecasting in microgrids, with the aim of providing a systematic analysis. For this purpose, a comprehensive database from the Web of Science was selected to gather relevant research studies on the topic. This paper provides a comparison and evaluation of all three techniques for forecasting in microgrids using tables. The techniques mentioned here assist electrical engineers in becoming aware of the drawbacks and advantages of ANN, ML, and DL in both load demand and renewable energy forecasting in microgrids, enabling them to choose the best techniques for establishing a sustainable and resilient microgrid ecosystem. [ABSTRACT FROM AUTHOR]

• This paper proposes a statistical feature-based deep neural network (S-DNN) islanding detection technique and classification of non-islanding disturbances for hybrid systems with both synchronous and inverter-based distributed generators. • Roposed method has the capability of islanding detection and non-islanding disturbance classification with high accuracy, precision, recall and F_1 score. • Moreover, the proposed scheme can detect islanding events even if active and reactive power between load and generation is small or zero power mismatch conditions. • The proposed technique does not affect system reliability or power quality because there is no communication involved. • The proposed techniques does not required any threshold setting because of its adaptive nature. This paper proposes a statistical feature-based deep neural network (S-DNN) islanding detection technique and classification of non-islanding disturbances for hybrid systems with both synchronous and inverter-based distributed generators. The proposed technique extracts five statistical features from the point of common coupling (PCC)'s three-phase voltage. Several islanding and non-islanding scenarios for the test system were developed in the MATLAB environment. The S-DNN model is employed to effectively detect islanding and classify non-islanding disturbances using extracted features. In the detection phase of this study, the model is designed to identify events that occur in both islanded and non-islanding modes, providing the capability to accurately detect islanding conditions. In the classification phase, the model focuses specifically on non-islanding disturbances, such as line faults, load switching, and capacitor switching disturbances, enabling precise categorization of these distinct types of events. By leveraging the S-DNN model's capabilities, this study aims to enhance both islanding detection and non-islanding disturbance classification. By introducing white Gaussian noise with varying signal-to-noise ratios (30 dB and 40 dB) to the data, we aimed to evaluate the method's ability to handle and mitigate the effects of noisy and uncertain input signals. The inclusion of noise was intended to simulate realistic conditions where measurement inaccuracies or disturbances can be present. The decision tree (DT), multilayer perceptron (MLP), and support vector machine (SVM) are put up against the proposed technique, and it performs better than them in terms of accuracy, precision, recall, and F1 score. [ABSTRACT FROM AUTHOR]

• Impact of demand response (DR) strategy on the optimal design of microgrid (MG). • Techno-economic feasibility assessment of a grid-tied MG considering DR strategy. • Proposing renewable Generation-based dynamic pricing to optimize MG configuration. • Employing the dandelion algorithm to solve the sizing problem of MG optimally. Integrating microgrids into the existing power system increases utility grid reliability and efficiency. Optimal sizing and configuration of Microgrid (MG) components are essential at the design stage for minimizing the overall cost and emissions of the MG. This paper presents a novel mathematical model for optimizing the configuration and operation of a grid-connected microgrid exploiting Demand-Side Management (DSM). This paper studies the impact of Demand Response (DR)-based DSM on optimal MG design from the customers' and utility's perspectives, considering both economic and technical performance metrics. A comparative performance study of six DR programs is investigated in order to verify the effectiveness of the proposed Renewable Generation-based Dynamic Pricing (RGDP)-based DR. In this paper, the sizing problem of MG is formulated as a bi-objective optimization in order to fulfil two objective functions: minimizing the total annual cost and minimizing life cycle emissions. An advanced evolutionary algorithm named the Dandelion Algorithm is utilized in order to solve the complex and constrained nonlinear optimization problem. The results demonstrate that considering RGDP-based DR in the MG sizing problem reduces the installation and operating costs of the MG without load shedding. The proposed DR strategy satisfies the customers' needs with high efficiency and low cost. [ABSTRACT FROM AUTHOR]

The 2050 net-zero emission goal has pushed the global transition of power systems from fuel-powered to renewable-powered. Solar photovoltaic (PV) power is anticipated to contribute significantly to renewable generation. However, the intermittent nature of solar power hinders the growth of PV capacity during this global transition. Integrating PV into power systems usually requires abundant support resources. Typical facilities include dispatchable fuel-based generators and energy storage systems. However, newer PV systems should not assume sufficient support from fuel-based generators to facilitate the net-zero transition. Although the option to use energy storage, especially batteries, to replace fuel-based generators exists, scaling the capacity can have affordability issues. Despite the challenges, PV penetration is growing and needs to grow further. Overcoming the challenges means eliminating intermittency using minimum storage and negligible fuel. The solution is effectively converting PV to a dispatchable source. The research about forecasting and controlling PV power has centered on reducing the impact of PV power intermittency. However, the need for developing dispatchability out of PV power has yet to be sufficiently addressed. This paper is conducted to identify the research directions needed to facilitate dispatchable PV and, thus, global high PV penetration. To describe the dispatchability of PV power, uncertainty, variability, and flexibility are chosen as descriptors. As the PV power gains flexibility, uncertainty and variability reduce for a PV system. Eventually, PV power can become flexible enough to be dispatchable. Moreover, the support services needed by PV power can be undertaken mainly by itself, thus enabling high penetration. From the literature, PV forecasting, energy storage, and inverter-controlled curtailment are identified to be cornerstones of dispatchable PV power. Power system dispatch algorithms have used PV forecasts to compensate for uncertainty efficiently. Storage, especially batteries, and PV inverters, have been used to control PV power output against undesirable variation. In this review paper, the practice of utilizing PV in power systems is uniquely divided into four categories according to the descriptors. Unlike the convention that curtailment should be avoided, this review emphasizes the practicality of overbuilding PV capacity and curtailing PV power. It ultimately will be possible to effectively eliminate uncertainty and variability as the three cornerstone technologies evolve. By presenting the road map for reducing the impact of PV power intermittency, this paper elaborates on the motivation for researching dispatchable PV. From the past and low penetration to the contemporary situation, PV power evolved from being unconstrained to forecasted and constrained. Based on the literature about forecasting, energy storage, and curtailment, this paper concludes that dispatchable PV power will be needed and is achievable. • A road map for the development of PV forecasting and PV control. • Advocates exploiting curtailment with solar forecast for error compensation. • A timely review of the development and application of PV systems. [ABSTRACT FROM AUTHOR]

This paper focuses on the issue of false data injection attack (FDIA) of controllers in AC microgrid, and proposes a distributed adaptive secondary controller for AC microgrid to achieve the control objective of restoring the rated frequency and voltage when the controllers are subjected to FDIA. Firstly, this paper analyzes the impact of constant FDIA on AC microgrid. Then, a distributed adaptive secondary controller is designed based on the adaptive compensation mechanism to compensate for the attack and eliminate the adverse effects of FDIA on the system. Further, the stability analysis for the designed secondary controller using Lyapunov theory proves that the control system is global asymptotically stable. Finally, the effectiveness of the proposed distributed adaptive secondary control method is demonstrated both in the islanded AC microgrid model built by MATLAB/Simulink and in the StarSim hardware-in-the-loop simulation. • An improved attack defense strategy. • A stronger ability for dealing with more attacked DGs. • A complete FDIA effect elimination. [ABSTRACT FROM AUTHOR]

This paper proposes a cooperative approach aimed at distributed energy resources sizing in a renewable energy community, with considerations of the community's optimal operation, impact on the electrical grid and an allocation of the benefits to its members. To this purpose, multiple investment modes are evaluated via a two-step procedure. In the first step, the size of renewable energy sources is determined by solving an optimization problem that maximizes community welfare, considering network and investments. In the second step, an optimization problem maximizing additional community member profit with price regularization is solved. This step shares benefits among community members. The potential of the proposed procedure is illustrated using a benchmark Dickert-LV network. This is a full y cooperative framework where the community operator is ensuring adequate grid operation, operational planning and sizing of new investments. • Energy communities are a good enabler for energy transition and prosumer empowerment. • The incentive for DER investment that they provide needs quantification. • Intra-community exchanges and co-investments have effects on the grid. • What are the benefits of an energy communities with and without co-investments? • How could these benefits and return on investments be computed? [ABSTRACT FROM AUTHOR]

• Considering the fault indicators allocation into the formulation of a fault locator • Utilizing multiverse optimization algorithm to allocate fault indicators. • Eliminating of the need for directional fault indicators installation, • Considering critical operational characteristics of the ADN and MG Fault location (FL) is one of the main challenges in Advanced Distribution Automation (ADA) of Active Distribution Networks (ADN). One of the commonly used strategies by utilities to deal with this challenge is the use of Fault Indicators (FIs), which indicate to the operator the path taken by the fault current. However, a good performance of this scheme depends on the number of installed devices, a high number of them could cause a high cost for the utility investment planning. In this context, this paper presents an artificial intelligence-based fault location strategy that determines the number and location of FI into ADN to maximize performance in fault section estimation. To achieve this objective, the ADN is divided into sections, and the FL problem is modeled as a classification problem to train an Artificial Neural Network (ANN). To determine the number of FIs to be installed and their location, the strategy uses the three-phase current magnitudes measured by the FI as features for an ANN model. Also, the strategy uses a feature selection and tuning scheme based on a multiverse optimization algorithm (MOA) to identify the features that maximize the accuracy of the ANN model. The strategy was validated on the IEEE123-node test feeder. The results showed accuracy close to 99.4 % with a reduction of 40 % of the number of FIs when compared with other method. The strategy shows its simplicity and promising prospects to apply it in the utility's investment planning. [ABSTRACT FROM AUTHOR]

This paper proposes an uncertainty modeling method for the aggregated power flexibility of DERs. Basically, both outer and inner approximated power-energy boundary models are utilized to describe the aggregated flexibility of controllable DERs. These power and energy boundary parameters are uncertain because the availability of controllable devices, such as electric vehicles and thermostatically controlled loads, cannot be precisely predicted. The optimal operation problem of the aggregator is thus formulated as chance-constrained programming (CCP). Then, a flexibility envelope searching algorithm based on the ALSO-X+ method is proposed to solve the CCP, the result of which is a conservative approximation of the original CCP but not as conservative as the Conditional Value-at-Risk approximation. After optimizing the aggregated power of the group of DERs, the decision at the aggregator level is disaggregated into the flexibility regions of individual DERs. Finally, the numerical test demonstrates the effectiveness and robustness of the proposed method. • Uncertainty modeling of the aggregated flexibility of DERs. • Chance constraint approximation based on the ALSO-X+ approach. • Comparative analysis of costs, risk levels, and feasibility with Conditional Value at Risk. • Comparison between the outer and inner approximated flexibility aggregation models. [ABSTRACT FROM AUTHOR]

As the penetration of inverter-based distributed generations into microgrids continues to rise, the significance of power electronic inverters in modern power systems becomes increasingly pronounced. They are designed to have fault ride-through capabilities, enabling them to sustain operation even during and after fault conditions. This paper presents a novel voltage compensation strategy based on the line impedances addressing both positive and negative-sequence aspects, for a three-phase three-wire inverter deployed to regulate the low-voltage network during unsymmetrical faults, thereby preserving voltage stability. The control strategy is carried out in a synchronous reference frame (dq) to govern the positive and negative-sequence voltages and currents of the inverter. By synthesizing AC currents, the inverter restores the positive-sequence voltage to its rated value while mitigating negative-sequence voltage at the point of common coupling arising from unsymmetrical faults. Through MATLAB/Simulink, are investigated three unsymmetrical fault scenarios (single line-to-ground, line-to-line, and double line-to-ground faults) within the low-voltage distribution network of the 18-bus European Cigré, incorporating three inverters equipped with the proposed voltage support capability. The results confirm that inverter-interfaced distributed generators with local voltage support can improve the system's fault ride-through capability by reducing voltage drops and unbalances. • Voltage resilience in the face of short-circuit challenges. • Balancing voltage fluctuations during grid faults. • Grid-supporting inverters optimize fault response. [ABSTRACT FROM AUTHOR]

In recent years, there has been an exploration of innovative electric grid concepts centered around power routers, devices capable of controlling power flows as desired. One of which is the Power Router Grid, a novel high-controllable network design fully based on power routers. Its ability to arbitrarily change power flows inside controllable lines raises the challenge of determining the optimal operation within such systems. This paper aims to push further the analysis of the operation and benefits of such networks by proposing a novel optimization model tailored for power router grids based on the most recent literature for the convexification of optimal power flows. Moreover, it demonstrated that radial-based models can be expanded for grids meshed through power routers. The model presented is also convex in the form of a second-order cone, ensuring a global optimum for diverse grid configurations. It has been implemented in Python using the PYOMO modeling language and applied to three case studies investigating the effects of power router operation modes on the grid's optimal operation and associated costs. Results show that the definition of the power router grid design and the ports operation mode must be carefully decided when demand uncertainty of over 25% is taken into consideration. Moreover, controlling power flow near lines of higher impedance can lead up to a 21% increase in line losses. • A novel and linearized optimal power flow model for electric grids based on power routers. • Application of second-order cone convexification for grids meshed through power routers. • Analysis of the effects of the layout and power controllability in line losses inside the power router grid. • Implementation of the optimization model in pyomo. [ABSTRACT FROM AUTHOR]

• Wideband harmonic mitigation. • No need to extract harmonic components. • Simple controller implementation. • Can be applied to other microgrid control, such as Droop control. In virtual synchronous generator (VSG)-based islanded microgrid, voltage harmonics induced by nonlinear loads seriously degrade system power quality. Existing harmonic mitigation controllers mainly rely on the extracted harmonic components to control, and generally have the weakness that can only mitigate harmonics with known frequencies. To better improve the power quality of the islanded microgrid, a wideband harmonic self-mitigation controller (WHSMC) is proposed in this paper, which can effectively mitigate wideband voltage harmonics above the fundamental frequency without extracting harmonics. Firstly, based on the impedance method, the reason why nonlinear loads will cause voltage harmonics in the islanded microgrid is analyzed in detail. Secondly, by establishing the impedance model of VSG with the proposed WHSMC, the mechanism how the proposed WHSMC mitigates voltage harmonics without knowing the harmonic frequency in advance is theoretically revealed. Finally, the effectiveness of the proposed WHSMC is verified through simulation and experimental results. The experiments indicate that the voltage total harmonic distortion (THD) can decrease from 7.02 % to 3.41 % under nonlinear load disturbance and from 8.27 % to 3.99 % under pulse load disturbance. [Display omitted] [ABSTRACT FROM AUTHOR]

• The paper makes a significant contribution by conducting an in-depth and comprehensive literature review, synthesizing the current body of research on methods for detecting faults in LVDC-MGs. • The investigation entails conducting a detailed simulation of LVDC-MGs with diverse fault scenarios, configurations, and operational conditions that are systematically considered and analyzed. • The major contribution lies in the proposal of two novel fault detection techniques: K-CUSUM and K-DCUSUM. • The study adds significant value by conducting tests with different fault resistances, DG penetration, and introduction of noise. The energy industry is rapidly shifting from conventional to smart grid systems, involving advancements in microgrids and power management systems. However, achieving desired outcomes with the existing grid setup poses significant challenges. To address the above issues, adopting a Low Voltage Direct Current (LVDC) distribution system provides successful operational advantages. The primary objective of this work is to improve the system's security by developing a more resilient fault detection scheme. The presented work has proposed a Kernel-based Cumulative Sum (K-CUSUM) and Kernel-based Differential Cumulative Sum (K-DCUSUM) technique which is designed to identify changes in data under fewer assumptions. Instead of using the classical Maximum Mean Discrepancy (MMD) technique, the K-CUSUM and K-DCUSUM methods use a non-parametric MMD testing framework to evaluate incoming data by comparing it to reference distribution samples. Further, a comprehensive analysis is undertaken on an LVDC test system, considering fault scenarios involving pole-to-pole and pole-to-ground configurations. This research encompassed the determination of fault location, evaluation of fault resistance, examination of noise introduction, and an exploration of the influence of photovoltaic (PV) penetration. Moreover, the proposed approach is tested for a standard LVDC Microgrid. The results are compared with other contemporary techniques and recent literature. [ABSTRACT FROM AUTHOR]

This paper presents an optimal resiliency-oriented operational-planning method. The method aims to enhance the robustness of the active distribution system (ADS) in response to extreme, high-impact, low-probability events through the integration of renewable energy sources. The authors employ a mixture model to establish a probabilistic framework that effectively captures the inherent randomness of weather-related variables. This framework is based on k-means clustering and Latin hypercube sampling methods serving to simplify the complexity of the weather related ambiguity. The proposed objective function strives to minimize the overall operation-planning costs, encompassing the operational, investment, and operation and maintenance costs of the ADS. Considering the mixture model, a refined version of Benders decomposition is devised to accommodate the inherent uncertainty in the solution methodology. The proposed model is formulated from the perspective of the ADS operator, contingent upon the availability of historical wind speed and solar radiation data specific to the simulated network site. • Optimizing a resiliency-oriented operational-planning model for robust active distribution. • Modeling the effect of high impact low probability events on the supply side. • Using a mixture model with k-means clustering and Latin hypercube sampling for probabilistic weather. • Solving the problem with a modified version of Benders decomposition. [ABSTRACT FROM AUTHOR]

• In this paper, the effect of mismatched line impedances in the system on the precise current distribution among ESUs is considered. A current compensation term is introduced into the droop coefficient. By adjusting the weight of the compensation term, precise current distribution among the energy storage units is achieved on the basis of rapid equilibrium. • The control strategy proposed achieves precise current distribution by altering the droop coefficient. Compared to traditional current distribution strategies, the use of proportional-integral controllers can be reduced. In the presented study, a novel droop control method has been developed for distributed energy storage systems, which ensures the precision of current sharing and the balance of state of charge (SOC). A strategy that has been newly introduced facilitates a logical allocation of SOC and ensures precise sharing of current in autonomous island DC microgrids. Within the framework of droop control, a linkage is established between the SOC value and the converter's output current. By mitigating the impact of disparate line impedance on SOC equilibrium, the service life of energy storage units (ESUs) is significantly improved. The droop coefficient has been augmented with the inclusion of a current compensation term. It has been ascertained that the ratio of SOC to output current within the droop coefficient can be determined independently, utilizing the state information of SOC. By incorporating accurate current sharing that considers SOC, ESUs with higher SOC levels output larger currents, while those with lower SOC levels output smaller currents. A newly devised control approach is distinguished by its reliance on low-bandwidth communication. This method ensures the stabilization of the DC bus voltage, maintaining it at a pre-set level, achieved through the application of a voltage restoration technique. [ABSTRACT FROM AUTHOR]

• Event-triggered secondary controllers under multiple delays are discussed. • Compared with traditional event-triggered and dynamic event-triggered, the proposed scheme has high accuracy in tracking voltage and frequency setpoints, and can effectively reduce the communication burden and maintain the system performance. • The proposed controller is robust to external disturbance and multi-delay. The stability of the proposed control strategy is proved using the lyapunov method. In this paper, an adaptive event-triggered H ∞ consensus control scheme is proposed for the secondary layer of AC MGs. The controller design problem of topological communication network with external disturbance, multiple delay, and communication burden is considered. Therefore, using the Lyapunov-Krasovskii theory, we obtain sufficient conditions for the robust consensus convergence of multi-agents under event-triggered and multiple time delays. Because traditional event-triggered often use fixed thresholds, it is challenging to balance reducing the communication burden and maintaining excellent system performance. Therefore, we design an adaptive event-triggered method that adaptively adjusts the trigger threshold according to the consistency error. Finally, a simulation system is established. The proposed control strategy has been validated through simulation results. [ABSTRACT FROM AUTHOR]

• The complex magnitude-phase plane (MPP) of the fault detection index (FDI), is verified as a key indicator for fault detection in microgrid. • The magnitude and angle of the FDI is used to develope the proposed protective relaying logic. • The relaying scheme is extensively evaluated for variations in fault types, fault locations, fault resistances and distributed generation (DG) penetrations in grid-connected (GC) and non-grid-connected (NGC) modes of operation. • The algorithm is initially tested on MATLAB/Simulink platform and validated on Typhoon HIL platform to assess the real-time performance. • The test results and response time show promising performance in detecting faults. The paper introduces a novel protective relaying method using symmetrical components of current to detect asymmetrical faults in microgrid. This approach is focused on utilizing the complex magnitude-phase plane (MPP) of the fault detection index (FDI), which is computed using the positive and negative sequence components of the current signal retrieved at one end of the faulty line. The MPP obtained from the settling values of the FDI's magnitude (MFDI) and FDI's angle (AFDI) after the fault inception, is considered as the key indicator for fault detection. The scheme is comprehensively evaluated for a wide range of fault situations including variations in fault types, fault locations, fault resistances and DG penetrations in grid-connected (GC) and non-grid-connected (NGC) modes of operation. Several critical no fault cases are also tested to show the efficacy of the proposed logic for false operation. The fault study is conducted extensively on a modified low voltage standard Consortium for Electric Reliability Technology Solutions (CERTS) microgrid and a standard IEEE-34 bus distribution system including DGs. Furthermore, the proposed FDI-based scheme is tested on MATLAB/Simulink platform and validated on Typhoon HIL platform to assess the real-time performance. The test results show that this FDI-based scheme using the MPP concept can be a potent solution for the protection of microgrid. [ABSTRACT FROM AUTHOR]

• A two-stage mixed integer second-order cone programming (MISOCP) method based on radial basis function stochastic response surface method (RBF-SRSM) is proposed, which takes into account the impact of the randomness of source and loads on the security of the distribution network. • A RBF-SRSM based stochastic optimization method for high dimensional configuration points is proposed. • The proposed model can ensure economic and environmental protection of dispatch strategy while preventing voltage overruns. • The RBF-SRSM based scheme is more efficient than SRSM and can be used to solve the larger uncertainty problem of future distribution network. As the high proportion of distributed generation (DG) and diversification of loads increase, the distribution network faces increasingly greater impact. To address the high-dimensional stochastic problems arising from the multi-dimensional uncertainty of power source and load, this paper proposes a two-stage optimization scheduling scheme for AC distribution networks based on RBF-stochastic response surface method (RBF-SRSM). This scheme takes into account economy, environmental protection and safety, and consists of day-ahead and intra-day stages. The day-ahead decision scheduling is based on an optimal low-carbon economy operation plan, while the intra-day reactive power optimization is achieved by converting nonlinear integral indicators into discrete linear indicators through probabilistic power flow calculation and the first moment derivation principle inspired by SRSM. The mixed integer second-order cone programming (MISOCP) method is used to solve the dispatching plan, and the results suggest that the proposed method is more efficient than the SRSM. [ABSTRACT FROM AUTHOR]

A power management strategy for balancing three single-phase sections in a three phase residential microgrids is presented in this paper. The scheme makes use of the previously developed intra- and inter-phase power management techniques to transfer power from the power surplus phase to power deficient ones to achieve dynamic phase balance. This scheme is particularly useful in situations where phase-dependent generation, single-phase loads, and home-based battery storage are involved, such as roof-top PVs, chargers for electric vehicles, and battery storage units. This scheme also opens up potential avenues for accommodating more advanced energy management programs among phases, such as peak shaving in different phases, and load shifting, to minimize potential risks of overloading substation transformers or forced load shedding due to power deficiency in one of the phases. Seven operating scenarios have been identified. Detailed power transfer models are developed and simulated in PSCAD/EMTDC to validate the proposed strategy. Experimental validation has also been carried out on a laboratory-scaled system involving a back-to-back converter. • A control strategy is introduced for unbalanced low voltage distribution systems. • Simulations are performed in PSCAD for various cases. • Experimental validation shows the effectiveness of the proposed EMS strategy. • The control strategy is effective in reducing the voltage unbalance. [ABSTRACT FROM AUTHOR]

Highlights • A transient stability assessment index based on SVM model is defined and its sensitivities are used to select control generators and calculate the control amount. • A hybrid TSA method combining SVM and T-D simulation is presented, which increases the accuracy rates from 99.0%, 99.3% to 100% for the example system. • The features of the SVM model used in TSC are the same as in TSA that include non-control variables, which will improve the accuracy of TSA and sensitivities. Abstract This paper presents a support vector machine (SVM)-based method for preventive transient stability control (TSC) of power systems. The features of the SVM model used in TSC are the same as in transient stability assessment (TSA). The features include non-control variables so as to improve the accuracy of TSA and sensitivities. A hybrid method combining SVM and time-domain simulation is also proposed to increase the TSA accuracy. First, this paper defines a transient stability assessment index based on SVM model. Second, the sensitivities of the SVM-based transient stability assessment index with respect to control variables (generator active power) are calculated and ranked to select control generators from them. Then, the power shifting amount of all the control generators and balance generators is calculated and the corresponding control scheme is verified by the hybrid TSA method. If generation redispatching measures are invalid, then load shedding measures are used at the same time. Finally, comprehensive studies are conducted on the WECC 9-bus system and a certain provincial 2036-bus system in China. The results reveal that the proposed hybrid TSA method increases the classification accuracy rates from 99.0%, 99.3% to 100% for the certain provincial 2036-bus system, and effective control measures are obtained with the proposed SVM-based TSC method for both systems. [ABSTRACT FROM AUTHOR]

Highlights • An enhanced SOGI-FLL scheme suitable for DC-offset rejection is proposed. • Good DC-offset and sub-harmonics rejection capabilities. • Ripples cancelation of the estimated frequency and phase error. • A comparative study of the proposed with two other schemes is reported. • Effectiveness and robustness are tested against various disturbances. Abstract For the proper operation of a microgrid, an accurate estimation of the grid parameters such as phase angle, operating frequency and amplitude under various disturbances is of prime interest. In this paper, an enhanced second-order generalized integrator-based frequency-locked loop (ESOGI-FLL) intended for DC-offset rejection in both grid-connected and islanded operation of a single-phase voltage source inverter (VSI) is presented. The main contribution in this work is the ability of the proposed scheme to remove the overall uninspected distortion in the orthogonal component and oscillations that affect the estimated frequency and phase caused mainly by the inherent DC-offset in the input voltage. Unlike the most popular PLLs dealing with DC-offset rejection, the proposed scheme has a great advantage in term of structure complexity and computational time. Numerical simulations as well as practical assessments are carried out to highlight the effectiveness and robustness of the proposed scheme in term of parameters estimation of highly shifted input voltage. In addition, the proposed scheme is tested against corrupted input voltage such as frequency change, phase jump and voltage sags. The paper also reports a detailed comparative study with conventional SOGI-FLL and third-order generalized integrator based FLL. The obtained results have shown best performances of the proposed ESOGI-FLL in term of DC-offset rejection in the orthogonal component, ripples elimination in the estimated frequency and less computational time. [ABSTRACT FROM AUTHOR]

Highlights • A new hierarchical optimization framework for optimal operation of multiMGs is presented. • MG operator's decisions and up-stream network operator's decision are considered. • Impact of up-stream network operator's decision on multiMGs optimization is illustrated. • Virtues of utilizing TOU demand response programs and price elastic loads are delineated. • Risk management of multiMGs for participating in the Real-Time market is discussed. Abstract This paper proposes a framework for the optimal operation of multi Micro Grids (multiMGs) based on Hybrid Stochastic/Robust optimization. MultiMGs with various characteristics are considered in this study. They are connected to different buses of their Up-Stream-Network (USN). Day-Ahead (DA) and Real-Time (RT) markets are contemplated. The proposed optimization structure in this paper is a bi-level one since both MGs operators' and USN operator's decisions are considered in the proposed model. The advantages of using time-of-use demand response programs on the optimal operation of USN in the presence of multiMGs are investigated. The uncertainty of different components, including wind units, photovoltaic units, plug-in electric vehicles, and DA market price is captured by using stochastic programming. In addition, robust programming is utilized for contemplating the uncertainty of the RT market price. Furthermore, the grid-connected and island modes of MGs' operation are investigated in this paper, discussing also the virtues of utilizing multiMGs over single MG. Finally, IEEE 18-bus and 30-bus test systems are considered for MGs and USN networks respectively to scrutinize the simulation results. [ABSTRACT FROM AUTHOR]

Highlights • DC distribution systems may suffer problems in protection selectivity. • Voltage source converter (VSC) protection can be obtained using a suitable control. • Coordination between VSC, dc feeders protections and storage devices is presented. • This methodology, experimentally validated, ensures selectivity and security. Abstract Over the recent years, low-voltage dc (LVDC) distribution systems have become increasingly interesting. One of the main problems in their diffusion is the realization of reliable protection systems ensuring selectivity and security to the loads. Several solutions to this problem are studied in the current literature and are mainly focused on the design and integration of new protection devices. Nevertheless, for some faults, it is possible to use traditional protection devices if proper control strategies are used on the power converters. In this paper, the ground fault of one of the dc poles is considered for grids operated with the neutral ground connected on the ac side and isolated on the dc side. In these conditions, if, as usual, a voltage source converter (VSC) is used as an interface between ac and dc grids, the IGBTs of the VSC are capable neither of limiting nor of blocking the fault current. In this paper, the integration of a proper control strategy implemented on the VSC with the protection devices is proposed to allow the system to interrupt, clearing the fault, saving the power converter. The proposed strategy ensures selectivity and security to the loads because it implies the interruption only of the faulty feeder of the dc microgrid. In this paper, the proposed strategy is tested by means of numerical simulations and experimental results, thus proving its good performances. [ABSTRACT FROM AUTHOR]

The importance of microgrids (MGs) lies in their capacity to enhance energy reliability, integrate renewable resources, and bolster resilience, yet their optimal design and sizing pose intricate challenges in balancing investment and operational cost while dispatching the MG equipment efficiently. This paper presents the optimal MG design problem formulated as an integer linear program (ILP) aimed at minimizing total investment and operational cost of MG as well as optimal hourly dispatch of MG asset over the project lifetime. Furthermore, a comprehensive analysis of the fuel procurement cost and the impact of ESS technical parameters, such as depth of discharge (Dod), ESS lifetime, and battery C-rate, on the optimal MG design, ESS lifetime and relevant costs is presented in this work for a MG operating in islanded and grid-connected modes. The simulation results demonstrate that the optimal design of a MG with the maximum load demand of 300 kW operating in the grid-connected mode can save about 28 k$ equivalent to 14% in total annual cost compared with the islanded mode operation thanks to the flexibility provided by the utility purchases and efficient MG equipment sizing. This study's unique contributions provide significant insights into the practical implications of MG design optimization, potentially influencing regulatory policies and business strategies. • Optimal microgrid design and equipment dispatch formulated as an integer linear programming. • Minimizing CapEx, O&M, and fuel procurement through optimal microgrid sizing. • Sensitivity analysis of individual equipment investment cost on the microgrid sizing. • Comprehensive analysis of ESS parameters on the microgrid design and battery lifetime. • Analysis of fuel procurement cost impact on the optimal microgrid design. [ABSTRACT FROM AUTHOR]

This paper proposes adaptive parameter tuning strategy for a virtual-synchronous generator (VSG) during islanding conditions to improve frequency oscillations occurring due to uncertainties in load and solar photovoltaic (PV) output. Accordingly, an adaptive two-level optimization model has been developed for optimal tuning of VSG parameters. It provides dynamic virtual inertia value to VSG by maintaining rate-of-change-of-frequency (RoCoF) within prescribed limits under disturbance. The first level calculates the initial value of VSG parameters using robust control considering day-ahead operation schedules and uncertainty information. During intra-day operation stage on the following day, as soon as islanding is detected, the VSG is operated with robust values of the parameters computed day ahead at the first level. Furthermore, during islanded operation, second level utilizes initial values from first level and determines expectation values of short-leading-time predictions of PV output and load, and performs an adaptive stochastic optimization of VSG parameters in intervals of 5 min. Extensive simulations have been performed to evaluate the performance of proposed adaptive parameters tuning strategy on modified Cigre European LV network. Furthermore, effectiveness of proposed control approach has been validated on laboratory-scale hardware experimental setup under uncertain environments and cyber-attack. Results reveal improved performance of adaptive VSG in regulating network frequency in presence of system uncertainties. • Development of adaptive parameters tuning strategy using bi-level optimization for optimal tuning of VSG in islanding operation to avoid undesirable triggering of the protection system for low-inertia microgrids. • The developed bi-level adaptive optimization framework evaluates robust VSG parameters day-ahead, followed by a stochastic programming model for adaptive multi-objective optimization of VSG parameters to counteract the effects of system uncertainties in shorter timescales upon islanding. • The performance of the proposed adaptive parameters tuning strategy has been evaluated through extensive simulations on a modified cigre European LV network. • Effectiveness of the proposed adaptive parameters tuning strategy has been validated under an uncertain environment and cyber-attack. [ABSTRACT FROM AUTHOR]

• A cooperative control for the online energy management of a microgrid. • The methodology adopts the Lyapunov theorem encompassing the sensitivity theory. • It aims to ensure real-time power balance within the MG at minimal operating cost. • Simulations demonstrated the self-adaptability of the proposed controller. This paper develops a cooperative control methodology for the online energy management of grid-connected microgrids. The main aim of this methodology is to actively manage the active power outputs of all dispatchable energy sources available within the microgrid as well as the power exchanged with the utility grid so as to match the total load demand at the minimum operating cost. This implies to solve a constrained multi-objective dynamic optimization problem aimed at minimizing the total microgrid operating costs and ensuring the real-time balance within the microgrid in compliance with its technical-operational constraints. Lyapunov's theorem using sensitivity theory is adopted to solve this optimization. To test the performances of the proposed control methodology, several computer simulations corresponding to different operating scenarios have been conducted on the PrInCE Lab experimental microgrid built at the Polytechnic University of Bari. [Display omitted] [ABSTRACT FROM AUTHOR]

To mitigate the vulnerability of distribution grids to severe weather events, some electric utilities use preemptive de-energization as the primary line of defense, causing significant power outages. In such instances, networked microgrids could improve resiliency and maximize load delivery, though the modeling of three-phase unbalanced network physics and computational complexity pose challenges. These challenges are further exacerbated by an increased penetration of uncertain loads. In this paper, we present a two-stage mixed-integer robust optimization problem that configures and operates networked microgrids, and is guaranteed to be robust and feasible to all realizations of loads within a specified uncertainty set, while maximizing load delivery. To solve this problem, we propose a cutting-plane algorithm, with convergence guarantees, which approximates a convex recourse function with sub-gradient cuts. Finally, we provide a detailed case study on the IEEE 37-bus test system to demonstrate the economic benefits of networking microgrids to maximize uncertain-load delivery. • Formulated robust reconfiguration and operation of microgrids with load uncertainty. • Derived generalized constraints to ensure islands contain a voltage source. • Developed tractable reformulation and a cutting-plane algorithm to solve it. • Leveraged networked microgrids for distribution grid resilience under contingencies. • Case study ensured robust feasibility of proposed methods across uncertainty levels. [ABSTRACT FROM AUTHOR]

This paper presents a high-performance control strategy to support an optimised transient performance for a hybrid AC/DC microgrid system based on an improved virtual synchronous generator (VSG). The standard VSG is modified and an improved control strategy is developed. A pre-synchronization controller is embedded within the improved VSG controller for grid-connection use. In addition, this paper builds the small-signal model for the improved VSG controller in order to analyse the system’s stability. A controller for the battery energy storage system is developed in order to assist the power output of the hybrid microgrid. The microgrid system is designed in a MATLAB/SIMULINK simulation environment based on the under-construction hybrid AC/DC microgrid system at Griffith University, Australia. A comparative study of droop control, conventional VSG control, and the improved VSG control is carried out under different possible transient cases. The pre-synchronization method is also tested. The simulation results show that the improved VSG control strategy is evidently able to ensure smooth variations in frequency, voltage and active power during transient cases. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of an innovative standalone AC/DC microgrid configuration with focus on electricity water nexus. The proposed configuration includes photovoltaic (PV) generator, hybrid fuel cell system, storage system, and both DC and AC loads. One of the most important advantages of this microgrid is waste water treatment which enhances the microgrid resilience during natural/climate disasters or in remote areas. Purified water is produced by Microbial Electrolysis Cell (MEC) which also generate cheap and sustainable Hydrogen as a viable fuel for Proton Exchange Membrane Fuel Cell (PEM fuel cell) with considerable power density. A dynamic control strategy is also suggested to ensure optimal power management during microgrid stand-alone operation. To verify the proposed configuration and control strategy, the AC/DC microgrid is modeled and simulated in MATLAB/Simulink and the system power balance behavior during different scenarios is evaluated. A real-time Hardware-In-The-Loop (HIL) based experimental setup with physical power component and LabVIEW-based control system is designed and tested with the same scenarios to confirm the simulation results. By considering the natural/climate disasters in the last decades and the availability of the vast waste water supplies in Southeast Texas, which is the target area of this paper, the proposed AC/DC microgrid is a viable choice to increase the power system resilience. [ABSTRACT FROM AUTHOR]

• The proposed data-driven control method eliminates the need for an accurate offline system model. • The presented control method incorporates a regularization term and introduces slack variables to effectively handle uncertainties and disturbances. • The FADMM method is utilized to enhance privacy and scalability by decomposing the centralized optimization problem into several sub-problems. The networked microgrid system (NMG) has become an effective alternative for integrating various types of distributed energy resources (DERs). However, because of the increasing share of DERs and high R/X ratio in the system, the uncertainty and variability of DERs' power generation may cause significant voltage violations in the system. To address these issues, this paper introduces a novel distributed data-driven voltage control strategy based on data-enabled predictive control (DeePC) to address voltage violations problems in the NMG. The DeePC algorithm uses only historical system trajectories, eliminating the need for parameter identification procedures of power system. Based on the system data model, the proposed controller coordinates MGs in the NMG in a distributed manner by employing a consensus version of the fast alternating direction method of the multiplier algorithm (FADMM), which achieves a better privacy and scalability. Simulation studies in a modified two-MG NMG demonstrate the effectiveness and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

• The output power volatility of wind-photovoltaic and the operating characteristics of the electrolyzer is considered. • A capacity optimization method for off-grid RES-H2 production systems considering the load-follow-source mechanism is proposed. • A multi-objective optimization model with minimum cost, minimum energy storage capacity and optimal power supply efficiency was constructed. • An improved optimization algorithm based on two common algorithms is designed. Based on the uncertainty of the output of renewable energy such as wind and photovoltaic (PV), a capacity optimization allocation method considering the load-follow-source mechanism is proposed to solve the shortages of traditional methods, which is low in utilization rate of energy and low in economy. Firstly, considering the fluctuations of renewable energy sources (RES) and the operating characteristics of the electrolyzer, this paper proposes a capacity optimization method for off-grid hydrogen(H2) production system of renewable energy sources considering the load-follow-source operation mechanism. Then, combined with this mechanism, a capacity optimization allocation model is established, the objectives contain minimizing the levelized cost of hydrogen (LCOH), minimizing the capacity of energy storage, and optimizing the efficiency of power supply. Finally, an adaptive non-dominated sorting differential evolution algorithm (ANSDE) with external archiving is proposed to solve the established model. The calculation results show that the load-follow-source mechanism is effective for improving the economy of the system, and the proposed algorithm is high in efficiency and good in convergence comparing with traditional algorithms. [ABSTRACT FROM AUTHOR]

Currently, microgrids are becoming more prevalent. Therefore, it is crucial to develop robust and reliable microgrid protection schemes. Researchers have recently explored various approaches to microgrid protection, including adaptive protection and AC microgrid protection. The study offers insights into fault detection and localization in microgrid protection, utilizing precise measurements from the point of common coupling (PCC). It distinguishes between fault occurrences and overload cases, addressing various challenges. Additionally, the analysis explores the role of Linear Discriminant Analysis (LDA) within the framework of multi-machine learning techniques, shedding light on its application in microgrid protection. Ultimately, the aim is to bolster microgrid resilience and reliability for end-users and stakeholders. The system model being tested has been created using Matlab/Simulink software and is based on a real system. The training and testing of the algorithms are developed and evaluated using MATLAB tools. The accuracy of the proposed method is demonstrated in the paper, indicating that it can be used to modernize the current protection apparatus in preparation for the eventual implementation of an advanced microgrid station protection system. • High Accuracy in Fault Identification: DTE and ANN models achieve 100% validation accuracy. • Efficient Overload Differentiation: Superior performance in managing faults and overloads. • Enhanced Fault Localization: Leveraging LDA for improved accuracy in fault localization. • Innovative Voltage Signature Signal: Novel composition enhances signal representation. • Promising Role of LDA: Proficient in fault localization, offering valuable insights. [ABSTRACT FROM AUTHOR]

The adoption of Distributed Generation (DG) technology has seen a substantial level of advancement in recent years. This has created potential protection issues in microgrids during faults and islanding. This paper proposes a fault and islanding detection method using wavelet packet transform (WPT) and Ensemble. A new index called Normalized RMS Node power index (NRNPI) is defined based on WPT to differentiate between transient behavior during faults and islanding, and the ensemble acts as a classifier. The ability of the method in detecting islanding and both grounded and non-grounded faults is demonstrated through simulations of a test system in Matlab Simulink. Real time simulation of the proposed method is done in OPAL-RT using UDP-IP communication protocol. The proposed method as an islanding detection technique gives an accuracy of 100% and 99.32 % as a fault detection technique under the test conditions. Results of both simulations and Hardware in Loop (HIL) implementation is promising. The proposed method has the potential of extending the idea for other transient analysis in the microgrid. • Method capable of detecting islanding and faults in AC microgrid. • Wavelet packet transform used for feature extraction from measured signals. • Ensemble machine learning technique is used for classification of faults and island. • Applicable for microgrids with single distributed generator. • Fast and accurate islanding and fault detection method. [ABSTRACT FROM AUTHOR]

• A clear input–output relationship for the family of frequency estimators is derived based on time-domain feedback analysis. It is revealed that the family of frequency estimators possesses inherent complex-coefficient comb filtering ability. The essential difference of all frequency estimators based on discrete oscillator can be obtained through the established input–output relationship. • An optimized DOM is further derived from the perspective of designing a complex-coefficient comb filter, which makes the frequency estimators have a high harmonic filtering ability near the nominal frequency. This design is simple and easy to understand because the filtering ability of DOM can be analytically expressed by the complex-coefficient comb filter. • An enhanced pre-filter is proposed to expand the frequency range. Different from cascading the same FIR filters at the nominal frequency in previous works, the enhanced pre-filter is tuned at different frequency for simpler digital implementation and flatter attenuation across a wide frequency range. The family of frequency estimators based on discrete oscillator is believed to be the simplest one for single-phase grid voltage. In order to make this family of frequency estimators more feasible in micro-grid, a novel design is proposed in this paper. The novelty includes a clear input–output relationship for the family of frequency estimators based on the discrete oscillator, an optimized design of the discrete oscillator model (DOM), and an enhanced pre-filter. Firstly, the input–output relationship is established by the time-domain feedback analysis, and it reveals that the frequency estimators inherently possess complex-coefficient comb filtering ability. Then, an optimized DOM design is presented to enhance the frequency estimators' filtering ability near the nominal frequency. Lastly, an enhanced pre-filter is proposed to match this optimized DOM for high filtering ability in a wide frequency range. The proposed design method has no stability issues and a very low computational burden. Compared with previous methods, the proposed method demonstrates higher accuracy in frequency estimation and similar response speed in micro-grid with significant frequency fluctuation and harmonic pollution, verified by experimental results. [ABSTRACT FROM AUTHOR]

• The key benefits of the method are as follows. • Detection of various fault with high resistance fault (HRF) about 200 ohms. • Appropriate response time that is nearly 5 milliseconds or 0.31 cycle. • High accuracy according to different cases for simulation is 98.33%. • Considering cross-country fault with CT saturation. • Considering the different case in changing mode with CT saturation. • Detection of bidirectional fault current. • Detection of low level short circuit current. • SST is good for threshold based method due to stablished high amplitude. • SST is not affected by heavy noisy conditions. In recent years, the protection of a microgrid has been a substantial challenge. This paper performs a differential protection scheme for the micro-grid based on Synchro-Squeezing Transform (SST). The proposed scheme protects the micro-grid in different modes i.e. islanded or grid-connected mode. Also, it is investigated in the ring and radial configuration. In the proposed scheme, currents on two sides of the line are measured by current transformers (CTs), and then differential current (I Diff) is calculated. This current is applied to extract the absolute value of the summation of the square root (ASSR). In this stage, transient and external faults without CT saturation and different switching such as connected or disconnected load/capacitor/distributed generation are detected from different internal faults. In the next stage, the frequency components of SST (FCSST) are extracted. By this feature, external fault and cross-country fault with CT saturation are detected. The proposed scheme is evaluated in noisy conditions, fault in different section of line with high resistance fault (HRF), and high impedance faults (HIF) of line. The micro-grid is simulated in PSCAD/EMTDC by various distributed generation (DG) like wind generation and photovoltaic systems penetrated at different buses. The proposed protection scheme is coded in MATLAB. The simulations represent the proposed protection scheme is correctly discriminate external and internal faults. At the same time, the method is immune to CT saturation and cross-country faults. [ABSTRACT FROM AUTHOR]