Search

Volt-VAR and Volt-Watt functionality in photovoltaic (PV) smart inverters provide mechanisms to ensure system voltage magnitudes and power factors remain within acceptable limits. However, these control functions can become unstable, introducing oscillations in system voltages when not appropriately configured or maliciously altered during a cyberattack. In the event that Volt-VAR and Volt-Watt control functions in a portion of PV smart inverters in a distribution grid are unstable, the proposed adaptation scheme utilizes the remaining and stably-behaving PV smart inverters and other Distributed Energy Resources to mitigate the effect of the instability. The adaptation mechanism is entirely decentralized, model-free, communication-free, and requires virtually no external configuration. We provide a derivation of the adaptive control approach and validate the algorithm in experiments on the IEEE 37 and 8500 node test feeders.

This work proposes a strategy that estimates the maximum distributed generation (DG) capacity that can be connected to the electric distribution system (EDS), when EDS upgrading actions are implemented. The problem is viewed from the distribution system operator (DSO) perspective and is formulated as a multiobjective optimization model that maximizes the DG capacity and minimizes the upgrading cost. Upgrading options include allocation of voltage regulators (VRs) and conductor replacement, which are coordinated with the application of generation curtailment, DG reactive power support, and voltage control using VRs. The uncertainty and variability of demand and DG power production are accounted for resorting to a multi-period robust formulation. The problem solution generates a set of upgrading plans, from which the DSO can select the one that meets its economic expectation and provides the EDS with the necessary capacity to accommodate the expected new DG. A post-optimization analysis is proposed to evaluate the impact of EDS upgrading on the DSO profit. Simulations are performed on a 135-bus EDS, and results show that the proposed strategy reveals an upgrading plan that increases the DG capacity up to 64.39% with a gain in the DSO profit of 5.43%, compared to the case without EDS upgrading. [ABSTRACT FROM AUTHOR]

PV curves are generally obtained by considering lumped models of transmission lines. This approximated model can yield an inaccurate estimation of the maximum loading condition of the system. This letter shows that accuracy can be improved by considering line models with uniformly distributed parameters. Analytical evaluations of the PV curve and of the voltage collapse point of a two-bus system are obtained by applying the Ossanna's theorem. Then the impact of different line models on large-scale systems is evaluated through a continuation power flow analysis of a real-world model of the Sicilian transmission system including the Sicily-Malta 120 km cable connection. [ABSTRACT FROM AUTHOR]

With the growing penetration of distributed renewable energy, distributed control approaches are widely utilized in voltage control of active distribution networks (ADNs), suffering from limited applicability for control devices or heavy communication burden. This paper develops an innovative distributed voltage control strategy of ADNs with global sensitivities (DVC-GS), which integrates network information from a global optimization view to coordinate energy storages, PV inverters and the OLTC with little communication and computing time. The global sensitivities of voltage violations across all buses with respect to nodal voltage and active/reactive power injection are formulated to quantify the ability of each controllable resource for alleviating voltage violations in the entire ADN. The back-and-forth communication combined with the modified DistFlow model is newly developed for the real-time update of global sensitivities at each bus with high accuracy and no iteration. Then the coordinated control of various devices is implemented on basis of global sensitivities to effectively ensure voltage security of ADNs. Comprehensive simulations based on modified 11-bus and 123-bus systems demonstrate the significant efficiency and superiority of the global sensitivities and DVC-GS. [ABSTRACT FROM AUTHOR]

Being important information of both network conditions and energy trading, distribution locational marginal prices (DLMPs) are greatly useful for distribution network (DN) management. The goal of this paper is to develop a market mechanism that motivates price-making agents to trade active and reactive power at DLMPs. According to the optimal power flow problem based on second-order cone (SOC) relaxation, we first design the market rules that allow agents to strategically submit proposals of price and power generation/consumption. The market rules induce a noncooperative game between the DN operator and distributed generators. We prove that DLMP pricing can be implemented at any generalized Nash equilibrium (GNE) of the game. We also show that economic properties of strong budget balance, individual rationality, and system cost minimization can be achieved at any GNE. A decentralized algorithm is developed to reach a GNE of the game. Further, based on the convex-concave procedure, an extension of the market mechanism is proposed to cope with the situations that SOC relaxation is inexact. In simulation, the proposed market mechanism is compared with other game-theoretic models, and the economic properties are verified. [ABSTRACT FROM AUTHOR]

Despite cascading failures being the central cause of blackouts in power transmission systems, existing operational and planning decisions are made largely by ignoring their underlying cascade potential. This paper posits a reliability-aware AC Optimal Power Flow formulation that seeks to design a dispatch point which has a low operator-specified likelihood of triggering a cascade starting from any single component outage. By exploiting a recently developed analytical model of the probability of component failure, our Failure Probability-constrained ACOPF (FP-ACOPF) utilizes the system’s expected first failure time as a smoothly tunable and interpretable signature of cascade risk. We use techniques from bilevel optimization and numerical linear algebra to efficiently formulate and solve the FP-ACOPF using off-the-shelf solvers. Extensive simulations on the IEEE 118-bus case show that, when compared to the unconstrained and N-1 security-constrained ACOPF, our probability-constrained dispatch points can significantly lower the probabilities of long severe cascades and of large demand losses, while incurring only minor increases in total generation costs. [ABSTRACT FROM AUTHOR]

This paper proposes an online voltage control strategy of distributed energy resources (DERs), based on the projected Newton method (PNM), for unbalanced distribution networks. The optimal Volt/VAr control (VVC) problem is formulated as an optimization program, with the goal of maintaining the voltage profile across the network by coordinating the VAr outputs of DERs. To overcome the slow convergence rate of conventional gradient-based methods, a PNM-based solution algorithm is developed to solve this VVC problem. It utilizes a non-diagonal symmetric positive definite matrix, developed from the Hessian matrix of the objective, to scale the gradient, and thus a fast convergence performance can be expected in this Newton-like algorithm. Moreover, taking advantage of the instantaneous feedback of voltage measurements, the online implementation of the PNM-based VVC is further designed to deal with fast system variations. In this online PNM-based VVC scheme, each bus agent communicates the instantaneous voltage measurements to the central agent, and the central agent communicates the VAr output commands of DERs back to each bus agent. The fast convergence performance of PNM results in a stronger capability to track the system variations in real time. Finally, numerical case studies are performed to validate the effectiveness, superiority, and scalability of the proposed method. [ABSTRACT FROM AUTHOR]

Severe geomagnetic disturbances (GMDs) increase the magnitude of the electric field on the Earth’s surface (E-field) and drive geomagnetically-induced currents (GICs) along the transmission lines in electric grids. These additional currents can pose severe risks, such as current distortions, transformer saturation and increased reactive power losses, each of which can lead to system unreliability. Several mitigation actions (e.g., changing grid topology) exist that can reduce the harmful GIC effects on the grids. Making such decisions can be challenging, however, because the magnitude and direction of the E-field are uncertain and non-stationary. In this paper, we model uncertain E-fields using the distributionally robust optimization (DRO) approach that determines optimal transmission grid operations such that the worst-case expectation of the system cost is minimized. We also capture the effect of GICs on the nonlinear AC power flow equations. For solution approaches, we develop an accelerated column-and-constraint generation (CCG) algorithm by exploiting a special structure of the support set of uncertain parameters representing the E-field. Extensive numerical experiments based on “epri-21” and “uiuc-150” systems, designed for GMD studies, demonstrate (i) the computational performance of the accelerated CCG algorithm, (ii) the superior performance of distributionally robust grid operations that satisfy nonlinear, nonconvex AC power flow equations and GIC constraints, in comparison with standard stochastic programming-based methods during the out-of-sample testing. [ABSTRACT FROM AUTHOR]

The wide variety of inverter control settings for solar photovoltaics (PV) causes the accurate knowledge of these settings to be difficult to obtain in practice. This paper addresses the problem of determining inverter reactive power control settings from net load advanced metering infrastructure (AMI) data. The estimation is first cast as fitting parameterized control curves. We argue for an intuitive and practical approach to preprocess the AMI data, which exposes the setting to be extracted. We then develop a more general approach with a data-driven reactive power disaggregation algorithm, reframing the problem as a maximum likelihood estimation for the native load reactive power. These methods form the first approach for reconstructing reactive power control settings of solar PV inverters from net load data. The constrained curve fitting algorithm is tested on 701 loads with behind-the-meter (BTM) PV systems with identical control settings. The settings are accurately reconstructed with mean absolute percentage errors between 0.425% and 2.870%. The disaggregation-based approach is then tested on 451 loads with variable BTM PV control settings. Different configurations of this algorithm reconstruct the PV inverter reactive power timeseries with root mean squared errors between 0.173 and 0.198 kVAR. [ABSTRACT FROM AUTHOR]

Reliability evaluation has developed a trend of embedding unit commitment to replace power flow for more accurate operation strategies, while its potential reverse, embedding reliability evaluation in unit commitment, has yet to see equal exploration. This unrecognized, yet meaningful, technical attempt will encounter modeling and computational burden, largely caused by the recursive function and non-convex structure of numerical reliability evaluation equipped with the necessary repair mechanism. To tackle this challenge, this study proposes a linear routine that overcomes the non-convexity of reliability evaluation and accommodates it in unit commitment, which is expected to bring optimal operation and reliability evaluation to a new era by enabling them both conducted at the same pace. [ABSTRACT FROM AUTHOR]

This letter proposes an analytical method to estimate the frequency of buses of transmission grid based on updated generator speed, internal generator voltages, admittance matrix and bus voltages. The proposed method estimates the buses frequency which are much more reliable, accurate and efficient for transient stability studies in contrast to other existing methods. To demonstrate the efficiency of the proposed approach, the method is applied on IEEE 39 bus test system for frequency support and is compared to other existing methods. [ABSTRACT FROM AUTHOR]

It was reported in the literature that the strong duality does not hold in general for the second-order conic program (SOCP) based AC optimal power flow in radial networks, which challenged many robust and stochastic methods using the dual form of SOCP. However, the letter shows that this viewpoint is wrong. In fact, SOCP does have a strong duality in general. Moreover, we give strict proof and counterpart examples to show the tightness of the strong duality. Finally, we investigate that the wrong conclusion in the literature is mainly resulted from a wrong duality form. The conclusion of this letter will support the utilizations of duality in SOCP based robust or stochastic optimization models. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel control approach for dynamic virtual power plants (DVPPs). In particular, we consider a group of heterogeneous distributed energy resources (DERs) which collectively provide desired dynamic ancillary services such as fast frequency and voltage control. Our control approach relies on an adaptive divide-and-conquer strategy: first, we disaggregate the desired frequency and voltage control specifications of the aggregate DVPP via adaptive dynamic participation matrices (ADPMs) to obtain the desired local behavior for each device. Second, we design local linear parameter-varying (LPV) $\mathcal {H}_\infty$ controllers to optimally match this local behaviors. In the process, the control design also incorporates the physical and engineered limits of each DVPP device. Furthermore, our adaptive control design can properly respond to fluctuating device capacities, and thus include weather-driven DERs into the DVPP setup. Finally, we demonstrate the effectiveness of our control strategy in a case study based on the IEEE nine-bus system. [ABSTRACT FROM AUTHOR]

This work presents the modelling fundamentals to study the dynamics of inverter-based resources (IBRs) in weak distribution grids and derive disturbance performance characteristics describing how they should behave under different conditions. More specifically, with respect to small-signal disturbances we study the possible voltage violations following frequency response from IBRs due to low system strength and also propose specific design requirements for IBR d–q current control to guarantee a stable response. In the context of large-signal disturbances, we highlight how active power-voltage control may not be effective due to a delay imposed by the physical features of the distribution network. Further, we mathematically discuss how IBR reactive power control could enhance its phase-locked loop stability. The proposed disturbance performance characteristics are then integrated into the IBR converter control via a novel voltage-priority reference generation strategy. Simulation results on a real Australian network show the efficacy of the proposed operational and control design requirements, and highlight possible unexpected active/reactive power interactions in weak distribution grids. [ABSTRACT FROM AUTHOR]

Optimal Volt/VAR control (VVC) in distribution networks relies on an effective coordination between the conventional utility-owned mechanical devices and the smart residential photovoltaic (PV) inverters. Typically, a central controller carries out a periodic optimization and sends setpoints to the local controller of each device. However, instead of tracking centrally dispatched setpoints, smart PV inverters can cooperate on a much faster timescale to reach optimality within a PV inverter group. To accommodate such PV inverter groups in the VVC architecture, this paper proposes a bi-level optimization framework. The upper-level determines the setpoints of the mechanical devices to minimize the network active power losses, while the lower-level represents the coordinated actions that the inverters take for their own objectives. The interactions between these two levels are captured in the bi-level optimization, which is solved using the Karush-Kuhn-Tucker (KKT) conditions. This framework fully exploits the capabilities of the different types of voltage regulation devices and enables them to cooperatively optimize their goals. Case studies on typical distribution networks with field-recorded data demonstrate the effectiveness and advantages of the proposed approach. [ABSTRACT FROM AUTHOR]

The time required to restore distribution systems following an extreme event is highly dependent on damage assessment. Waiting for field assessors patrolling the feeders to identify fault locations is a bottleneck in improving restoration efficiency. This paper proposes an optimal service restoration model for resilient distribution systems considering the coordination with damage assessment, as a contribution to earlier studies. The restoration actions such as fault isolation, network reconfiguration, crew mobilization and fault repair are brought forward to the damage assessment stage and the restoration schedules are dynamically updated with the reveal of the damage status. The relationship between fault location, switch status and node status is established to optimize the network topology and guarantee crew operation safety under the condition that the network has multiple faults or unchecked potential faulted areas. Moreover, the crew routing formulations are modified to enable fault isolation and load island reconnection by manual switches during the restoration process. Case studies validate the effectiveness of the proposed model in reducing load shedding and restoration duration. [ABSTRACT FROM AUTHOR]

This paper proposes an optimization approach for day-ahead reactive power planning to improve voltage security in transmission networks. The problem is formulated as a voltage-secure multi-period optimal reactive power dispatch (MP-ORPD) problem. The optimization approach searches for optimal set-points of dynamic and static reactive power (var) resources. Specifically, the output includes set-points for switching shunts, transformer taps, and voltage magnitudes at the regulated buses. The primary goal is to maximize the dynamic reactive power reserve of the system, by minimizing the reactive power supplied by synchronous generators. As the size of the MP-ORPD problem increases significantly with increasing number of contingencies and time periods, efficiency is crucial for practical applications. In this paper, a decomposition technique based on consensus and alternating optimization, where integer variable targets are obtained via MILP, is used to partition the MP-ORPD problem into a set of subproblems, which can be solved in parallel to reduce the computation time. The proposed MP-ORPD problem and its solution algorithm are integrated into the EPRI-VCA software. The results of various power networks of large electric utilities in the Eastern interconnection demonstrate the effectiveness of the proposed algorithm in providing preventive control schedules. [ABSTRACT FROM AUTHOR]

The paper establishes convergence properties of decentralized and distributed control strategies that use a Steinmetz-based technique for mitigating voltage unbalance on distribution feeders. Reactive power from distributed energy resources (DERs), such as solar photovoltaic (PV), is used to balance voltages at critical nodes in the distribution network. Interactions between controllers are analyzed and a theoretical guarantee is derived for stability of the control algorithms. This is achieved using Banach fixed-point theory. Providing such convergence results ensures robustness of the proposed control algorithms in realistic settings where parameters are uncertain and/or slowly varying, disturbances are prevalent, and control and measurement signals are prone to delays. The convergence results are evaluated on three test distribution networks. [ABSTRACT FROM AUTHOR]

Microgrid's voltage regulation is of particular importance during both grid-connected and islanded modes of operation. Especially, during the islanded mode, when the support from the upstream grid is lost, stable voltage regulation is vital for the reliable operation of critical loads. This paper proposes a robust and data-driven control approach for secondary voltage control of AC microgrids in the presence of uncertainties. To this end, unfalsified adaptive control (UAC) is utilized to select the best stabilizing controller from a set of pre-designed controllers with the minimum knowledge required from the microgrid. Two microgrid test systems are simulated in MATLAB to verify the effectiveness of the proposed method under different scenarios like load change and communication link failure. [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]

Distribution power systems (DPSs) are generally unbalanced, and their loads may have notable static voltage characteristics (ZIP loads). Hence, although many papers have focused on linear single-phase power flow models, it is still necessary to study linear three-phase distribution power flow models. This paper proposes a data-driven-aided linear three-phase power flow model for DPSs. We first formulate how to amalgamate data-driven techniques into a linear power flow equation to establish our linear model. This amalgamation makes our linear model independent of the assumptions commonly used in the literature (e.g., nodal voltages are nearly 1.0 p.u.); therefore, our model is characterized by relatively high accuracy, even when the assumptions become invalid. We then demonstrate how to apply our model to DPSs with ZIP loads. We also show that with the Huber penalty function employed, the adverse impact of bad data on our model's accuracy is significantly reduced, rendering our model robust to poor data quality. Case studies demonstrate that our model is generally more accurate, with 2- to 100-fold smaller errors, than most existing linear models, and remains fairly accurate even under poor data conditions. Our model also contributes to a rapid solution to DPS analyses and optimization problems. [ABSTRACT FROM AUTHOR]

This letter proves that a grid-following converter can stably connect to a weak grid even short-circuit ratio (SCR) is 1. Root instability causes of this grid-following control are identified including fast control response, insufficient damping, and slow voltage support. A simple and effective tuning method is proposed to stabilize this connection. Three control modes are considered in this tuning method including current control, active power and voltage ($ PV$) control, and active power and reactive power ($ PQ$) control. The switching model of a two-level converter is used for the simulation validation. [ABSTRACT FROM AUTHOR]

This letter presents a novel sequential black-start restoration model to improve the system resilience after a natural disaster in an active distribution network. Two challenges have been addressed: First, a new set of radiality constraints is designed as the network topology is changing along the restoration paths; Second, a black-start restoration model is proposed where multiple backup black-start units in the system are coordinated to find the best restoration paths. Case studies on two IEEE test systems verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Flexible transmission line impedances on one hand are a promising control resource for facilitating grid flexibility, but on the other hand add much complexity to the concerned optimization problems. This paper develops a convexification method for the AC optimal power flow with flexible line impedances. First, it is discovered that a flexible-impedance line is equivalent to a constant-impedance line linking a pair of transformers with correlated and continuously adjustable tap ratios. Then, with this circuit equivalent, the original optimization problem is reformulated into a semi-definite program under the existing convex relaxation framework, which improves the solution tractability and optimality in an easy-to-implement manner. The proposed method is verified by numerical tests on the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

This letter studies formulations on the safety regions of the voltage and reactive power (Volt/Var) of each bus in a power system by nonlinear network decomposition and proposes visualizations of these regions for operators to monitor the Volt/Var safety of the system. Unlike the conventional approach that searches for boundaries of such regions by a large number of repeated power flow calculations, the proposed method takes an analytical approach so as to avoid repeated calculations. Firstly, the power network is decomposed into a set of two-bus channels, where a complex-valued index is introduced to represent the Volt/Var status with each channel. Then, by using a scalable holomorphic embedding method, the trajectories of the indices of all channels are obtained, which together predict Volt/Var safety of the entire system under prospective operating conditions. Next, boundaries of the Volt/Var safety regions are derived and visualized to monitor the margin information of voltage stability and control. Finally, the effectiveness of the proposed method is validated on the IEEE 14-bus system in detail. [ABSTRACT FROM AUTHOR]

Bipolar VSC-MTDC is a promising solution to increase power transmission capacity and system reliability for large-scale renewable energy integration. However, traditional interpolar active power control methods cannot comprehensively explore the maximum transmission capability of the bipolar VSC-MTDC under abnormal operating conditions. Considering the flexibility of the bipolar VSC-MTDC that the positive-pole and negative-pole DC networks can be operated independently, a novel fault self-recovering control strategy is proposed in this paper to provide automatic, global and timely recovery solutions under various fault conditions: (a) Firstly, a coordinated time-driven and event-driven security monitoring, optimization and recovering control framework is proposed to guarantee the accuracy and speed of the corresponding calculation and control, hence to meet the timeliness requirement of fault self-recovery; (b) Secondly, a global optimal power allocation calculation method is proposed to automatically calculate the optimal power allocation between the positive-pole and negative-pole DC networks; (c) Thirdly, an interpolar active power dispatch method is proposed to realize the fault self-recovering control strategy based on primary control strategies of bipolar VSC-MTDC. Simulation results using MATLAB and PSCAD/EMTDC show that the proposed control strategy can timely and effectively enhance the overall power transmission capability for large-scale renewable energy integration after the fault. [ABSTRACT FROM AUTHOR]

Following an unforeseen disturbance in a power system, the system state should be known to extract the emergency voltage restoration strategy. Such a condition does not usually hold in distribution systems due to the lack of enough measurements. Here, the joint probability density function (pdf) of uncertain parameters is extracted from historical data. This pdf is updated to comply with the measurements. A set of samples is then generated that best models the updated pdf. These data reconciliation and sampling techniques enable the functioning of the emergency voltage control (evc) with measurement scarcity. They are designed to be fast enough to meet the quasi-real-time requirements of the intended application. The evc problem is cast as a stochastic programming problem. The resultant problem is a mixed-integer non-convex (and hence, NP-hard) optimization problem. It is solved using five distinct sms based on relaxation/approximation of the non-convex constraints. The results show that a novel combination of relaxation and approximation aimed at respectively mitigating the emergency under- and over-voltages outperforms the others. The propounded stochastic evc is validated through numerical studies. [ABSTRACT FROM AUTHOR]

Linear droop control is a standard approach for the decentralized operation of AC microgrids. While the traditional design of the real and reactive power droop functions does not consider economic aspects, recent approaches present modifications to enable least-cost operation. This paper proposes mixed-integer conic programming (MICP) for computing the real and reactive power droop parameters from a stochastic optimization framework that captures several snapshots of the microgrid’s operation. The model permits distributed generation to switch between grid-forming and grid-feeding modes. Unlike previous works, MICP provides droop parameters that are globally optimal for the design scenarios. Numerical results show that using traditional linear cost-based droop design methods may result in voltage magnitude violations. In contrast, the proposed method gives a solution free of violations and is yet more economical. [ABSTRACT FROM AUTHOR]

The increase in distributed energy resources and flexible electricity consumers has turned TSO-DSO coordination strategies into a challenging problem. Existing decomposition/decentralized methods apply divide-and-conquer strategies to trim down the computational burden of this complex problem, but rely on access to proprietary information or fail-safe real-time communication infrastructures. To overcome these drawbacks, we propose in this paper a TSO-DSO coordination strategy that only needs a series of observations of the nodal price and the power intake at the substations connecting the transmission and distribution networks. Using this information, we learn the price response of active distribution networks (DN) using a decreasing step-wise function that can also adapt to some contextual information. The learning task can be carried out in a computationally efficient manner and the curve it produces can be interpreted as a market bid, thus averting the need to revise the current operational procedures for the transmission network. Inaccuracies derived from the learning task may lead to suboptimal decisions. However, results from a realistic case study show that the proposed methodology yields operating decisions very close to those obtained by a fully centralized coordination of transmission and distribution. [ABSTRACT FROM AUTHOR]

Real-time detection of the microgrid stability is crucial for determining and adjusting the power-sharing droop control's gains to maintain a sufficient stability margin. Maintaining minimum relative stability should be ensured at different operating conditions to accommodate sudden system changes. This article develops a novel subspace-based identification technique to assess microgrid stability in real-time without relying on offline analytical small or large-signal models. Unlike conventional system identification techniques that require the introduction of external excitation (signal probing, load switching, or contingency event), the proposed method employs a simple internal routine through small and short-duration perturbations in the active power droop gain of inverter-based distributed generation (IBDG). The use of subspace identification does not require pre-defining the system's order, avoids the exhaustive computations associated with iterative identification methods and can handle a change of microgrid's network configuration. The proposed stability assessment method has been tested on an IBDG microgrid considering different operating conditions in MATLAB/Simulink. The accuracy of the proposed real-time stability assessment tool is determined by comparing the results to the analytically-derived small-signal model as well as the Matrix pencil and Prony methods. [ABSTRACT FROM AUTHOR]

Renewable Energy Sources (RESs) integration strengthens the need for a power network that can robustly handle the system’s uncertain scenarios. This paper proposes the first nonlinear novel dual-based bi-level approach for robust AC Transmission Expansion Planning (TEP) with uncertainties in RES generations and loads. It utilizes a convex relaxation and is solved by Benders Decomposition (BD), where the master determines the robust AC expansion plan. The novel dual slave for the second level of BD circumvents the issues in using conventional conic dual theory and aids in the worst-case realization of uncertainties using additional novel constraints. The proposed slave is solved using Interior Point Method (IPM), as it is not a mixed-integer problem. The proposed work includes additional linear constraints to speed up BD’s convergence and direct the master towards optimality. The approach is tested on several transmission systems, including the Indian Northern Regional Power Grid (NRPG) system. The robustness of the obtained plans is verified by Monte-Carlo Simulation (MCS) of the actual nonlinear and nonconvex AC Optimal Power Flow (OPF). The effect of the budget of uncertainty on the AC expansion plan is also investigated. A comparison with two previous works reveals the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Power systems are undergoing fundamental changes with increasing penetration of renewable energies. A reactive power ancillary service market is of significance to incentivize private providers, such as thermal power units and renewable power plants (RPPs), to participate in maintaining voltage security. Because of the local nature of reactive power, one of the recognized issues is that monopolistic participants may have great market power and strategically manipulate their costs. To pursue economic efficiency, this paper proposes an incentive-compatible mechanism based on Vickery-Clarke-Groves (VCG) auctions for the day-ahead reactive power ancillary service market. The obligations of reactive power ancillary service are quantified in the VCG-based market mechanism. Depending on the expected performance of participants compared with the corresponding obligations, payments are obtained for thermal power units, RPPs, and loads. Hence, providers have the incentive to declare their true costs and undertake obligations. Furthermore, a scarcity price is employed to reward the provision of scarce reactive power resources and ensure reliable market clearing. The proposed mechanism is illustrated using the IEEE 24-bus and 118-bus systems. The results verify the effectiveness of the proposed mechanism. Moreover, high rewards or penalties are observed for voltage weak areas, thereby inducing appropriate investments in reactive power capacities. [ABSTRACT FROM AUTHOR]

Inverter based islanded MicroGrids (MGs) are very fascinating but challenging ways to integrate Distributed Energy Resources (DERs) in electric networks. Active and reactive power regulation is a major issue due to the necessity of optimally exploiting the sources characteristics and controlling voltage and frequency. Focusing the attention on the reactive power control, the main needs are to regulate voltage at suitable values and ensure a proper reactive power sharing among the energy sources. The conventional control for reactive power presents relevant drawbacks and so an Advanced Droop Control strategy (ADC) is presented to approach primary voltage control and reactive power sharing among Grid-Supporting inverters in islanded MGs. The ADC strategy is presented defining its control law and the control scheme with a stability analysis. Then, an analytical procedure is developed to set the controller parameters. Following, a comparison between the ADC and droop control is performed with dedicated simulations on a common benchmark Microgrid in order to highlight the advantages of the proposed control strategy. Finally, a comparison with other advanced control techniques is proposed in order to show that ADC is able to guarantee improved performance in terms of the combined regulation of voltage and reactive power. [ABSTRACT FROM AUTHOR]

Power systems are facing the challenges of integrating massive electric vehicles (EVs) and lacking operational flexibility. An optimal and efficient coordination strategy is needed to coordinate the operations among EV charging stations (CSs) and the distribution system operator (DSO) and to make full use of the EVs’ charging flexibility for improving the operational flexibility of power systems. To this end, this paper proposes a CSs-DSO distributed coordination strategy. The proposed strategy integrates a supply-curve-based quantification method to quantify the EVs’ flexibility contribution and a Nash bargaining game-theory-based peer-to-peer (P2P) transactions model for maximizing the profits of entities participating in the coordination. To tackle the CSs-DSO coordination problem that has a bi-level-parallel coupling structure, an analytical target cascading (ATC) and alternating direction method of multipliers (ADMM) jointly-based distributed solution approach is proposed. First, the CSs-DSO bi-level model is decoupled by ATC with tie-line power being the only exchanged information; then, the model is further decomposed for each CS by ADMM for protecting the CSs’ privacy and autonomy. The effect of coordination and the computational efficiency of the proposed strategy is verified by numerical simulations on a modified IEEE 33-bus distribution system connecting multiple CSs. [ABSTRACT FROM AUTHOR]

Distribution systems are becoming more active and provide more power support for transmission systems via their connection points at the transmission-distribution (T-D) interfaces. This paper proposes a chance constrained optimization model to estimate the flexibility area at a T-D interface. In this model, network flexibility is for the first time involved and facilitated by introducing power flow routers (PFRs) into the distribution system. The chance-constrained flexibility area (CCFA) given by the proposed model provides a description of the aggregated power dispatchability of distribution system with the guarantee of low risks of voltage violations under renewable uncertainties. We exploit the mechanism of network flexibility and reveal that it significantly reduces the voltage standard deviations, which cannot be achieved by node power flexibility. To evaluate the CCFA, an efficient two-layer iteration algorithm is designed. The inner layer finds the boundary point of CCFA along a given direction for active and reactive power. The outer layer determines those key directions to be included in the estimation as the corresponding points capture the features of the CCFA boundary. Case studies show that PFRs significantly enlarge the CCFA, which reveals that network flexibility is an important supplement to node power flexibility in T-D interaction. [ABSTRACT FROM AUTHOR]

In view of the increasing levels of renewable generation across the world, the operational dynamics of power systems are changing. One of the dimensions of this transformational change is the nature of fault ride through behavior of renewable technologies such as wind and the associated differences compared to conventional generation. This paper investigates the impacts of fault ride through behavior of wind farms on the system stability in detail, using full dynamic model of a low inertia island power system. Recorded PMU measurements are used to establish the variations in wind farm behavior during and after a fault. A detailed sensitivity analysis on the active and reactive power injection behavior of wind farms is carried out to establish the component of fault ride through behavior that is most critical to system stability, using the full model of the Ireland and Northern Ireland Power system (All island power system). Detailed investigation of the mechanics of a fault in a low inertia, wind generation dominated system is carried out to reveal potential technical scarcities. Finally, mitigations for identified scarcities arising from non-ideal fault ride through behavior of wind farms are presented in terms of Transmission System Operator led novel system services. [ABSTRACT FROM AUTHOR]

Since the wide application of virtual synchronous generators (VSGs), the power grid faces great challenges in the safe and stable operation due to their limited thermal capacity and weak anti-disturbance ability. During transient period, for example, a fault occurs in the transmission line, the VSG may lose the transient angle stability and provoke the current hard limit. Even if the fault is cleared by tripping of line, it still faces the problem of instability and voltage dips. To address this problem, in this paper, the post-fault large-signal model of VSG is derived first via the travelling waves based fault information acquisition. Subsequently, with the effect of both active and reactive power loops taken into account, a two-stage simultaneous control scheme is proposed for improving the transient stability of VSG, while considering the current limitation during fault state and voltage support after fault clearance. This method is fulfilled by mode switching and an additional feedback control based on the fault signal. Finally, the effectiveness of the proposed method under both symmetrical and asymmetrical faults is verified. Moreover, the application of the proposed method in a multiple VSGs system is also verified. Besides, the robustness to parameter mismatch and the feasible operating region for the method are discussed. [ABSTRACT FROM AUTHOR]

We propose an approach to solving the AC network-constrained unit commitment problem (AC-NCUC) of large-scale power systems. This approach relies on solving convex (continuous and mixed-integer) optimization problems. First, we formulate a second-order conic relaxation of the original optimization problem, which renders a mixed-integer second-order conic optimization problem. To solve this problem, we use Benders’ decomposition, which decomposes it into a master problem, which is mixed-integer linear, and a subproblem, which is continuous and second-order conic. To improve the convergence of the Benders’ algorithm, we add several linear feasibility constraints to the master problem. Since the second-order relaxation of the original problem cannot guarantee AC feasibility of the solution found, we ensure such feasibility by solving a sequence of continuous convex optimization problems. We numerically validate the proposed approach using a Texas 2000-bus system. [ABSTRACT FROM AUTHOR]

Volt/VAr Optimization (VVO) is becoming increasingly crucial in distribution management systems with renewable sources that require setting their reactive power in coordination with legacy voltage and reactive power control devices. This paper presents a VVO method that operates in complex variables based on the Wirtinger calculus; it employs a penalty method that keeps voltage magnitudes and controller parameters within limits together with a probabilistic rounding technique for handling switched device variables. The complex variable implementation permits using the compensation technique when solving the Karush-Kuhn Tucker (KKT) system, thus achieving a significant speedup due to limiting the number of linear system factorizations. The proposed method is contrasted with a classical VVO implementation employing discrete coordinate search from the current operating point and an enhanced version that uses sensitivity information. Numerical results on distribution networks having up to 3147 nodes show that the proposed method is significantly faster than classical methods and gives operating points free of voltage magnitude violations and lower power loss. [ABSTRACT FROM AUTHOR]

We consider a distributed optimal power flow formulated as an optimization problem that maximizes a nondifferentiable concave function. Solving such a problem by the existing distributed algorithms can lead to data privacy issues because the solution information exchanged within the algorithms can be utilized by an adversary to infer the data. To preserve data privacy, in this paper we propose a differentially private projected subgradient (DP-PS) algorithm that includes a solution encryption step. We show that a sequence generated by DP-PS converges in expectation, in probability, and with probability 1. Moreover, we show that the rate of convergence in expectation is affected by a target privacy level of DP-PS chosen by the user. We conduct numerical experiments that demonstrate the convergence and data privacy preservation of DP-PS. [ABSTRACT FROM AUTHOR]

High penetrations of photovoltaic (PV) systems can cause severe voltage quality problems in distribution networks. This paper proposes a distributed control strategy based on the dynamic formation of coalitions to coordinate a large number of PV inverters for voltage regulation. In this strategy, a rule-based coalition formation scheme deals with the zonal voltage difference caused by the uneven integration of PV capacity. Under this scheme, PV inverters form into separate voltage regulation coalitions autonomously according to local, neighbor as well as coalition voltage magnitude and regulation capacity information. To coordinate control within each coalition, we develop a feedback-based leader-follower consensus algorithm which eliminates the voltage violations caused by the fast fluctuations of load and PV generation. This algorithm allocates the required reactive power contribution among the PV inverters according to their maximum available capacity to promote an effective and fair use of the overall voltage regulation capacity. Case studies based on realistic distribution networks and field-recorded data validate the effectiveness of the proposed control strategy. Moreover, comparison with a centralized network decomposition-based scheme shows the flexibility of coalition formation in organizing the distributed PV inverters. The robustness and generalizability of the proposed strategy are also demonstrated. [ABSTRACT FROM AUTHOR]

The evolution of power distribution grids from passive to active systems creates reliability and efficiency challenges to the distribution system operators. In this paper, an energy management and control scheme for managing the operation of an active distribution grid with prosumers is proposed. A multi-objective optimization model to minimize (i) the prosumers electricity cost and (ii) the cost of the grid energy losses, while guaranteeing safe and reliable grid operation is formulated. This is done by determining the active and reactive power set-points of the photovoltaic and storage systems integrated in the grid buildings. The resulting optimization model is non-convex, thus a convex second-order cone program is developed by appropriately relaxing the non-convex constraints which yields optimal results in most operating conditions. The convexified model is further utilized to develop an algorithm that yields feasible solutions to the non-convex problem under any operating conditions. Moreover, a second novel algorithm to find the operating point that provides fairness between the prosumers and the grid costs is proposed. Simulation results demonstrate the effectiveness and superiority of the proposed scheme in managing an industrial distribution grid compared to a self-consumption approach. [ABSTRACT FROM AUTHOR]

Due to the increasing penetration of large-scale renewable energy generation at transmission level, hybrid AC/DC transmission expansion is becoming more relevant by the day, especially if the considered renewable generation is far away from existing AC grid infrastructure. This paper presents a multi-period hybrid AC/DC network expansion planning model that incorporates node voltages, reactive power and network losses. Since the operation of a high voltage DC link is influenced considerably by the converter stations, converter transformer, filter, and phase reactor are modeled in each converter station. Since the AC power flow equations render a non-convex problem whose solution algorithms do not always guarantee convergence or optimality, a second-order conic relaxation is utilized. The resulting model is a mixed-integer convex problem with a convergence guarantee that embodies a better approximation of system operation than its DC linear counterpart. Three case studies are considered to illustrate the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes a finite-time event-triggered secondary frequency and voltage control for islanded AC microgrids (MGs) in a distributed fashion. The proposed control strategy can effectively perform frequency restoration and voltage regulations, while sharing the active and reactive power among the distributed generators (DGs) based on their power ratings. The finite-time control enables a system to reach consensus in a finite period of time enhanced from the asymptotic convergence. The event-triggered communication is utilized to reduce the communication burden among the DG controllers by transmitting data among DGs if an event-triggering condition is satisfied. The performance of the proposed finite-time event-triggered frequency control is verified utilizing a hardware-in-the-loop experimental testbed which simulates an AC MG in Opal-RT. [ABSTRACT FROM AUTHOR]

Weak grid scenarios and low-inertia systems are emerging issues in power systems, which could lead to voltage and frequency instabilities. Synchronous Condensers (SynCons) have recently drawn renewed attention as a promising solution to provide system strength and inertia support. Even though the exciter control of SynCons is a well-established technology, further developments are required to guarantee the stability of post-fault operations, in particular, in weak grids. This paper proposes a data-driven approach for designing higher-order optimized exciter controllers to meet this requirement. A pseudo-random binary sequence (PRBS)-based system identification method is used to obtain frequency response data of the power system, from the exciter point of view, which is then fed into the proposed optimal control design procedure. The proposed exciter controller is tested for voltage ride-through and fault scenarios in a single machine infinite bus (SMIB) case and the IEEE 39-bus test system to assess its performance compared to the conventional AC1A exciter controller. The results obtained through simulation tests carried out using the PSCAD/EMTDC software verify that the proposed exciter controller guarantees the post-fault stability in both strong and weak grids. [ABSTRACT FROM AUTHOR]

An error-resilient state estimation is devised to calculate authentic states for microgrids equipped with hierarchical controls. New contributions include: 1) a state estimation incorporating droop control which helps mitigate estimation errors due to transient disturbance; 2) a secondary-control-empowered microgrid state estimation for leveraging power sharing and voltage regulation among DERs. Case studies demonstrate the robustness, efficiency and excellent convergence performance of the authentic state estimation approach. [ABSTRACT FROM AUTHOR]

The paper introduces the concept of complex frequency. The imaginary part of the complex frequency is the variation with respect of a synchronous reference of the local bus frequency as commonly defined in power system studies. The real part is defined based on the variation of the voltage magnitude. The latter term is crucial for the correct interpretation and analysis of the variation of the frequency at each bus of the network. The paper also develops a set of differential equations that describe the link between complex powers and complex frequencies at network buses in transient conditions. No simplifications are assumed except for the usual approximations of the models utilized for the transient stability analysis of power systems. A variety of analytical and numerical examples show the applications and potentials of the proposed concept. [ABSTRACT FROM AUTHOR]

As the inverter-based generation replaces the conventional synchronous generators, it may also need to fill in the missing ancillary service support. One of these ancillary services is dynamic reactive power provision and voltage control. This paper analyzes optimal strategy of reactive and active fault-current support of the inverter-based generation leading to fast voltage recovery of the system. For the purpose of the analysis, new ramping active current controller able to emulate different behavior of active current injection is proposed. By optimizing its parameters for different case studies of the system, the conclusions about optimal behavior of the inverter based generation with respect to system parameters and operating conditions are drawn. It is observed that the optimal combination of active and reactive fault-current is the most sensitive to the dynamic load component penetration levels in the system. With the increasing penetration levels, the significance of active fault-current injection increases. The results show that with higher penetration levels of dynamic load component in the heavy load areas, the ramping down of the inverter-based generation active fault-current results in slower voltage recovery of the system. Following this conclusion, a recommendation on update of current European grid codes is proposed. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new mathematical model for power flow problem based on the linear and nonlinear matrix inequality theory. We start with rectangular model of power flow (PF) problem and then reformulate it as a Bilinear Matrix Inequality (BMI) model. A Theorem is proved which is able to convert this BMI model to a Linear Matrix Inequality (LMI) model along with One Nonconvex Quadratic Constraint (ONQC). Our proposed LMI-ONQC model for PF problem has only one single nonconvex quadratic constraint irrespective of the network size, while in the rectangular and BMI models the number of nonconvex constraints grows as the network size grows. This interesting property leads to reduced complexity level in our LMI-ONQC model which in turn makes it easier to solve for finding a PF solution. The non-conservativeness, iterative LMI solvability, well-defined and easy-to-understand geometry and pathwise connectivity of feasibility region are other important properties of proposed LMI-ONQC model which are discussed in this paper. An illustrative two-bus example is carefully studied to show different properties of our LMI-ONQC model. We have also tested our LMI-ONQC model on 30 different power-system cases including four ill-conditioned systems and compared it with a group of existing approaches. The numerical results show the promising performance of our LMI-ONQC model and its solution algorithm to find a PF solution. [ABSTRACT FROM AUTHOR]

The paper proposes methodology for development of dynamic equivalent model of hybrid renewable energy source (HRES) plant suitable for reliable assessment of the overall transient stability of the realistic, large power systems. Transient stability index is used for system stability assessment, and consequently for the evaluation of the model performance. The historical plant production data and transmission network short-circuit fault statistics, together with probabilistically modelled uncertainties associated with system operation, are used to generate a set of realistic dynamic responses of the plant over the period of one year. The use of clustering algorithms enabled unsupervised grouping/clustering of responses and development of the low order equivalent models in the form of a transfer function with voltage as an input and real and reactive power as outputs. The methodology is illustrated on a number of case studies using two HRES plant configurations. It is demonstrated that a very few low order dynamic models can be used to model the HRES plant during the year for sufficiently accurate transient stability assessment of the power system. The possibility of deriving these equivalent models based on forecasted HRES plant composition makes them attractive for practical application in power system dynamic security studies. [ABSTRACT FROM AUTHOR]