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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]

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]

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]

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]

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]