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The integration of renewable energy (RE) sources is increasing day by day because of their permanent existence and the limited quantities of fossil fuels. One of the most promising RE sources is photovoltaic (PV) technology, which is developing quickly in many countries worldwide. PV cells generate electricity by converting the sunlight to DC voltage. PV arrays are installed in outdoor areas and on the rooftops of homes to be directly subjected to the sun. Consequently, they are frequently subjected to lightning strikes, which may cause damage to PV arrays, service interruption, and additional cost for PV replacement. Therefore, an adequate lightning protection system (LPS) must be installed to protect the PV panels. In addition, the transient performance of PV panels during lightning strikes must be analyzed well. This paper presents a comprehensive review of the superior modeling methods of PV systems during lightning strikes. In addition, the paper displays the different platforms to simulate the transient effects of lightning strikes on PV systems. The lightning transient effects on PV arrays are studied based on the system modeling to assess the recommended LPS designs studied in the literature. The paper also gives some recommendations about the modeling methods and protection of PV systems during lightning strike. [ABSTRACT FROM AUTHOR]

This paper reviews the applications of Internet of Things (IoT) and digital twin technology in electrical power systems. It begins by discussing the generalized IoT value chain, followed by the terminology of smart grid, with clarifying the role of IoT‐systems and the digital twin structure within the Smart Grid. A comparison between different short‐range and long‐range transports is presented. The paper then discusses the use of IoT and digital twin technology for effective energy management with applications in smart homes, smart buildings, smart grids, smart industries (Industry 4.0), smart transportation and smart cities. Additionally, the paper explores the use of IoT and digital twin technology for condition monitoring and diagnosis (CMD) in electrical power systems. Three different cases are presented for CMD, that is, CMD of power transformers, CMD of electrical grids and CMD of substations. IoT and digital twin applications are also highlighted in power electronic systems. Finally, the paper discusses the challenges and opportunities of applying IoT and digital twin technology to electrical power systems and provides recommendations for future research. [ABSTRACT FROM AUTHOR]

Affected by extreme hot and dry weather events, the power supplied by hydropower is seriously insufficient in Sichuan province during the summer of 2022, causing severe power shortage and incalculable economic losses for the society. Therefore, a novel multi-objective scheduling model based on grid-connected hydro-wind-solar-battery energy resources combining flexible reserves is proposed to collaboratively guarantee the power supply reliability of both the contracted long-distance power transmission and the local electricity demand under extreme hot and dry weather. The intermittent nature of water inflow, wind speed, solar irradiance, and load is considered, and the multi-scenarios are produced using Latin Hypercube Sampling method. In this work, thermal plants are regarded as flexible reserves for easing the load shedding level of local load. The McCormick's Envelope method is implemented to linearize the power production model of the hydropower station. A multi-objective model, including minimum penalty cost of load shedding and carbon dioxide emission, is proposed to achieve the economic-environmental equilibrium of the power system. The proposed multi-objective optimal hybrid energy complementary strategy is transformed into a single objective model via ε -constraint method, and the fuzzy satisfying method is introduced to select the best compromise solution in the Pareto Front. The meteorological information of the summer of 2022 is collected to verify the effectiveness of this proposed mixed-integer-linear-programming energy complementary model based on a hydropower station on the Jinsha River in Sichuan province, China. Numerical experiments demonstrate that the proposed model is efficient and can enhance the reliability of real-world power systems under extreme hot and dry weather. A set of policy suggestions have been provided for Sichuan province to develop the power grid to face the extreme weather effect. [ABSTRACT FROM AUTHOR]

High-voltage direct-current (HVDC) transmission systems are considered an outstanding solution due to high electrical losses emerging from long-distance transmission. However, HVDC transmission lines (TLs) are vulnerable to lightning strikes. In this work, the Yunnan-Guizhou 500 kV HVDC transmission system is used as a case study to evaluate the impact of lightning strikes on DC-TL overvoltages, as no research studies have been conducted to assess the lightning transient behavior of DC-TLs. A comprehensive investigation of the 500 kV DC-TL transient performance during lightning strikes is performed, taking into account different technical aspects that have not been studied in detail by previous researchers. Additionally, analysis of the back-flashover phenomenon has not been conducted well in previous work, and results on the effect of changing the lightning strike current peak and tower grounding resistance on shielding-failure flashover are quite limited. The distributed-parameter model is used to represent the DC-TL using the electromagnetic transients program (EMTP), considering real parameters of shielding wires and DC towers to study the lightning impact in the case of back-flashover and shielding-failure phenomena. Lightning strike is applied to the shielding wire, and the impact of increasing the peak value of lightning current is investigated on the back-flashover occurrence. Moreover, the influence of tower grounding resistance variation on the transient overvoltages across the tower body and back-flashover phenomenon is evaluated. From the simulation results, increasing the lightning current peak and grounding resistance results in higher overvoltages across the tower body, which increases the probability of back-flashover. Additionally, the shielding failure of the TL is assumed, and the variation impact of the lightning current peak and grounding resistance on shielding-failure flashover is investigated. The results show that the impact of the lightning current peak has a more significant impact than the grounding resistance in the case of shielding-failure flashover. [ABSTRACT FROM AUTHOR]

The unbalanced load distribution, the single-phase connection of renewable energy, and the uncoordinated charging of electric vehicles (EVs) will bring a severe issue corresponding to the three-phase unbalance in modern distribution networks. To deal with this issue, a novel multistage optimal dispatching model with the hybrid energy storage system (HESS), consisting of the battery energy storage system (BESS), EV, and supercapacitor (SC), is proposed in this paper. The first stage is conducted on the day-ahead stage, driven by minimizing the total operation cost and relieving power unbalance, the unbalanced penalty cost is introduced into the optimal dispatching model with the electricity purchasing cost and the degradation cost of HESS. Also, the chance-constraint stochastic programming (SP) model with the coordinated operation of HESS is accommodated to handle the diverse uncertainties of renewable energy, load demand, and EV users' behaviors. In the intra-day operation stage, a rolling optimization-based dispatch model is formulated to re-optimize the operation of the SC for the rapid response of mitigating the real-time three-phase unbalance caused by renewable energy. The numerical experiments are executed on the IEEE 34-bus three-phase test system. Compared with the cases without considering SC and the degradation cost of HESS, the power unbalance in the proposed model is reduced by 3.27% and 3.62% per day at the real-time stage, respectively, while total operation cost is reduced by 46.77 US$ and 350.62 US$ per day, respectively. The results validated that the proposed model is efficient in reducing the three-phase unbalance under multi-time scales, improving the economic operation of the distribution network. • Three-phase power unbalance reduction is achieved by hybrid energy storage system. • Supercapacitor is embedded with BESS and EV in day-ahead and intra-day stages. • Multi-stage optimization scheduling model proposed to minimize power unbalance. • Rolling optimization employed in intra-day stage to address short-term unbalance. [ABSTRACT FROM AUTHOR]

Renewables (i.e., solar and wind power) in the Nordic area have highly seasonal characteristics, which severely restrict the wide development of renewables since they can be excessive in summer but insufficient in winter with intermittent outputs. The conventional battery energy storage system (BESS) with short-term adjustment functionality cannot eliminate the seasonal imbalance of renewables. In this regard, a risk-based bi-level planning model is presented to maximize the hosting capacity (HC) of renewables through configuring seasonal hydrogen storage (SHS) and BESS. Specifically, the upper level applies a multi-objective scheme to maximize HC and minimize the investment cost simultaneously. In turn, the lower level is driven by maximizing the profits of the distribution system operator (DSO) with the implementation of price-based demand response (PBDR). Due to forecasting errors of renewables and load resulting from intermittent output and random behaviors, a stochastic programming (SP) method is developed to address and adapt multiple uncertain fluctuations. Moreover, the conditional value-at-risk (CVaR) is introduced to measure the effect of the risks raised by multiple uncertainties on system operation. Finally, numerical studies are employed to verify the effectiveness of the proposed model. Compared to the cases without considering PBDR and SHS, the total renewable energy HC in the proposed model is increased by 2.30 MW and 0.37 MW, respectively, while the yearly cost benefit of DSO is enhanced by 28063.2 US$ and 17823.7 US$, respectively. The promising results demonstrate the empowerment of SHS can promote the cross-seasonal consumption of renewables, effectively maximizing the HC and improving the economic operation of distribution systems. • The hydrogen storage system is considered in this work for the cross-seasonal balance of renewables. • A bi-level planning model is proposed to improve hosting capacity and economic operation of the system. • The coordinated operation of seasonal hydrogen storage, demand response, and battery storage is designed. • The uncertainties and the operation risk brought by renewables and load are considered. [ABSTRACT FROM AUTHOR]

The application of virtual synchronous generators (VSGs) in power systems is gradually increasing to address the low inertia issue caused by the high penetration of renewable energy sources. Besides, the stability of microgrids (MGs) is threatened by constant power loads (CPLs) consisting of power electronic converters with closed‐loop controllers. To investigate the stability of the MG composed of VSG and CPL, this paper analyzes the operational principles of VSG and CPL, revealing that only the bipolar switch logic function is suitable for establishing a closed‐loop model if the output of the inner‐loop controller is considered as the duty cycle of the PWM signal. Furthermore, the closed‐loop impedance models of VSG and CPL were established in the dq frame. Impedance‐based analysis results show that the MG is prone to oscillation in the mid‐band. Therefore, the active power loop parameters of the VSG have a small impact on the stability of the MG, while the LC filter and inner loop controllers have a greater impact on the stability. Based on the oscillation mechanism and passivity theory, the impedance reshaping strategy for VSG and CPL is proposed. It is verified that the proposed control strategy can significantly improve the stability of the MG through the comparison of simulation results and theoretical analysis. [ABSTRACT FROM AUTHOR]

Summary: The large integration of distributed generation (DG) and electric vehicles (EVs) facilitates daily life and reduces carbon emissions. However, it brings problems such as increased uncertainty and power electronic permeability to the distribution network. In this context, it is important to solve the line loss optimization problem as closely as possible to the real situation. Therefore, this paper solves the line loss optimization problem based on a probabilistic model of three‐phase unbalanced modern power electrical distribution network. Firstly, the paper proposes a frequency domain model of the distribution network and the optimization problem model. Then, to deal with the uncertainty of the system, the point estimation method (PEM) and Monte Carlo Simulation (MCS) are used. Finally, this paper proposes two optimization schemes considering the power quality when single and multiple DGs are integrated. The simulation results demonstrate that the PEM using the Gram–Charlier series expansion of the fourth‐order statistical moments to estimate the probability density function (PDF) is significantly less time consuming than the traditional MCS method while maintaining accuracy. The comparative analysis reveals that under the optimization scheme with single DG integration, the expected value of system line loss and expected line loss rate are reduced from 283.95 kW to 218.96 kW (22.89% reduction) and from 13.44% to 10.68%, respectively. Under the dual DG integrated optimization scheme, the expected value of line losses and expected line loss rate are reduced from 283.95 kW to 208.88 kW (26.4% reduction) and from 13.44% to 10.25%, respectively. However, after taking the uncertainty into account, the operational reliability of the system has been enhanced under different scenarios. In addition, it is found that the optimization approach incorporating multiple DG units can effectively mitigate the system line loss under diverse operational scenarios while enhancing the system's DG integration capability. [ABSTRACT FROM AUTHOR]

Wind energy integration in power grids is increasing day by day to reduce the use of fossil fuels, and consequently greenhouse gas emissions. Using the pulse-width modulated (PWM) power converters in wind turbine generators, specifically in doubly-fed induction generators, results in generating a common-mode voltage (CMV). This common-mode voltage causes a flow of common-mode current (CMC) that leaks through the stray capacitances in the generator structure. These currents impose a voltage on the generator bearing which may deteriorate them. In the current work, an active common-mode voltage canceler (ACMVC) is developed to eliminate the CMV produced by a PWM converter. The ACMVC generates a compensating voltage at the converter terminals to eliminate the CMV with a subsequent reduction of the voltage stress on the generator bearing. This compensating voltage has the same amplitude as CMV, but opposite polarity. A simulation of the ACMVC model is performed using the PSCAD/EMTDC (Electromagnetic Transient Design and Control) software package. Results confirm the effectiveness of ACMVC in canceling not only the CMV but the CMC and bearing voltage as well. In addition, the relationship between the rise time of CMV and the peak value of CMC is investigated. [ABSTRACT FROM AUTHOR]

Fault diagnosis and location play a pivotal role in expediting fault restoration and enhancing power system resilience. However, integrating distributed generation and diverse load profiles has led to more complicated distribution networks, intensifying fault diagnosis and location challenges. Hence, there is a need to transform traditional distribution networks into resilient active ones that actively guide and utilize distributed energy resources, possessing active control and operational capabilities. This paper comprehensively reviews fault diagnosis and location techniques in distribution networks, focusing on faulted line selection, fault section estimation, and accurate fault location. It provides an in-depth analysis of current fault diagnosis and location techniques, along with an assessment of their challenges, summarizing and evaluating the current research status at both local and international levels. To address existing fault diagnosis and location technologies limitations, a method utilizing micro-phasor measurement units (μPMUs) to enhance situational awareness and state estimation of active distribution networks is proposed. The paper also provides a comprehensive analysis of the optimized configuration strategy for achieving network observability and fault diagnosis using limited μPMU, in addition to comparing and analyzing the advantages and disadvantages of typical solution algorithms for the optimal PMU placement (OPP) problem. In response to extreme disturbance scenarios in active distribution networks, resilience enhancement strategies are proposed from three perspectives: fault prevention, fault response, and fault restoration. Finally, a summary and outlook on current research methods for fault diagnosis and location, as well as the challenges and future research directions in resilience enhancement strategies, are provided. [Display omitted] • Review fault diagnosis, section estimation, and accurate fault location methods. • Improving power system resilience through fault diagnosis and location. • Strategies using limited μPMUs to enhance distribution network situation awareness. • Comprehensive methods for power system resilience in extreme disasters. [ABSTRACT FROM AUTHOR]

As the variety of loads in microgrids continues to grow rapidly, the drawbacks of using conventional voltage and current double closed-loop PI control are becoming increasingly intolerable. These disadvantages include poor static tracking of the output and the need for complicated tuning of optimal PI control parameters. Model predictive control (MPC) is widely studied in recent years and gradually applied to the inverter as a modern control strategy. Currently, the research on MPC mainly focuses on reducing the computational burden of algorithms and improving computing skills. In this paper, the control theory of continuous-control-set model predictive control (CCS-MPC), optimal switching vector model predictive control (OSV-MPC), quasi-sliding mode model predictive control (QS-MPC) and optimal switching sequence model predictive control (OSS-MPC) are elaborated. Also, the disadvantages of adopting conventional voltage and current double closed-loop PI control on microgrids are clarified. Moreover, aiming at evaluating the influence of connecting and/or removing the common loads, such as electric vehicles to the microgrid on the output performance of microgrids in practical engineering applications, single three-phase voltage source inverter with LC filter system with two-phase pure resistance load, three-phase diode rectifier bridge nonlinear load, constant power load and constant current source load applying four different MPC methods, are simulated. The simulation results show that under different types of load, system with nonlinear load applying OSV-MPC method has the biggest value of total harmonic distortion (THD) of the output voltage and the biggest steady state root mean square (RMS) tracking error of the output voltage, which are 1.33% and 2.1 V, respectively. The performances of the output voltage of the system adopting MPC are generally improved compared to the system using conventional voltage and current double close-loop PI control. Regarding the output voltage performance of a system under load step change, a system using the OSS-MPC method with a nonlinear load exhibits the smallest overshoot of the output voltage and the smallest root mean square value of the tracking error (RMSE) between the output voltage and the reference value within 20ms after the load step change. Specifically, the overshoot and RMSE are 2.804 V and 0.810 V, respectively. The simulation results provide valuable guidance for selecting the appropriate model predictive control strategy for microgrid integrating complex loads, such as electric vehicles in practical applications. • Three different kinds of model of three-phase voltage source inverter with LC filter system are established. • Four main types of MPC methods are adopted to the system. • Different types of load are connected to the system. • Output performances in load jump and steady state are compared by simulating in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

• Analysing circuit principle of harmonic source of nonlinear equipment. • Studying the harmonic source of ferromagnetic saturation devices. • Evaluating working characteristics of impact load equipment like arc furnace. • Discussing harmonic emission level of electric locomotive in different working conditions. • The causes of harmonics are explained from the physical level. The future of power systems is moving towards a greater use of renewable energy sources and a higher proportion of power electronic devices. However, this has led to an increase in power quality issues that can seriously affect the stable operation of power systems. One key aspect of evaluating power quality of the grid is analysing harmonics and their sources. There are several challenges in understanding and controlling harmonics, including modelling the sources of harmonics, tracing them, and controlling their impact. This paper presents a comprehensive review on the common models of harmonic sources in modern power systems, and provides insight into the circuit mechanisms, mathematical models, and operational processes of these sources. It also examines the harmonic characteristics of various sources in typical operating scenarios, involving typical residential power load, electric vehicle charging scenario, frequency conversion speed regulating device, renewable energy generation scenario, electric arc furnace load and electric locomotive load, and offers a summary of typical harmonic source equipment. Additionally, this paper looks ahead at the future and development directions of harmonic analysis and control in the context of modern power systems. This work can be used as a guide to improve the understanding of harmonic distortion in modern power systems and to develop methods for mitigating its negative effects on power quality and system stability. [ABSTRACT FROM AUTHOR]

Nowadays, the load monitoring system is an important element in smart buildings to reduce energy consumption. Nonintrusive load monitoring (NILM) is utilized to determine the power consumption of each appliance in smart homes. The main problem of NILM is how to separate each appliance's power from the signal of aggregated consumption. In this regard, this paper presents a combination between particle swarm optimization (PSO) and artificial neural networks (ANNs) to identify electrical appliances for demand‐side management. ANN is applied in NILM as a load identification task, and PSO is used to train the ANN algorithm. This combination enhances the NILM technique's accuracy, which is further verified by experiments on different datasets like Reference Energy Disaggregation Dataset, UK Domestic Appliance‐Level ElectricityUK‐DALE, and Indian data for Ambient Water and electricity Sensing. The high accuracy of the proposed algorithm is verified by comparisons with state of the art methods. Compared with other approaches, the total mean absolute error has decreased from 39.3566 to 18.607. Also, the normalized root mean square error (NRMSE) method has been used to compare the measured and predicted results. The NRMSE is in the range of 1.719%–16.514%, which means perfect consistency. This demonstrates the effectiveness of the proposed approach for home energy management. Furthermore, customer behavior has been studied, considering energy costs during day hours. [ABSTRACT FROM AUTHOR]

Hybrid DC microgrid clusters contain various types of converters such as BOOST, BUCK, and bidirectional DC/DC converters, making the control strategy complex and difficult to achieve plug-and-play. The common master–slave hierarchical control strategy makes it difficult to achieve accurate and stable system control. This paper proposes an accurate peer-to-peer hierarchical control method for the hybrid DC microgrid cluster, and the working principle of this hierarchical control method is analyzed in detail. The microgrid cluster consists of three sub-microgrids, where sub-microgrid A consists of three BUCK converters, sub-microgrid B consists of three BOOST converters, and sub-microgrid C consists of two bidirectional DC/DC converters. According to all possible operations of various sub-microgrids in the microgrid cluster, the top-, mid-, and bottom-level controls are designed to solve the coordination control problem among different types of sub-microgrids. In this paper, a hybrid microgrid cluster simulation model is built in the PLECS simulation environment, and an experimental hardware platform is designed. The simulation and experiment results verified the accuracy of the proposed control strategy and its fast plug-and-play regulation ability for the system. [ABSTRACT FROM AUTHOR]

Currently, distribution systems are continuously evolving towards modern and flexible structures while integrating promising renewable energy resources (RERs). In this regard, an optimal network constraint-based expansion planning model combined with an optimal integration framework of intermittent RERs is proposed in this work to improve the topological flexibility in modern distribution networks (DNs). Specifically, the best investment locations and times of substations, lines, and RER-based distributed generations (DGs) are jointly taken into consideration. Additionally, the uncertainty-based multiple scenarios are modeled by probability distribution functions to strengthen the robustness and reliability of DNs influenced by the stochastic of renewable energy and load behavior. The novel network constraint is combined with three levels, where the first level introduces the graph theory to guarantee the radiality topology of modern DNs. In the second level of the network constraint, graph theory and fictitious load theory are collaboratively applied to ensure that each subsystem has a reserve connection interconnected to other subsystems. The third level is modifying the conventional fictitious load theory to ensure each subsystem is linked with at least one DG. The proposed planning model is driven by the minimum present value of total cost, including investment cost of branches, DGs, and substations, cost of substations operation, the electricity purchasing cost of substations and DGs, power losses cost, and environmental penalty cost of conventional generators. Numerical results are presented to verify that a more flexible and resilient topology of the DN system is obtained, and criteria evaluation is introduced to validate its higher performance with respect to existing procedures from power supplied quality, environmental burden, and supplied flexibility three aspects. [ABSTRACT FROM AUTHOR]

Achieving the goal of sustainable development is dependent on the widespread integration of renewable energy sources, energy storage systems (ESSs), and electric vehicles (EVs). However, a continuous increase in the penetration of such elements would bring more complexities to the distribution network. Accordingly, this paper presents a unified planning model comprising renewable energy-based distributed generation (DG), ESS, and electric vehicle charging stations (EVCSs). In this regard, a Latin Hypercube Sampling method is utilized to generate multi-scenario for describing the uncertainty of renewable energy and load demand. The stochastic EV charging behaviors are represented by various probability density functions (PDF). In addition, an exploitable capacity loss of ESS and EV batteries is calculated by the battery degradation model based on the depth of discharge (DOD). Furthermore, the battery degradation cost is incorporated into the objective of the planning model to identify the optimal decision for candidate assets. A piecewise linearization approach is introduced to convert the problem into a mix-integer linear programming (MILP) model. Numerical results demonstrate that the exploitable capacity loss of batteries plays a key role in asset planning and provides potential contributions to the optimal decisions of the distribution network. In the meantime, by considering battery degradation in the optimization model, the sustainability and lifetime of the battery can be preserved. • Uncertainties include the renewable energy, load demand, and behaviors of electric vehicles are considered. • Renewable energy-based DG, ESS, and EVCS are involved in the unified planning model. • The degradation model is proposed to analyze the exploitable capacity loss of ESS and EV battery. • The enhancement of investment decision while maintaining the lifetime of battery is achieved. [ABSTRACT FROM AUTHOR]

• Establishing a realistic unbalanced harmonic power flow calculation model. • Establishing DG line loss optimization model with harmonic constraint. • Analyzing several DG line loss optimization schemes in distribution network with multi-type harmonic loads. • The harmonic contents have been decreased but also increased the line loss. • Under the same line loss, the optimal capacity of double DG is less than that of single DG, • The optimization of double DG is better without considering the cost. With the large penetration of power electronic devices in distribution networks, power quality problems such as line loss and harmonics have become the main factors affecting the access of distributed generation (DG). At present, the research on DG integration, such as the optimization of the DG capacity using particle swarm optimization algorithm and ant colony algorithm, is mainly focused on the traditional distribution network. In contrast, the research on the power electronic distribution networks, which include a large number of harmonic sources, is not sufficient. This paper presents a novel optimization method for connecting DG to power electronic distribution network to reduce line loss. Firstly, based on the frequency domain model of the distribution network, this paper establishes the harmonic model of distribution network components, including generators, transformers, lines, harmonic sources and non-harmonic sources. Then the location and capacity of DG are optimized using genetic algorithm with network loss reduction as a target and voltage and harmonic as constraints. Finally, the power electronic distribution network is modelled based on the IEEE 34 - node standard model. The obtained results confirmed that the optimization model with harmonic constraints can effectively reduce the line loss by 108.26 kW and the line loss rate by 4.67 % using single DG. Also, when using the double DG, the line loss and the line loss rate are decreased by 118.53 kW and 5.14 %, respectively. In addition, the optimization effect of dual DG is better than that of single DG without considering the cost. [ABSTRACT FROM AUTHOR]

Reliability improvement is regarded as a crucial task in modern distribution network expansion planning. Compared to previous works, this paper presents a bi-level optimization model to optimize the planning of the distribution network complying with multiple renewable energy and energy storage system (ESS) functionalities to guarantee the economical and reliable operation of the distribution network. The candidate assets include substations, distribution lines, renewable energy-based distributed generations (DGs), and ESSs are systematically involved. The load level affected by seasonal change and the multiple uncertainties, including renewable energy, load fluctuation, and contingency outage, are comprehensively considered. The uncertainties caused by the stochastic of renewable energy and load demand are described using Latin Hypercube Sampling (LHS) method. To address the computational burden and complexities associated with non-linear AC power flow, the mixed-integer linear programming (MILP)-based bi-level model is proposed via piecewise linearization methodology. Therein, the upper-level optimization model is proposed to minimize the total present value cost of the planning scheme in normal operating conditions. The lower level model, which is constrained to investment decision-making of the upper-level framework, aims to minimize the total cost of expected energy not supplied (EENS) considering the uncertainties of the single contingency outage. The effectiveness of the proposed bi-level planning model is validated by numerical studies to guarantee economic and reliability improvement for distribution network. • Multiple uncertainties are comprehensively considered in the proposed model. • Branches and multi-type generators are incorporated to the joint planning model. • Optimal allocation and reliability assessment are coordinated to build bi-level model. • The benefits from ESS for reliability enhancement is analyzed. [ABSTRACT FROM AUTHOR]

• Multi-damping factor design method for PBC of SPVSI with LC filters. • Ensure the stability of islanded SPVSI system under various load scenarios. • Ensure the stability of islanded SPVSI system under LC filter parameter drift. • Adopting a design sequence from the inner to the outer control loop. • Design of control loops with good performance and distinct control bandwidth. With the advantages of fast response, good stability, and strong robustness to filter parameter variations as well as load perturbations, the application of passivity-based control (PBC) in the single-phase voltage source inverter (SPVSI) has received extensive attention. However, as a non-linear control strategy, PBC control has a complex coupling structure containing feed-forward, negative feedback, etc., which poses many difficulties for multi-damping design. In addition, ensuring the passivity of the islanded system under various load conditions or filter parameter drift is still an unresolved issue in the damping coefficient design of the PBC controller. Therefore, for SPVSI systems with LC filters, this paper proposes a multi-damping coefficient design method for PBC controllers based on stability domain analysis. The designed PBC controller can ensure system stability under several load conditions or certain deviations of LC filter parameters. Moreover, the design order from the inner to the outer control loop is adopted according to the distribution of individual damping coefficients in the control loop. As a result, each control loop has a good dynamic performance and distinct control bandwidth. Finally, robustness analysis, simulation, and experimental results verify the correctness and effectiveness of the proposed multi-damping coefficients design method for the PBC controller. [ABSTRACT FROM AUTHOR]

• Based on impedance model of two-stage PV inverter in frequency domain, the passive equivalent impedance network of PV inverter connected to power grid is built. • The harmonic amplifying characteristic curve of PCC in full frequency range is established, and the influence of inverter parameters, reactive power compensation device and distributed transmission line model on harmonic characteristics is deeply analyzed. • A harmonic mitigation control strategy with superimposed multi-current resonance controllers and active damping controllers in synchronous rotating coordinate system is proposed, and the effectiveness of this control strategy is verified by simulation. To investigate the harmonic characteristics of a photovoltaic (PV) system connected to the weak grid, a passive impedance network is constructed using the impedance model of a PV inverter in the positive and negative sequence coordinate system. By analyzing the series resonance of the impedance network, the amplification coefficient of the harmonic voltage at the point of common coupling (PCC) is obtained. In addition, the effects of different PV inverter parameters, different reactive power compensation capacities, and different lengths of distributed transmission lines on the harmonic amplification are analyzed in detail. To solve the problem that the output harmonics exceed the standard under the background harmonic condition of the weak grid, a harmonic mitigation control strategy is implemented. This strategy is designed based on multiple resonant current controllers and active damping feedback to improve the ability of the PV inverter to suppress harmonics under the grid background harmonic conditions. The effectiveness of the harmonic mitigation control strategy is demonstrated by the simulation example of the inverter connected to the grid with symmetric and asymmetric background harmonics, respectively. [ABSTRACT FROM AUTHOR]

• Establish a complete impedance model of the two-stage PV inverter. • Evaluate impedance characteristics and stability issues in case of a weak grid. • The increase of output capacity results in high frequency oscillations. • The increase of PLL bandwidth also causes oscillations in PV inverters. • The stability analysis is verified by the simulation results using PSCAD/EMTDC. In order to obtain impedance characteristics of the photovoltaic (PV) inverter and reveal potential stability issues of the PV inverter connected to a weak grid, a complete impedance model of the two-stage PV inverter is established in this paper. The model includes the PV arrays, front-end Boost converter, and rear-end inverter with output LCL filter. The impedance modeling of the PV inverter is derived at different interfaces of DC-link and point of common coupling (PCC), where the DC impedance characteristic at DC-link and d -q axis impedance feature at AC side are both investigated. It is worth noting that the DC output impedance of front-end circuit behaves as a first-order low-pass filter, and it is mainly influenced by the DC-link capacitor. Moreover, a significant feature is found that a reduced integral gain in the outer voltage loop may cause a negative resistance and capacitive impedance in d -axis impedance component. In addition, based on the impedance analysis method, the oscillation stability issues of the grid-connected PV inverter in case of a weak grid are evaluated by different divisions of source-load subsystems. It is demonstrated that the increase of the PLL bandwidth and the decrease of the integral gain of the outer voltage loop will both lead to the oscillation of the PV inverter. Moreover, the increase of the output capacity will deteriorate the stability margin, resulting in the high frequency oscillation of the system. Finally, the impedance model and the stability analysis are verified by the simulation results implemented in PSCAD/EMTDC platform. [ABSTRACT FROM AUTHOR]

• Analyze the structure of conventional atomic decomposition algorithm (CAD). • Improve the computational efficiency and the accuracy of sub-dictionaries. • Propose an improved CNN-based atomic decomposition algorithm. The atomic decomposition (AD) algorithm for Power Quality Disturbance (PQD) signals can obtain sparser and physically clearer results than the conventional fixed basis decomposition method. However, the conventional atomic decomposition (CAD) algorithm for PQD signals suffers from excessive computational resource consumption and low accuracy of sub-dictionaries selection. In this paper, the CAD algorithm for PQD signals is optimized by introducing a Convolutional Neural Networks based (CNN) sub-dictionary predictor inspired by the PQD signal classification technique. In the optimized algorithm, by using a sub-dictionary predictor to select sub-dictionaries directly, the range of each atomic search is significantly reduced. In addition, the undesirable effects of the intelligent optimization algorithm are mitigated, which match the non-global optimal results in search of sub-dictionaries. Besides, the goal of reducing computation resources is achieved, and the accuracy of sub-dictionaries selection is improved. Finally, the CAD algorithm and optimized CNN-based atomic decomposition (CNN-AD) algorithm are compared and analyzed on the synthetic dataset and the measured dataset from IEEE 1159.2 Working Group on power quality disturbances. Consequently, it is verified that the CNN-AD can reduce the requirement of computation resources and improve the accuracy of sub-dictionaries selection in the decomposition for PQD signals. [ABSTRACT FROM AUTHOR]