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This paper focuses on the issue of network connectedness (NC) in security-constrained optimal transmission switching problems, which is complicated by branch contingencies and corrective line switching. Two criteria are firstly proposed with the principle of preserving NC as much as possible within reasonable limits. By extending the electrical flow based NC constraints, a proposition is derived to associate different cases of NC with the optimum of a linear program, yielding the mathematical formulation of the NC criteria. By Karush-Kuhn-Tucker conditions, this formulation is further transformed into a tractable version which can be incorporated with existing SCOTS models without affecting the applicability of original solution approaches. Finally, case studies on various networks and SCOTS models demonstrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a novel hierarchical cooperative control strategy to solve the problems of unbalanced State of Charge (SoC), unreasonable load current sharing, and unstable bus voltage for battery storage system (BSS) in islanded DC microgrid. In the communication layer, a neighbor-to-neighbor communication network architecture is constructed in which each battery storage unit (BSU) only communicates information with neighboring nodes, and a multi-agent consensus algorithm is used to iteratively estimate the relevant average global variables. In the main control layer, the droop coefficient is dynamically adjusted by constructing a fast SoC convergence function to ensure that the load current is reasonably distributed based on the rated capacity of each BSU. In the secondary control layer, a virtual voltage drop equalization controller and an average bus voltage compensation controller are designed to eliminate the impact of line impedance mismatch and compensate the average bus voltage. Furthermore, an optimized factor is designed to accelerate the later stage of SoC convergence. Finally, a DC microgrid experimental platform based on StarSim HIL is built, and the results demonstrate that the proposed strategy can achieve the control objectives of fast SoC balance, proportional load current sharing, and bus voltage stability. [ABSTRACT FROM AUTHOR]

This paper presents a novel distributed voltage control method for multi-terminal direct current (MTDC) systems based on the average consensus algorithm. The proposed method combines the idea of secondary integral voltage control and regulator synchronization problem. It realizes adjustable tradeoff between two conflicting control objectives, that is, voltage regulation and power sharing. The proposed control algorithm only needs a low-bandwidth communication between two adjacent voltage source converters (VSCs) and local information to work effectively. Moreover, regarding the system dynamic response, a parameter tuning method for the proposed controller is provided to achieve the fastest convergence of the distributed control algorithm. This paper also develops a small-signal dynamic model for VSC-MTDC systems with distributed controllers to evaluate the system dynamic performance. The proposed method is validated by time-domain simulation of a 4-terminal VSC-MTDC system. The simulation results show that flexible tradeoff between voltage regulation and power sharing can be achieved under necessary constraints on the DC bus voltages and power sharing ratio. [ABSTRACT FROM AUTHOR]

This paper emphasizes the importance of including unbalanced distribution systems for voltage stability studies in power systems. The paper aims to: discuss the various simulation methods for power system analysis; highlight the need for modeling unbalanced distribution system for accurate load margin assessment; demonstrate the influence of net-load unbalance (NLU) on voltage stability margin (VSM). We also share a T&D co-simulation interface with commercial power system solvers. The distribution system is evolving rapidly with high proliferation of distributed energy resources (DERs); these are not guaranteed to proliferate in a balanced manner and uncertainty resulting due to these DERs is well acknowledged. These uncertainties cannot be captured or visualized without representing the distribution system in detail along with the transmission system. We show the impact of proliferation of DERs in various 3-phase proportions on voltage stability margin through T&D co-simulation. We also study the impact of volt/VAR control on voltage stability margin. This analysis is only possible by representing the distribution system in detail through T&D co-simulation. Higher percentage of net-load unbalance (NLU) in distribution system aggravates the voltage stability margin of the distribution system, which can further negatively influence the overall voltage stability margin of the system. [ABSTRACT FROM AUTHOR]

Variability in power generation at multiple consumer-owned renewable energy sources can cause random voltage fluctuations, which may result in voltage violations at multiple nodes in a power distribution system. Traditional methods of voltage control are ineffective to address fast voltage variations. New dynamic methods of voltage control using end-user devices can significantly benefit from the knowledge of the dominant influencer of voltage fluctuation (DIVF). This paper introduces information theoretic metrics to identify DIVF for every node in the power distribution system. A node can be DIVF due to its location in the distribution system and its capacity to generate and change its power. Use of traditional power flow algorithms to identify the DIVF is computationally complex, which limits their use in real-time applications. In this paper, information theoretic indicators of the DIVF are computed analytically in a computationally efficient manner, and their effectiveness to identify the DIVF is tested using the IEEE 69 node test system. From simulations, it is shown that differential entropy, Kullback–Leibler distance, and Frechet distance are effective indicators of the DIVF and can successfully identify the most influential nodes providing the foundation for intelligent voltage control. [ABSTRACT FROM AUTHOR]

In practical power systems, it is still very challenging to figure out a cost-effective undervoltage load shedding (UVLS) scheme that can reliably and adaptively react to the short-term voltage stability (SVS) problem. Faced with this challenge, this paper develops an intelligent data-driven predictive UVLS scheme for online SVS enhancement. Inspired by valuable ideas in model predictive control and supplementary excitation control in power systems, a novel deep feedback learning machine (DFLM) is designed to precisely predict future voltage violations after UVLS execution. With the help of the DFLM, the UVLS scheme is aware of potential effects of various candidate UVLS actions. Owing to this desirable nature, it can adaptively respond to diverse SVS conditions and optimize UVLS decisions in a non-iterative way. Further, two well-designed strategies, i.e., stepwise constraint relaxation and incremental DFLM adaptation, are introduced to enhance the scheme's reliability and adaptability during online application. Numerical test results on the Nordic test system and the realistic North GZ Power Grid in China showcase the excellent performances of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper proposes advanced control strategies to enhance fault ride-through capability of modular multilevel converter-based high voltage direct current (MMC-HVDC) connected doubly-fed induction generator (DFIG)-based wind farms. A stepwise voltage drop control is proposed for the sending-end MMC to suppress dc line voltage fluctuations by demagnetizing DFIGs. Meanwhile, a modified transient current control is proposed for the DFIG, where a voltage-dependent active current control is integrated into the rotor-side converter to improve synchronization stability of the converter, and a feedforward transient stator current control structure is designed to eliminate dc component in the stator current. The proposed control strategies are validated by comparing with three typical methods through time-domain simulations. [ABSTRACT FROM AUTHOR]

The renewable energy source based generating technologies and flexible demand and storage devices exhibit significant temporal and spatial uncertainties in generating and loading profiles and introduce additional level of uncertainty in network operation. The dynamic behaviors of such a network can be affected and the stable operation may be compromised. This paper proposes a probabilistic analysis approach for the evaluation of the effect of uncertain parameters on power system voltage and angular stability. Load margin, the damping of critical eigenvalues and the transient stability index have been chosen as the relevant stability indices for voltage stability, small-disturbance stability, and transient stability analysis, respectively. The Morris screening sensitivity analysis method coupled with a multivariate Gaussian copula to account for parameter correlations is used for the priority ranking of uncertain parameters. The approach is illustrated on a number of case studies using modified IEEE 68-bus NETS-NYPS test system. The results obtained in this paper reveal that the critical parameters appear as groups if the input dataset is correlated, and, hence even a parameter (which may be uninfluential individually) can have a significant impact on system dynamic behavior due to its correlation with other influential parameters. [ABSTRACT FROM AUTHOR]

Load characteristics have substantial influence on the voltage stability of power systems. The self-restorative characteristic and stalling of induction motor loads can deteriorate the voltage stability, so it is necessary to develop accurate and efficient dynamic analysis methods for voltage stability analysis of systems with induction motor loads. In this paper, a set of methods based on holomorphic embedding is proposed, which is able to solve steady states and dynamics of a power system with induction motors. The paper is the first work that applies holomorphic embedding to dynamic problems of power systems. The test cases on the IEEE 14-bus system, the NPCC 140-bus system, and the Polish 2383-bus system verify both accuracy and efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable-rich distribution systems, and the prohibitive cost of upgrading the system infrastructure, has rendered voltage instability a real concern for heavily loaded systems. The voltage instability of distribution systems can spread to the corresponding transmission grid, as proven by real-life incidents. Recent advances in energy storage systems (ESSs), however, have offered a viable means of enhancing the reliability and robustness of power systems. In this paper, the optimal placement, sizing, and operation of ESS devices in wind-intensive distribution power systems are studied. The objectives of this paper are to minimize the ESS size (power and energy), required to ensure a desired voltage stability margin (VSM), and to minimize the reactive power loss and reactive power import from the upstream network. Wind uncertainty has been accounted for through a risk-based stochastic optimization framework. Besides, active network management (ANM) tools, such as the tap position of on-load tap changers, modelled by using a new method, and reactive power capabilities of both ESS devices and wind farms, are used as additional means to reduce the required ESS size. The results show that the required ESS significantly increases with increase in the desired VSM. Nevertheless, the increase can be considerably curtailed by using risk-based VS constraints and ANM tools. [ABSTRACT FROM AUTHOR]

To uncover the mechanism by which voltage-dependent loads (VDLs) influence electromechanical dynamics, this paper mathematically deduces the damping torque induced by VDLs based on a single machine infinite bus system. Moreover, by continuously regulating the terminal voltage of a typical large-scale VDL, i.e., the aluminum electrolysis load, this paper proposes a novel load damping control architecture to dynamically modulate the power consumption of controlled loads so as to eliminate interarea oscillations in power systems. Specifically, the decentralized load damping controllers (LDCs) used in this architecture are designed by a proposed multistage mixed ${{{H}}_{2}} / {{{H}}_\infty }$ control approach to guarantee robustness against uncertainties (e.g., tie-line outages and wind generation fluctuations) as well as to ensure reasonable control efforts of controlled VDLs. Simulation results on the modified New England and New York interconnected system validate the method for analysis of VDLs’ effects on interarea oscillations and show the proposed load damping control strategy can satisfactorily damp interarea oscillations over multiple operating points. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the combined effects of load variability and phase imbalance onto simulated low-voltage grid losses. The paper proposes new indices for relative load time-variability and phase-imbalance. With those indices, linear mappings are derived for the relative losses caused by a single three-phase load when modeled as a random variable that is per-phase identical and independently distributed. Impacts of increasingly complex load modeling are then obtained by simulation and used to gain insight into loss estimation errors caused by simplified representations of time-variability and phase-imbalance. Based on the linear mappings and on the simulation results obtained under realistic grid loading, limitations of present day meter resolution are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a new security-constrained multiobjective optimal dispatch (SC-MOOD) framework for an economic and reliable operation of microgrids. The framework is developed based on a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The new method considers grid steady-state and dynamic constraints while solving the optimal dispatch in both grid-connected and islanded modes. The constraints consist of power balance, voltage magnitude, line flows, power generation, frequency, and voltage transients. The proposed framework finds the most economic operating solutions to not only minimize the generation cost but also minimize the reliability cost. In this paper, the PaCcET is utilized to solve the SC-MOOD. The PaCcET uses an extraordinary transformation to first transfer all the points from a multiobjective space to a transformed objective space. It then solves a linear combination of transformed objectives using a single-objective optimizer to find all the nondominated points of the original multiobjective space. The performance of the new framework is verified using the simulation results in a microgrid with several distributed energy resources in both grid-connected and islanded modes. The results are then compared with two multiobjective optimization techniques, nondominated sorting genetic algorithm II and multiobjective particle swarm optimization, as two well-known benchmarks. [ABSTRACT FROM AUTHOR]

The introduction of an equivalent model for a regional power area in a large-scale power system with complex loads is essential for reducing the computation burden in real-time dynamic analyses. In this paper, we propose a generalized discrete-time equivalent model (GDEM) with specific relations among model parameters for simulating the physical characteristics of a regional power area. The GDEM facilitates the interconnection of equivalent models representing regional power areas and improving the simulation accuracy and speed in large-scale dynamic power systems. This paper first investigates the inherent relations among GDEM parameters in the discrete-time models of synchronous generators and composite loads so as to guide the GDEM parameter estimation in regional power areas. This paper then develops relations among GDEM parameters for a regional power area. Numerical experiments are conducted by simulating ground faults in the China Electric Power Research Institute system and the accuracy of the proposed GDEM is verified by analyzing the dynamic simulation results. In addition, this paper has applied the GDEM to study the regional power area of Central China, which validates the use of GDEM in practical power system analyses. [ABSTRACT FROM AUTHOR]

Centralized electricity markets currently do not optimize reactive power and voltage in the market clearing software. Voltage and local reliability (VLR) commitment requirements are mostly identified through out of market operational procedures. Failure to maintain VLR may incur voltage collapse, generation, transformer loss, or even blackout. Midcontinent Independent System Operator (MISO) employs binary constraints, minimum/maximum generation constraints, interface constraints, and manual commitments to address VLR requirement in the market clearing process and ensure adequate commitment for reliability. This paper integrates binary VLR constraints in day-ahead security constrained unit commitment to improve market efficiency. However, VLR constraints may cause uplift cost, and sometimes the associated uplift cost can be significant. An uplift cost allocation method with the consideration of resources commitment reasons is developed in this paper. The proposed approach is considered for implementation in MISO market clearing process and a MISO test case is used to validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The uncertainty has been one of the main obstacles in the operation of distribution systems with renewable energy resources whose power generation is, by nature, highly intermittent, often resulting in the unbalanced conditions of distributed networks. This unbalance degrades voltage profiles and, thus, aggravates power loss consumed in distributed networks. In this sense, the pragmatic coordination scheme between day-ahead and real-time optimization to achieve economic and stable operation is presented in this paper. At the day-ahead optimization stage, the objective aims to minimize operation costs by controlling the energy storage system such as battery systems. This stage is based primarily on historical data about the daily profiles of power demands or renewable distributed generations, so uncertain elements are always inevitable in operational procedures. The real-time monitoring system plays a pivotal role in computing present operating conditions on a real-time basis sufficient to address these uncertainties of renewable energy resources. The operating conditions are, then, utilized to formulate the objective function and relevant constraints to calibrate control orders once decided at the day-ahead optimization stage. This paper explains the proposed coordination scheme with real-time monitoring capability and, then, presents the test results of numerical experiments with a 15-bus test distribution system. [ABSTRACT FROM AUTHOR]

This paper discusses the marginal line loss approximation in the dc optimal power flow (DCOPF) and proposes a new methodology that improves the accuracy of current practices. In practice, the DCOPF solution may have significant differences compared to the ac base point that determines marginal losses, and this paper provides the only published example that illustrates this problem to our knowledge. The proposed methodology updates the marginal losses without solving a new ac base point so that the optimal solution accurately reflects system losses. Previously proposed methodologies require nonlinear programming solvers, additional ac power flow solutions, or are less accurate compared to actual losses, and they only give results for one or two test networks. This paper provides results on nine different test networks. The key advantage of the proposed methodology is that it can be easily integrated into current market software. [ABSTRACT FROM AUTHOR]

Power system operation will encounter numerous variabilities as the proliferation of renewable energy continues. Such random events will require the evaluation of corresponding variables and the assessment of their impacts on the monitoring and the control of stochastic power systems. In this paper, a global sensitivity analysis (GSA) method is proposed to perform a priority ranking of renewable energy variabilities that will affect the voltage stability of power systems. First, a probabilistic model for the load margin calculation is presented considering the renewable power generation. Then, GSA is applied to models with correlated random input variables and the importance index is designed for evaluating the impacts of such variables. Next, the stochastic response surface method is adopted in GSA to improve the computation efficiency of the proposed evaluation method. Finally, the overall procedure is presented to identify critical variables that can affect the variability of load margins in voltage stability analyses. The proposed method is applied to power systems with a large penetration of renewable power and the influences of critical variabilities on voltage stability are analyzed. In this paper, the proposed method is tested using the IEEE 9-bus and the IEEE 118-bus systems, and its accuracy is compared with those of the local sensitivity analysis method and the commonly used GSA methods. [ABSTRACT FROM PUBLISHER]

This paper presents a fundamental study of voltage collapses that occur on a post-fault trajectory of a stressed power system in seconds after large disturbances. The focus of the study are voltage collapses that are induced by certain load models. Using an n-machine-N-bus power system model, the paper explicitly shows that the voltage collapse is caused by the non-existence of a real, positive solution for a load voltage magnitude in different areas of a relative rotor angle space when the load is of non-linear type. These “areas without voltage solution” are denoted as Voltage Impasse Regions (VIR) and are mathematically characterized as trigonometric functions of (n -1) relative rotor angles. Once the post-fault trajectory enters a VIR, voltage magnitude solutions become complex or negative, the algebraic Jacobian becomes singular, and the behaviour of a system becomes undefined. The case study has been carried out using a simple 3-machine-1-load system with static load models. In the study, VIR appeared and enlarged as the non-linear (constant power and constant current) load increased. Furthermore, the non-convergence of time-domain solution occurred exactly at VIR, thereby confirming that the problem is of structural nature. [ABSTRACT FROM PUBLISHER]

This paper proposes a multi-agent deep reinforcement learning-based approach for distribution system voltage regulation with high penetration of photovoltaics (PVs). The designed agents can learn the coordinated control strategies from historical data through the counter-training of local policy networks and centric critic networks. The learned strategies allow us to perform online coordinated control. Comparative results with other methods show the enhanced control capability of the proposed method under various conditions. [ABSTRACT FROM AUTHOR]

Conventional droop control methods for power-sharing in a multi-terminal high voltage DC (MTDC) grid lead to voltage deviation from the nominal value. Moreover, the power-sharing is inaccurate in the droop-controlled MTDC system. This paper proposes a secondary controller with a distributed architecture to compensate the voltage deviation and to achieve equal power sharing automatically among the converter stations. A distributed observer is used to estimate the average voltage of the converter stations. The proposed distributed controller and observer use local measurements of output powers and voltages, and only communicate with neighboring stations. Therefore, the requirement of the global information in the centralized secondary control schemes is eliminated, which reduces the communication requirement and improves the reliability of the MTDC grid. The case studies illustrate that the proposed distributed controller regulates the stations’ average voltage and shares the power mismatch accurately. Impact of the communication time-delays and the control gain on stability of the MTDC grid are also investigated using the Lyapunov-KrasovskiiLMI condition. It is shown that reducing the control gain can stabilize the MTDC grid in the case of large communication time-delays. [ABSTRACT FROM AUTHOR]

This paper describes the two test systems for voltage stability studies set up by the IEEE PES Task Force on “Test Systems for Voltage Stability Analysis and Security Assessment” under the auspices of the Power System Stability Subcommittee of the Power System Dynamic Performance Committee. These systems are based on previous test systems, making them more representative of voltage stability constraints. A set of representative results are provided for both systems, with emphasis on dynamic simulation. They illustrate various aspects such as long-term dynamics, voltage security assessment, real-time detection, and corrective control of instabilities. The value for educators, researchers and practitioners are emphasized. [ABSTRACT FROM AUTHOR]

This paper proposes two new distributed fault-tolerant control (FTC) algorithms for the restoration of voltage and frequency in autonomous inverter-interfaced AC microgrids (MGs). The proposed control schemes give fault-tolerance capability to the system against different potential faults in sensors and actuators. In the first algorithm, a distributed adaptive fault-tolerant method is employed to compensate for the potential sensor faults. Then, to address both sensor and actuator faults simultaneously, a distributed ${H_\infty }$ protocol is employed to guarantee the voltage and frequency synchronization for the closed-loop system. In the design of these algorithms, there is no need to know the amplitude or any quantitative information about fault signals. Additionally, there is no restriction on the number of faulty units. Finally, to evaluate the performance of the proposed distributed cooperative fault-tolerant control algorithms, simulation studies are carried out on a test MG system, including several distributed generation (DG) units in MATLAB/Simulink environment and also the results are compared with several previously-reported methods. Simulation results and comparison with previous works reveal the effectiveness and accuracy of the proposed method in regulating MG voltage and frequency and providing accurate proportional active power-sharing. [ABSTRACT FROM AUTHOR]

This paper focuses on power system stability issues arising under adverse network conditions requiring support from wind farm (WF) electronic converters. The specific instability mechanism investigated refers to a WF participating in emergency reactive support to enhance long-term voltage stability of a weak transmission network. During this support the WF converter may be operating under maximum current limit, in which case it is shown that the WF can become unstable. An aggregate WF equivalent model for voltage stability studies is derived, so as to simplify power system modeling. Protection schemes are proposed to avoid the above-mentioned instability, taking into account the WF converter and pitch control operation. Finally, a typical feeder connecting a WF taken from the Hellenic Interconnected System is simulated as an illustrative case study and the efficiency of the protection schemes proposed is determined. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient dc voltage control scheme in rail transit traction power systems with reversible converters for dc voltage regulation and power sharing. The proposed dc voltage control scheme is executed in a hierarchical structure based on the optimal power flow. Unlike conversional constant dc voltage control applied in traction power systems, this scheme allows the reversible converters operating in both rectifier and inverter regions and considers regenerative braking power sharing among multiple traction substations. The steady-state equivalent models of traction power systems including reversible converters are established, and the ac/dc sequential power flow algorithm based on Newton–Raphson method is presented. Finally, a multi-trains dynamic operation simulation is carried out with Matlab. The simulation results prove the validity of proposed scheme and indicate that the system energy saving effect in traction power systems with reversible converters is obvious with proposed scheme. [ABSTRACT FROM AUTHOR]

Based on the knowledge accumulated off-line and feature extractions, a novel data-based learning and control method is proposed for the long-term voltage stability problem in this paper. All the spatial-temporal data is considered and the features of different emergency events are extracted by principle component analysis which can reduce the dimension and reveal the significant internal structure of the data. An artificial neural network is used to build a classifier to reinforce the relationship directly between the system dynamics and optimal control actions. With the prepared control knowledge, it is faster to find an optimal control action online with a good system performance. Simulation results on the 6-bus system, New England 39-bus system and Iceland 189-bus system are given to show the potential of this method for on-line control. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of network structures on small-disturbance voltage stability of power systems in the long-term. A differential-algebraic model is established in terms of network topology characteristics and the aggregate nonlinear recovery load model. We define the weighted load connectivity (WLC) as an index to indicate the stability of network structures. Then robust stability assessment is used to eliminate the impact of uncertain recovery time of loads. The Monte Carlo method is used to study the relationship between WLC and small-disturbance voltage stability (SDVS) for a broad range of network topologies and parameters. We discover from the simulation results that the network with a larger value of WLC has a stronger ability to maintain SDVS. To further study the impact of renewable energy sources (RESs), we improve the system model by including an inverter-based distributed generator in parallel with each aggregated nonlinear dynamic load. The simulation results of the Hong Kong power grid show that the WLC can still indicate the stability of network structures effectively, and the systems with more stable network structures are less impacted by the penetration of RESs. The proposed WLC appears useful in providing guidance for power network planning and operation. [ABSTRACT FROM AUTHOR]

The conventional voltage observer based distributed control can make a tradeoff between voltage restoration and reactive power sharing. However, it suffers from estimation error when there exist input disturbances, such as initial values and communication delays. To address this problem, this paper proposes a novel distributed secondary control based on PI consensus algorithm. A voltage controller and a frequency controller are designed separately to realize the restoration of voltage/frequency and also accurate reactive/active power allocation. Moreover, a detailed small-signal model with PI consensus algorithm is established to show the impact of the proposed control strategy on the system stability. Compared with the conventional distributed control, the proposed control scheme is simpler with higher control accuracy under input disturbances. Simulations are conducted to verify the effectiveness of the proposed control strategy in an isolated ac microgrid. [ABSTRACT FROM AUTHOR]

In this paper, we develop a data-driven framework for controlling distributed energy resources (DERs) in a balanced radial power distribution system with the objective of regulating voltages across the whole system. The objective is to determine optimal DER power injections that minimize the voltage excursions outside a desirable voltage range without knowing a complete model of the power distribution system. To this end, we approximate the nonlinear relationship between the voltage magnitudes and the power injections by a linear model. The parameters of this linear model—referred to as the voltage sensitivities—can be computed using information on the network topology and the line parameters, the values of which will be estimated. Assuming the knowledge of feasible network topology configurations and distribution line resistance-to-reactance ratios, we propose a framework for identifying the true network topology configuration and the corresponding line parameters using only a few measurements of voltage magnitudes and power injections. Utilizing the estimated voltage sensitivities, the optimal DER power injections can be readily determined by solving a convex optimization problem. Due to its data-driven nature, the proposed framework is intrinsically adaptive to changes in system conditions such as unknown topology reconfiguration. The effectiveness of the proposed framework is validated via numerical simulations on the IEEE 123-bus distribution test feeder. [ABSTRACT FROM AUTHOR]

Modular Multilevel Converter based High Voltage Direct Current (MMC-HVDC) connected offshore wind farms could suffer serious challenges: DC overvoltage during a fault and post-fault DC voltage restoration. In this paper, to mitigate DC overvoltage, a two-stage voltage drop control scheme is proposed for offshore MMC to realize a fast active power reduction, by coordinating with a voltage-dependent active current control of individual wind turbines. The voltage drop depths are designed by considering the offshore de-loading efficiency and the stability of WTs. To improve the post-fault DC voltage recovery performance, an adaptive voltage rise control scheme is proposed to coordinate the recovery of onshore and offshore active power. The recovery trajectory of DC voltage is formulated and further employed to design the onshore active power ramp rate for uninterrupted operation of WTs. Case studies have been conducted on two test systems to validate the proposed method. [ABSTRACT FROM AUTHOR]

Modern grid codes demand the integration of voltage support capability with photo-voltaic (PV) generators to ensure a secure operation of power systems. On the other hand, short-term voltage instability (STVI) of distribution networks (DNs) is one of the key issues to be addressed. It can occur due to high proportion of induction motor loads. However, the existing literature lacks a thorough analysis of short-term voltage stability (STVS) of DNs following an asymmetrical fault. Furthermore, an effective voltage-support strategy for PV units, which can improve the STVS while mitigating the excessive voltage swell, is essential for secure operation. Hence, firstly this paper thoroughly investigates the STVS of DNs subjected to asymmetrical faults. It is perceived that voltage support through conventional methods can increase the risk of STVI and excessive voltage swell. Secondly, a new voltage-support strategy is proposed based on the negative sequence voltage at point of common coupling (PCC) aimed at mitigating the STVI and regulating the phase voltages within the margins. The key features of the proposed strategy are, fast and accurate estimation of the network's impedance at PCC is not required and it can be easily re-designed considering the network's dynamic behaviors. The efficacy of the proposed method is validated on two IEEE benchmark test systems, and the results demonstrate the effectiveness in improving the STVS and alleviating over voltage issues. [ABSTRACT FROM AUTHOR]

Stalling of residential air conditioners (RACs) following a transient fault can delay the voltage recovery ranging from 3 to 20 seconds. This phenomenon is referred to as fault-induced delayed voltage recovery (FIDVR). Several aggregated RAC models have been presented to replicate the actual FIDVR events. However, they usually have two main drawbacks as: i) considering independent stalling voltage and stalling time for all RACs, ii) resulting in only two ultimate modes; either 100% stalled or 100% normal running. This paper amends the abovementioned shortcomings by proposing a simple and effective performance-based RAC model. The proposed model utilizes a simple explicit relation between the stalling voltage and its required time to stall the RAC, furthermore, it can stall a fraction of RACs based on the voltage dip characteristics. The experimental results support the proposed model and computer simulations employing the IEEE 118-bus test system and Iran's electricity grid reveal the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

This paper addresses the optimal allocation of the electric spring (ES) smart load device in radial distribution systems for voltage regulation. An ES can transform a connected noncritical load into a smart load providing voltage support and voltage suppression functions. A risk-limiting ES planning method is proposed to obtain the optimal ES configuration (number, locations, capacities, and types) to mitigate the voltage violations caused by uncertainties in renewable distributed generation. The forecasting uncertainties are placed into multi-state discrete levels to reduce scenario numbers. The voltage regulation capability of different types of ES are quantified and compared to determine the optimal allocation model. The optimal ES installation plan is identified as per the minimal total cost and lowest voltage violation risk. The proposed optimal allocation method is validated on a modified IEEE 15-bus distribution network. [ABSTRACT FROM AUTHOR]

Volatile voltage profiles in distribution systems caused by the fluctuating nature of renewable distributed generation (DG) are attracting growing concern. In this paper, we develop a new formulation of network reconfiguration to mitigate voltage volatility. It provides new insights into the voltage regulation problem in distribution systems with high renewable penetration, which is commonly addressed by power electronic controllers. From the linear DistFlow equations, we first propose a novel index that measures the voltage volatility of each bus in the system. This index is a function of distribution network parameters that characterizes the role of network structure in voltage volatility. Then, we formulate a new reconfiguration model that minimizes the network loss and restricts the voltage volatility indices with the coordination of switched capacitor banks. A Benders decomposition-based approach is designed to solve the problem using mixed-integer quadratic programming. The simulations on the IEEE 69-bus system show that the reconfiguration scheme is able to: first, minimize network loss when DG outputs are as predicted; and second, significantly reduce the risk of voltage violations when DG outputs deviate from the prediction. The proposed formulation unleashes the distinctive power of network reconfiguration in reducing voltage volatility, by which the cost of power electronic controllers can be saved. [ABSTRACT FROM AUTHOR]

This paper proposes a voltage stability index (VSI) suitable for unbalanced polyphase power systems. To this end, the grid is represented by a polyphase multiport network model (i.e., compound hybrid parameters), and the aggregate behavior of the devices in each node by Thévenin equivalents (TEs) and polynomial models (PMs), respectively. The proposed VSI is a generalization of the known $L$ -index, which is achieved through the use of compound electrical parameters, and the incorporation of TEs and PMs into its formal definition. Notably, the proposed VSI can handle unbalanced polyphase power systems, explicitly accounts for voltage-dependent behavior (represented by PMs), and is computationally inexpensive. These features are valuable for the operation of both transmission and distribution systems. Specifically, the ability to handle the unbalanced polyphase case is of particular value for distribution systems. In this context, it is proven that the compound hybrid parameters required for the calculation of the VSI do exist under practical conditions (i.e., for lossy grids). The proposed VSI is validated against state-of-the-art methods for voltage stability assessment using a benchmark system, which is based on the IEEE 34-node feeder. [ABSTRACT FROM AUTHOR]

Uncertain power sources are increasingly integrated into distribution networks and causes more challenges for the traditional load modeling. A variety of distributed load components present dynamic characteristics with time-varying parameters. Toward the end, this paper proposes a robust time-varying parameter identification (TVPI) method for synthesis load modeling in distribution networks, including time-varying ZIP, induction motor, and equivalent impedance models. The nonlinear optimization model is developed and solved by the nonlinear least square (NLS) to find the minimum error between estimated outputs and measurements. To cope with TVPI deteriorated by voltage disturbances, dynamic programming is first used to detect the disturbance. Then, a robust TVPI engine is designed to constrain the estimated time-varying parameters within a stable range. Furthermore, advanced tolerance thresholds are also required during iterations of NLS. Numerical simulations on the 9- and 129-bus distribution systems verify the effectiveness and robustness of the proposed TVPI method. Also, this method can be robust to the ambient noise of measurements. [ABSTRACT FROM AUTHOR]

This paper first presents an optimization model to flexibly control available plug-in electric vehicle (PEV) battery charging/discharging power based on three-phase power flow and sensitivity approaches. This model can achieve one of the two goals: 1) minimizing both battery charging/discharging cost and extra battery degradation cost due to vehicle-to-grid (V2G) activities (cost-reduction strategy); 2) maximizing local peak load shifting and minimizing extra battery degradation cost due to V2G activities (peak-shifting strategy). The first strategy can determine the appropriate charging/discharging rates of an available PEV battery in order to benefit both the PEV owners and the distribution utilities for the day ahead. The second strategy can reduce the peak loads of the system. Both strategies can improve the power quality at the same time. With the help of a sensitivity method, most of the nonlinear constraints are transformed into linear constraints, and the number of constraints is reduced in the model. An interior point optimization approach is utilized to solve the optimization model. The optimization model is modified further to address unexpected PEV connections and travel scenarios during operation. The effectiveness and accuracy of the proposed method are demonstrated and verified on a 75-node test feeder. [ABSTRACT FROM AUTHOR]

This paper analyzes the delayed voltage recovery phenomenon by simplifying the western electricity coordinating council composite load model using the load admittance and the thermal relay dynamics. From this analysis, a closed form expression approximating the recovery time is derived and the key load parameters impacting the behavior of voltage recovery are identified. A monitoring scheme based on the measured load admittance is then proposed to detect the onset of stalling, even in the presence of voltage oscillations, and estimate the duration of the delayed voltage recovery. A mitigation scheme utilizing smart thermostats and offline learning is also derived to ensure that the voltage recovers to the pre-contingency voltage within a specified time. Both the monitoring and mitigation schemes only need local measurements at a substation making them promising for online applications. Results for the monitoring and mitigation schemes are described in detail for the IEEE 162 bus system validating the various assumptions used for the analysis and establishing the connection between the delayed voltage recovery phenomenon and load admittance. [ABSTRACT FROM AUTHOR]

The PMU data is increasingly used in the grid monitoring system SCADA. As the DFT algorithm used in PMUs fails to distinguish the fundamental frequency signal with low-frequency interference, the low-frequency disturbance (LFD) included in fundamental frequency variable data, which are collected from PMUs, will affect the correctness of calculation and analysis of the power system's steady state. In order to extract the fundamental frequency variable from PMU data, taking low-frequency forced oscillation as an example, a method for filtering LFD in PMU data is proposed. First, the effect of low-frequency oscillation to the fundamental frequency variable is analyzed in this paper. Then, the component of LFD in PMU data is explained. By finding the maximum value and minimum value of voltage or current in PMU data to draw the envelopes and add them together, the mean value or fundamental frequency variable of voltage and current is obtained. The mechanism of error in calculating active power is analyzed when low-frequency oscillation occurs in the power grid. The results of analyzing actual PMU data under low-frequency oscillation verify the correctness of the method proposed in this paper. This method is of great significance to improve the accuracy of calculation in SCADA. [ABSTRACT FROM AUTHOR]

This paper presents a modeling approach for capturing closed-loop load behavior in distribution networks using bottom-up time-variant load models and incorporating load-flow feedback for thermal loads. Traditional load models are useful for providing insights into instantaneous changes in power, however, they do not capture the time-variant response to changes in voltage due to the effects of appliances with closed-control loops such as those which are thermostatically controlled. This paper proposes a modeling and co-simulation platform to simulate closed-loop load-modeling using state-of-the-art bottom-up load modeling techniques for the residential sector with a feedback model for time series steady-state load-flow. It incorporates time-variant load models and discrete state-space representation of thermostatically controlled appliances. The developed methodology is used in a conservation voltage reduction case study on an urban distribution network, allowing detailed assessment of the voltage response and analysis of changes in active and reactive power and network losses. [ABSTRACT FROM AUTHOR]

This paper focuses on the control of Modular Multilevel Converters (MMC) for High Voltage DC (HVDC) applications during unbalanced AC grid voltage sags where positive and negative sequence voltages are equal. The control scheme is based on six arm energy regulators, six independent current controllers, and two reference calculation stages that convert the power references into grid and inner current references. Conventional inner AC currents reference calculation fails if the amplitude of the positive and the negative sequence AC grid voltages are equal, a state which is referred to in this paper as singular voltage condition. This paper discusses the types of network faults that cause this condition and proposes three different solutions to operate the converter in such scenarios. The adequacy of the proposed solutions is validated through simulations considering each of the problematic fault scenarios. [ABSTRACT FROM AUTHOR]

Phase angle measurements from synchrophasors show discontinuities when they roll over from +180 to -180 degrees or vice versa. This paper proposes efficient strategies for unwrapping of the angles in real-time data streams. Examples presented in this paper first show that the phase angle differences across bus voltage phasors can go over 360 degrees in a synchronized power system under stressed conditions. Unwrapped phase angles are shown to be useful in fast reliable islanding detection methodology, and for phase angle arithmetic such as for averaging of phase angles and for phase angle difference calculations. Strategies for handling missing phase angle data in real-time data streams are also discussed. [ABSTRACT FROM PUBLISHER]

The method of symmetrical components is not effective for fault location in the case of untransposed lines, due to potential couplings between the sequence circuits. This paper proposes a non-iterative algorithm in the phase-coordinates for wide-area fault location on untransposed transmission networks. In doing so, first, an improved two-terminal method is suggested to accurately locate faults on untransposed lines. Next, an algorithm is proposed to infer voltage and current phasors at the faulted line ends without direct measurements, by taking advantage of the data provided by phasor measurement units (PMUs). Accordingly, the adverse effect of close instrument transformers transients on the estimation accuracy is minimized. Being highly nonlinear in terms of fault distance and impedance, the fault equations are derived and made linear in this paper by defining six suitable auxiliary variables. The resulting system of equations is solved using the least-squares method to obtain three-phase voltages and currents at the faulted line ends. A main feature of the proposed algorithm is that it only requires a limited number of current and voltage synchrophasors. An additional advantage of the proposed algorithm is that the faulted line is not required to be known a-priori. The proposed algorithm is validated using extensive simulation studies on the New England 39-bus test system, accounting for different fault locations, types and resistances. [ABSTRACT FROM PUBLISHER]

Conservation voltage reduction (CVR) has been traditionally applied adopting moderate settings at primary substations and when distributed generation was uncommon. However, as new infrastructure is deployed across European-style medium voltage (MV) and low voltage (LV) networks, driven by increasing photovoltaic (PV) penetration levels, the opportunity arises to develop more advanced CVR schemes. This paper proposes a centralized, three-phase AC optimal power flow (OPF)-based CVR scheme that, using monitoring, on-load tap changers and capacitors across MV and LV, actively manages voltages to minimize energy consumption, even with high PV penetration, while considering MV–LV constraints. To tackle scalability issues brought by discrete variables, a two-stage approach is proposed to solve the OPF as a non-linear programming problem (relaxing integer variables). A process that continuously checks customer voltages is adopted to trigger the optimization only when needed. Moreover, CVR benefits are not only quantified at a network level but also for customers, providing useful insights to policy makers. The proposed control is assessed using a realistic, unbalanced U.K. residential MV–LV network (2,400+ customers) with high PV penetration, and 1-min resolution time-varying profiles and load models. Results demonstrate that the proposed control effectively coordinates voltage regulation in MV and LV levels throughout the day, minimizing energy imports for all customers. [ABSTRACT FROM AUTHOR]

In this paper, we formulate and solve the ac optimal power flow (AC-OPF) as an equivalent circuit problem in terms of current, voltage, and admittance state variables. The generator models are represented using conductance and susceptance state variables, and the operational and network constraints are translated to corresponding current/voltage constraints without loss of accuracy or generality. To understand the physics behind the optimality conditions of the optimization problem, we extend the linear adjoint circuit theory to translate them to equivalent circuit domain. It is shown that the operating point that defines the equivalent circuit solution precisely represents an AC-OPF solution. We then further exploit the equivalent circuit representation to use power flow simulation techniques to robustly solve the optimization problem. The efficiency of our approach is demonstrated for several AC-OPF benchmark test cases (up to 70 k buses) under nominal and congested operating conditions, and the runtime and scalability properties are presented. [ABSTRACT FROM AUTHOR]

The ever-increasing utilization of sensitive loads in the industrial, commercial, and residential areas in distribution networks requires enhanced reliability and quality of supply. This can be achieved, thanks to self-healing features of smart grids that already include the control technologies necessary for the restoration strategy in case of a fault. In this paper, an analytical and global optimization model is proposed for the restoration problem. A novel mathematical formulation is presented for the reconfiguration problem reducing the number of required binary variables while covering more practical scenarios compared to the existing models. The considered self-healing actions besides the network reconfiguration are the nodal load-rejection, the tap setting modification of voltage regulation devices (incl. OLTCs, SVR, and CBs), and the active/reactive power dispatch of DGs. The voltage dependency of loads is also considered. Thus, the proposed optimization problem determines the most efficient restoration plan minimizing the number of de-energized nodes with the minimum number of self-healing actions. The problem is formulated as a Mixed-Integer Second Order Cone Programming (MISOCP) and solved using the Gurobi solver via the MATLAB interface YALMIP. A real 83–node distribution network is used to test and verify the presented methodology. [ABSTRACT FROM AUTHOR]

It is well known that a single (constant power) load infinite-bus system reaches a static voltage stability limit point, or equivalently, a singularity point of the power flow Jacobian, at the unity line-load admittance ratio, i.e., the equivalent admittance of the load has the same modulus as the transmission line admittance. In this paper, we rigorously extend this result to generic distribution systems with distributed generators (DGs). We introduce a new concept called the network-load admittance ratio that is in terms of the parameters of power network, loads, and DGs. This concept is a generalization of the line-load admittance ratio that characterizes the loading status of a distribution system with the effects of DGs included. We prove that the power flow Jacobian is singular if and only if the network-load admittance ratio is unity, which provides new insights into the mechanism of voltage stability. In addition, we establish a new voltage stability index by using the network-load admittance ratio. Numerical simulations on several IEEE test systems show that the index has good linearity with load increase and estimates voltage stability margin with high precision. The index also reflects the impact of DG penetration level and control mode on voltage stability. The obtained results can be extended to ZIP load models, unbalanced three-phase networks, and mesh networks with slight modifications. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new hierarchical control scheme for microgrid (MG) clusters, given by the interconnection of atomic dc MGs with ZIP loads, each composed by both grid-forming and grid-feeding converters. In the primary level, we develop a new Plug-and-Play (PnP) voltage/current controller in order to achieve simultaneous voltage support and current feeding function with local references. The coefficients of each stabilizing controller are characterized by explicit inequalities, which are related only to local electrical parameters of the MG. Moreover, we provide a sufficient condition on the ZIP loads to guarantee passivity and asymptotic stability of electric system. The robustness of performance to system uncertainties is also demonstrated. In the secondary level, a leader-based voltage/current controller is proposed to achieve both voltage and current regulation for the MG cluster without specifying the individual setpoints for each MG. The proposed distributed controller requires a communication network where each regulator exchanges information with its communication neighbors only. With the proposed scheme, each MG can plug-in/out seamlessly, irrespective of the power line parameters and models of other MGs. Closed-loop stability proof of MG clusters is formally proved independently of the cluster topology. Moreover, theoretical results are validated by extensive hardware-in-loop tests showing robustness of the closed-loop cluster against perturbations in the loads, PnP operations, and noises/delays in the communication network. [ABSTRACT FROM AUTHOR]

This paper investigates the enactment of battery energy storage system (BESS) and static compensator (STATCOM) in enhancing large-scale power system transient voltage and frequency stability, and improving power export capacity within two interconnected power systems. A PI-lead and lead-lag controlled BESS is proposed for multimachine power system to provide simultaneous voltage and frequency regulation within the defined battery state-of-charge ranges and an equivalent Finnish transmission grid is used to evaluate the system performance. According to Australian National Electricity Market grid requirements, the performances of the proposed control schemes are compared with conventional PI controlled BESS and STATCOM under multiple temporary and permanent fault conditions. In addition, two adjacent disturbance events are also applied to evaluate system performance with BESS and STATCOM. Through simulation results, it is shown that when there is a ${\text{44}\%}$ increase in power export and the STATCOM fails, incorporating BESS improves the performance and justifies the novelty of this study. Moreover, the proposed lead-lag controlled BESS manifests better transient performance than BESS with PI-lead and traditional PI controller, in the event of divergent temporary and permanent faults. [ABSTRACT FROM AUTHOR]

High penetration of distributed renewable energy introduces significant uncertainties to active distribution networks. Optimal control methods accounting for inherent uncertainties are needed to facilitate economic and reliable operation of active distribution networks. This paper proposes a stochastic receding horizon control method based on modified stochastic model predictive control framework to integrate high penetration of distributed generation. Multiple controllable resources are jointly optimized over a finite prediction horizon while ensuring relevant security restrictions. The simplified Z-bus sensitivity for active distribution networks is developed for computationally efficient estimation of system nonlinearity with high accuracy, and is combined with the sequential linear programming to iteratively derive the linear state space model for compensation of cumulative modeling errors. Furthermore, the voltage limitations are reformulated as chance constraints to indicate the probabilistic reliability index of voltage qualification rate, and achieve tradeoffs between cost reduction and voltage regulation. The affine-disturbance feedback control policy is leveraged here to enforce close-loop control performance and analytically transform intractable chance constraints into second-order cone constraints. Comprehensive case studies based on 33-bus and 123-bus distribution systems are carried out to demonstrate the capability and effectiveness of the proposed approach in terms of modeling accuracy, control performance, cost reduction, and method scalability. The proposed approach can effectively enforce voltage regulation against uncertainties with the prescribed probability level. Control costs and constraint violation can be reduced compared with deterministic model predictive control and open-loop control strategies. [ABSTRACT FROM AUTHOR]