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This paper concerns the detection and identification of errors in the parameters of three-phase transposed as well as untransposed transmission line (TL) models used by various network applications. Such detailed models are increasingly needed in particular by power system applications where loads may not be balanced and/or TLs may not be symmetrical, and a full detailed three-phase solution may have to be obtained. To address this problem, the paper proposes an efficient algorithm for detection, identification, and estimation of parameter errors using synchronized phasor measurements. The suspect TL is detected using the modal domain networks in the first stage. The developed algorithm extends the previously developed largest normalized Lagrange multiplier (NLM) test for positive sequence parameters to the full coupled three-phase lines. An estimation method is also proposed for estimating the erroneous parameters, which takes into account the correlation of the parameters. To illustrate the effectiveness of the method, several tests are performed on the IEEE 118-bus system and a large 3474-bus utility system. [ABSTRACT FROM AUTHOR]

The stability of power systems can largely limit the power transfer capability limit of transmission lines. The PV generator control is different from synchronous generator control. The impact of PV generator dynamics on the power transfer limit constrained by stability is not well explored in the literature. This paper focuses on improving the stability constrained power transfer capability limit of transmission lines emanating from PV generators. The PV generator is provided with dc link voltage and reactive power control and is equipped with low voltage ride through capability, voltage and frequency support functionalities. In this paper, Lyapunov function analysis based adaptive tuning laws are proposed for PV control parameters to improve the power transfer capability limit (constrained by stability) of transmission lines connecting PV generators to grid. The tuning laws are proposed for Phase Locked Loop (PLL), outer and inner control loop parameters. The proposed tuning laws have inherent robustness towards faults, changes in solar irradiation, changes in grid topology, network impedances, generation and loads in the system. The effectiveness of the proposed method is validated on a Single PV-Synchronous Machine system, modified IEEE-39 and IEEE-118 bus system. The performance of the proposed method is investigated considering various disturbances such as symmetrical and asymmetrical faults on transmission line, switching of a transmission line and change in solar irradiation of PV. Comparison with existing method shows that the proposed tuning method can achieve higher power transfer capability limit considering stability. [ABSTRACT FROM AUTHOR]

The advantages of operating selected transmission lines at frequencies other than the standard 50 or 60 Hz are numerous, encompassing increased power transfer capacity and better utilization of existing infrastructure. While high voltage DC (HVDC) is by far the most well-established example, there has been an emerging interest low frequency AC (LFAC) transmission in applications ranging from offshore wind to railway systems and mining. In this paper, we investigate the use of LFAC as a transmission upgrade and propose models and analysis methods to determine the optimal choice of frequency. The paper first presents an optimal power flow model with frequency as a variable, assuming modular multilevel converters for frequency conversion. Using this model, we analyze LFAC as an embedded upgrade in a transmission system using existing lines. We quantify the system-wide advantages from improved power flow control and frequency reduction and find that an LFAC upgrade achieves similar and sometimes better results compared with HVDC upgrades. Finally, we analyze the factors which determine the optimal frequency for these upgraded transmission lines, and we demonstrate the benefits of changing the frequency in response to different system topologies and operating conditions. [ABSTRACT FROM AUTHOR]

The paper develops an optimization method for assessing transmission network vulnerability to small changes in generation (as caused, for example, by wind forecast inaccuracy). The method computes the smallest deviation (in a weighted 2-norm sense) from the nominal generation pattern that would drive a particular line to a specified temperature, over a given time horizon. The 2-norm weighting matrix provides a means of capturing spatial and temporal coupling between generation sites and time intervals. The temperature constraint is second-order in voltage angle differences. The problem is therefore a quadratically-constrained quadratic program (QCQP). Solving the QCQP for each line in the network yields a set of candidate generation deviation patterns which may then be sorted to determine the lines that are most vulnerable to overloading. The paper develops a computationally efficient algorithm for solving this QCQP. An example explores line-overload vulnerability due to changes in wind patterns. Numerical results emphasize the framework’s ability to incorporate evolving ambient and system conditions, as well as computational scaling properties. [ABSTRACT FROM AUTHOR]

This paper proposes a scalable framework for the real-time detection and localization of power line outages in transmission networks. While localizing outages is pivotal for ensuring grid reliability, forming such decisions faces an inherent combinatorial complexity that grows with the grid size and becomes prohibitive even for moderate grid sizes. Hence, designing outage detection and localization algorithms that are amenable to real-time implementation critically hinges on circumventing the computational complexity. This paper proposes a graph-guided quickest change detection (GG-QCD) approach that leverages the grid topology and performs quickest change detection in the spectral domain of the graph underlying grid's topology. The GG-QCD algorithm's key features are that (i) it uses a one-dimensional metric that tests the data's conformity to the grid topology, and (ii) it decouples the detection and localization processes to avoid testing all the lines at all times. Specifically, a lack of such conformity of the data to the system model will be alarming the potential existence of an outage. Once an outage is deemed to exist, an active graph clustering approach will be used to localize the line in outage. The clustering approach will also be relying on the same one-dimensional conformity metric. Overall, this approach will be performing only one test over time when the system is outage-free. Once an outage is detected, it will require $\mathcal {O}(\log (L))$ additional tests to identify the line in outage. This paper presents the theory for GG-QCD and algorithms for outage detection and localization. To evaluate these algorithms’ efficiency and complexity, they are examined in the standard IEEE 30- and 118-bus systems. [ABSTRACT FROM AUTHOR]

Since modern smart grids have various and deeply coupled cyber-physical components, they are vulnerable to malicious cyber attacks. Although regular defenses including firewall and IDS are deployed, they may be weakened by zero-day vulnerabilities and sophisticated attack schemes. Therefore, defense strategies to mitigate the risk of blackouts during cyber attacks are necessary. This paper proposes a cyber-physical coordinated defense strategy to overcome the disruption and minimize the risk as much as possible. At the cyber layer, a zero-sum multilevel Markovian Stackelberg game is proposed to model sequential actions of the attacker and the defender. The defender distributes defensive resources to protect lines in a real-time manner, according to the attacker's action. If cyber attacks should result in physical outages, defense at the physical layer is then employed. A security-constrained optimal power flow reserving security margin of critical components will be performed to minimize the blackout scale and potential future risk. To solve the corresponding optimization problem and further get the optimal defense strategy, this paper devises a novel “water-pouring” algorithm. Lastly, test results show that the proposed dynamic defense strategy mitigates risk significantly and outperforms existing methods. [ABSTRACT FROM AUTHOR]

Co-simulation of heterogeneous systems allows for in-depth analysis of various aspects of power systems’ operation while staying within the environments of the simulation tools that are best fit to represent their respective domains. Equipped with a proprietary co-simulation platform, the paper focuses on the issue of power-conjugate coupling between parts of power grids modeled in transient stability and electromagnetic transient simulation tools. The problems of co-simulation stability and precision in presence of delays are tackled by means of designing a proper coupling interface. It is shown that two established interface methods – the V-I method and the Transmission Line Interface – are special cases of a generalized interface framework proposed in the paper. Moreover, a new interface algorithm is described by parametrizing the generalized framework. Analytical tools are also formulated to aid in the analysis of interface stability and precision via the concepts of passivity and transparency. Simulation results of benchmark systems of various complexity demonstrate the application of the developed power coupling interface. [ABSTRACT FROM AUTHOR]

This paper presents a distributionally robust network-constrained unit commitment (DR-NCUC) model considering AC network modeling and uncertainties of demands and renewable productions. The proposed model characterizes uncertain parameters using a data-driven ambiguity set constructed by training samples. The non-convex AC power flow equations are approximated by convex quadratic and McCormick relaxations. Since the proposed min-max-min DR-NCUC problem cannot be solved directly by available solvers, a new decomposition algorithm with proof of convergence is reported in this paper. The master problem of this algorithm is solved using both primal and dual cuts, while the max-min sub-problem is solved using the primal-dual hybrid gradient method, obviating the need for using duality theory. Also, an active set strategy is proposed to enhance the tractability of the decomposition algorithm by ignoring the subset of inactive constraints. The proposed model is applied to a 6-bus test system and the IEEE 118-bus test system under different conditions. These case studies illustrate the performance of the proposed DR-NCUC model to characterize uncertainties and the superiority of the proposed decomposition algorithm over other decomposition approaches using either primal or dual cuts. [ABSTRACT FROM AUTHOR]

This paper proposes a novel repair rule set (RRS) for scheduling the power system infrastructure repair after the occurrence of extreme events. RRS is made up of multiple repair rules, each of them can be applied in arbitrary post-disaster failure scenarios to rank the repair actions by priority. A learning-to-rank technique called AdaRank is used to train the repair rules by combining the weak learners derived from the dynamic repair scheduling model. Then, RRS is constructed by iteratively clustering the training cases and retraining the repair rule for each cluster. Increasing the number of repair rules within RRS allows it to differentiate various types of failure scenarios, thereby improving its performance. Further combined with multi-label K nearest neighbor (ML-KNN) technique, RRS is able to schedule the repair without the full knowledge of real-time failure information, such as the estimated repair time. The results of case studies on IEEE-118 test systems show that the proposed method has a desirable performance compared to the exact mathematical optimization model. Moreover, it reduces the requirement for failure information while significantly improving the computational efficiency. [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]

Natural disasters, such as extreme weather events (EWEs), can cause significant damage to power systems. In fact, it is expected that the intensity and frequency of EWEs will increase the next years due to climate change, making power system resilience enhancement necessary. This paper proposes a transmission resilience planning solution by determining the lines to be placed underground in order to minimize load shedding in the most cost-efficient way taking into account historical EWEs (HEWEs). The problem is formulated as a stochastic robust optimization problem and is decomposed into a master problem determining the lines to be placed underground and a number of subproblems, where each subproblem corresponds to a HEWE and provides the worst damage scenario that leads to the maximization of load shedding. The problem is solved using a decomposition-based algorithm. The proposed method is illustrated on a modified IEEE Reliability Test System and IEEE 118-bus System and it is evaluated by applying a Sequential Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

This paper proposes a novel modeling framework and decomposition-based solution strategy combining stochastic programming (SP) and robust optimization (RO) to deal with multiplex uncertainties in coordinated mid- and long-term power system planning. The problem is formulated as a multi-year generation and transmission planning problem from an independent system operator (ISO)’s perspective to minimize both expansion and operational costs under binary and continuous uncertainties, ${\bf i.e.}$ , system component contingency and load/generation variation. N- $\bf {k}$ contingencies are captured in RO using the reformulated contingency criteria, while the load/generation uncertainty is considered in SP embedded with RO using operating scenarios generated from the historical data with spatiotemporal correlations. The original hybrid model is highly intractable, but the intractability can be relieved by the proposed decomposition strategy based on the column-and-constraint generation and L-shaped algorithms. We apply our model to perform long-term system planning under extremely high renewable penetration and investigate the case of 100% renewables in long-term planning. Numerical experiments on multi-scale test systems verify the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper addresses the incorporation of transmission switching in the contingency-constrained unit commitment problem within the context of co-optimized electricity markets for energy and reserves. The proposed generation scheduling model differs from existing formulations due to the joint consideration of four major complicating factors. First, transmission switching actions are considered both in the pre- and post-contingency states, thereby requiring binary post-contingency variables. Secondly, generation scheduling and transmission switching actions are co-optimized. In addition, the time-coupled operation of generating units is precisely characterized. Finally, practical features of modern power systems, such as uncertain nodal net injections and the operation of energy storage, are also considered. The proposed model is cast as a challenging mixed-integer program for which the off-the-shelf software customarily used for simpler models may lead to intractability even for moderately-sized instances. In order to circumvent this computational issue, this paper presents an enhanced and novel application of an exact nested column-and-constraint generation algorithm featuring the inclusion of valid constraints to improve the overall computational performance. Numerical simulations based on the IEEE 118- and 300-bus systems demonstrate the effective performance of the proposed approach as well as its economic and operational advantages over existing models disregarding post-contingency transmission switching. [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]

This paper presents a new formulation for the preventive security-constrained unit commitment problem modeling N-k line outages and transmission losses. The pre- and post-contingency transmission constraints, representing N-k line outages, are explicitly included by using generalized generation distribution factors. To account for security, a contingency selection procedure based on line outage distribution factors finds a list of worst-case contingencies. Transmission losses are incorporated using piecewise linear expressions. The proposed model is formulated as an instance of mixed-integer linear programming. The effectiveness of the proposed approach is illustrated with the IEEE 57-bus system and the 1,354-bus portion of the European transmission system. As empirically evidenced, the explicit consideration of N-k line outages and transmission losses leads to different decisions in the generation scheduling and dispatch, ensuring secure power system operation. [ABSTRACT FROM AUTHOR]

Reliable planning of electricity networks is a crucial challenge to maintain the continuous power supply. This can be ensured through careful planning which requires a number of parameters as inputs such as electricity demand, generation capacity, fuel price, renewable intermittent generation, among others. The uncertain behaviors of such parameters have been well studied in literature. Another important parameter which is a vital requirement for reliable planning is the resistance of overhead transmission lines. Traditionally, the current models ignore to consider the resistance variations due to Joule heating and ambient temperature changes in transmission expansion planning (TEP) problem. In this sense, this paper presents an adaptive robust optimization (ARO) framework for TEP to model the uncertain resistance through ellipsoidal uncertainty set. Moreover, a data-driven selection of the ellipsoidal uncertainty set is proposed. In this regard, Khachiyan's algorithm (KA) is used to identify the minimum-volume covering ellipsoid (MVCE) that contains all uncertain parameters. A case study based on IEEE 118-bus power system is presented to demonstrate the effectiveness of the proposed method. Simulation results show that resistance uncertainty is of serious concern in the TEP problem since the solutions are highly sensitive to fluctuations in the line resistances. [ABSTRACT FROM AUTHOR]

Low frequency electromechanical oscillations can pose a threat to the stability of power systems if not properly addressed. This paper proposes a novel methodology to damp these inter-area oscillations using loads, the demand side of the system. In the proposed methodology, loads are assigned to an aggregated cluster whose demand is modulated for oscillation damping. The load cluster control action is obtained from an optimal output feedback control (OOFC) strategy. The paper presents an extension to the regular OOFC formulation by imposing a constraint on the sum of the rows in the optimal gain matrix. This constraint is useful when the feedback signals are generator speeds. In this case, the sum of the rows of the optimal gain matrix is the droop gain of each load actuator. Time-domain simulations of a large-scale power system are used to demonstrate the efficacy of the proposed control algorithm. Two different cases are considered: a power imbalance and a line fault. The simulation results show that the proposed controllers successfully damp inter-area oscillations under different operating conditions and with different clustering for the events considered. In addition, the simulations illustrate the benefit of the proposed extension to the OOFC that enable load to provide a combination of droop control and small signal stability augmentation. [ABSTRACT FROM AUTHOR]

The proliferation of Phasor Measurement Units (PMUs) to monitor power grid dynamics at a high resolution (10–100 samples/sec) has opened a new paradigm to situational awareness. Existing event detection techniques for identifying multiple events like transmission line faults, generation trip, line trip, load loss, current transformer (CT) failure, islanding, etc., are prone to misdetection, delayed detection, and false detection. Moreover, most of them can detect events either with fast (transient events) or slow dynamics (oscillatory and excursion events) using synchrophasor measurements. This paper focuses on detecting events with both fast and slow dynamics using wide-area frequency measurements. To this end, a novel method is proposed based on Weibull distribution, which we call as Weibull-based Excursion Transient and Oscillatory (WETO) method. The WETO method can identify the time of inception, location, and severity of the event in near real-time using only a single parameter, known as variability. The events are detected within a time window of 5 cycles using only frequency measurements. The proposed method is validated for the Indian as well as the North American grid disturbances, and the results show that it would be beneficial to the system operator in visualizing the true situation of the grid events. [ABSTRACT FROM AUTHOR]

Natural disasters which include major storms, floods, tornados, and hurricanes can seriously threaten the resilience of large and coupled infrastructures such as electric power distribution and transportation systems. This paper proposes a planning (i.e., investment + operation) method for enhancing the resilience of coupled power distribution and transportation systems. The proposed investment method includes capacity expansions of power lines, roads, and charging stations, and the hardening of roads and power lines. A tri-level problem is proposed and formulated to accommodate random natural disasters. The proposed model is solved by applying the Benders decomposition and the column-and-constraint generation (C&CG) algorithms. Benders decomposition will decompose the tri-level coupled problem into a single-level master problem and a bi-level subproblem. However, the latter with binary variables is not a convex problem and cannot be converted to the maximization problem. The C&CG algorithm is applied to solve the bi-level subproblem with binary variables. The proposed resilience enhancement algorithm is tested using a coupled power distribution and transportation system with 21 electric buses and 20 roads and numerical results are analyzed to validate the effectiveness of the proposed planning method. [ABSTRACT FROM AUTHOR]

The coordinated operation of interconnected but locally controlled electricity markets is generally referred to as a “coupling”. In this paper we propose a new decentralized market mechanism for efficient coupling of independent electricity markets. The mechanism operates after each individual market has settled (e.g. hour-ahead). Based upon the reported supply and demand functions for internal market optimization (clearing), each market operator is asked to iteratively quote the terms of energy trade (on behalf of the agents participating in its market) across the transmission lines connecting to other markets. We show the mechanism’s outcome converges to the optimal flows between markets given the reported supply and demand functions from each individual market clearing. In light of incentive compatibility issues that result from pricing power flows across interconnection lines with locational marginal prices, the mechanism features incentive transfers (updated at each iteration) that compensate each given market with its marginal contribution, i.e. the cost reduction to all other participating markets. We show that these transfers imply truthful participation in the mechanism is a Nash equilibrium. The proposed decentralized mechanism is implemented on the three-area IEEE Reliability Test System where the simulation results showcase the performance guarantees of the proposed mechanism. [ABSTRACT FROM AUTHOR]

The icing on transmission lines threatens the power system security while the heat caused by power transmission losses can prevent icing growth. This paper proposes a preventive scheduling model for mitigating the glaze icing by optimizing the distribution of power losses on ice-coated transmission lines. An analytical glaze icing growth model is established based on the heat balance theory, which builds a direct relationship between icing growth and power transmission losses. Accordingly, the analytical glaze icing model is embedded into the proposed scheduling model to quantify the impact of power system schedules on transmission line icing and reduce the glaze icing of transmission lines. The scheduling model co-optimizes active power dispatch, demand response, and reactive power optimization for promoting the de-icing effect. To overcome the computational difficulties, the analytical glaze icing growth model is further linearized, and the Lagrangian relaxation method is adopted for identifying a practical solution. Case studies are conducted on different icing scenarios in the IEEE RTS-79 test system to verify the validity of the proposed model. Results show that the proposed preventing scheduling model can avoid the icing on transmission lines for mild ice disasters, while efficiently restraining the icing growth on transmission lines when they cannot be completely de-iced in severe storms. [ABSTRACT FROM AUTHOR]

High-capacity long-distance transmission lines, such as high-voltage direct-current (HVDC) lines, are vulnerable to extreme weather. Their failures may cause significant power loss and frequency drop in the receiving-end power systems, which should be considered in the power system scheduling. In this paper, the failure rates of transmission lines subject to extreme weather conditions are firstly modeled to obtain the probability of failure events. Then, a novel criterion defined by the integration of abnormal frequency during the primary and secondary frequency regulation process is proposed to measure frequency security. This criterion is capable to reflect the cumulative frequency deviation effect and distinguish the contributions of different frequency regulation reserve providers, e.g., generators and flexible loads. Moreover, the linearity of the criterion makes it easy to be incorporated into optimization problems. Finally, a two-stage stochastic frequency constrained unit commitment (FCUC) model is developed to optimally schedule generators and flexible loads while satisfying the frequency security constraints under transmission line failure events. The proposed FCUC model is efficiently solved by a regularized L-shape algorithm. The proposed model and techniques are validated based on the modified IEEE 118 and 300 bus systems with realistic meteorological data. [ABSTRACT FROM AUTHOR]

In the face of increasing natural disasters and an aging grid, utilities need to optimally choose investments to the existing infrastructure to promote resiliency. This paper presents a new investment decision optimization model to minimize unserved load over the recovery time and improve grid resilience to extreme weather event scenarios. Our optimization model includes a network power flow model which decides generator status and generator dispatch, optimal transmission switching (OTS) during the multi-time period recovery process, and an investment decision model subject to a given budget. Investment decisions include the hardening of transmission lines, generators, and substations. Our model uses a second order cone programming (SOCP) relaxation of the AC power flow model and is compared to the classic DC power flow approximation. A case study is provided on the 73-bus RTS-GMLC test system for various investment budgets and multiple hurricane scenarios to highlight the difference in optimal investment decisions between the SOCP model and the DC model, and demonstrate the advantages of OTS in resiliency settings. Results indicate that the network models yield different optimal investments, unit commitment, and OTS decisions, and an AC feasibility study indicates our SOCP resiliency model is more accurate than the DC model. [ABSTRACT FROM AUTHOR]

Distributed optimization algorithms for security-constrained economic dispatch (SCED) problems have been the subject of significant research interest in recent years. However, existing distributed SCED algorithms can be ineffective in the presence of malicious participants and inefficient in the absence of a coordinator. On the other hand, blockchain, an emerging technique known as the trust machine, has not shown its potential to address the above challenges in state-of-the-art literature. This paper proposes a blockchain-based distributed SCED algorithm. Using blockchain to form a coordination committee and enable balance among committee members, the proposed method allows the use of hierarchical SCED algorithms in the absence of a coordinator and can disable malicious participants. Numerical results show the robustness and necessity of the proposed blockchain-based SCED algorithm, by comparing the SCED results with and without blockchain. [ABSTRACT FROM AUTHOR]

The placement of phasor measurement units (PMUs) in modern power systems provides improved monitoring and control characteristics of the entire electrical network. Nevertheless, the installation of additional PMU devices is associated with relatively high cost and complicated communication infrastructure. As a result, the allocation of the PMU devices needs to be optimized to achieve complete observability of the system while minimizing the related cost. This paper proposes a new method for solving the optimal PMU placement (OPP) problem using integer linear programming (ILP) such that the global optimal solution is guaranteed. As opposed to the reported studies in the literature, the proposed method considers the network parameters such as the series impedances and the shunt admittances of the transmission lines and transformers impedances in the formulation of the OPP problem. These parameters are found to have a crucial impact on the observability of the entire network. A distinguishing feature of the proposed approach is that it decomposes the network into smaller subnetworks, with reduced dependence between them, thus making it scalable when applied to typical networks. In addition, the proposed method seeks to achieve the maximum measurement redundancy while considering the impact of failures among individual PMU devices (N-1 contingency), the PMU channel limitation and the pre-existing conventional measurements. Furthermore, the presented approach incorporates additional constraints which are associated with the control feedback signals of the supplementary damping controllers and thus enhance the small signal stability of the power grid. The effectiveness of the proposed method is tested using different standard IEEE systems as well as a large practical network. [ABSTRACT FROM AUTHOR]

Distributed Series Reactances are devices that dynamically increase the impedance of a line to reduce the power flow it carries. This work explores whether widely deploying these devices enhances a power system's robustness against line overload cascading failures. The presence of Distributed Series Reactances may make it less likely that equipped lines would become overloaded by contingencies elsewhere, and so their presence may arrest the propagation of line overloads through a system. However, the efficacy of these devices in this role has not been widely investigated. Likewise, there are few extant methodologies for siting dynamic reactances within the grid to mitigate the propagation of cascades. In this paper, the ability of these devices to arrest the propagation of cascading failures within power grids is investigated. First, a novel dc power flow is formulated, which models dynamic line impedances. A novel methodology is proposed for siting the devices on lines spread throughout the network. With these innovations in hand, the devices’ effects on cascade propagation are simulated using a sizeable database consisting of multiple load & generation snapshots across eight test networks. No major beneficial effect is found, even when 25% of lines are equipped. [ABSTRACT FROM AUTHOR]

Battery-based Energy Storage Transportation (BEST) is the transportation of modular battery storage systems via train cars or trucks representing an innovative solution for a) enhancing Variable Renewable Energy (VRE) utilization and load shifting, and b) providing a potential alternative for managing transmission congestions. This paper focuses on point b) and proposes a long-term transmission-planning model coordinated with both stationary and mobile storage units. The planning-problem objective function minimizes the total system cost, i.e., the sum of i) the investment cost of candidate transmission lines, stationary and mobile storage systems, and ii) the operation cost, including conventional generating units fuel consumption, load shedding penalty and BEST transportation costs. An alternative approach for BEST vehicle scheduling problem is implemented. The contribution lies in the accomplishment of the spatial-temporal scheduling of the mobile storage units by including the Number-of-nonzero mathematical function in the optimization model set of constraints instead of using additional binary variables as generally accomplished. The identification of either storage systems optimal location, or both optimal location and size of storage systems is also allowed. BEST usefulness is analyzed and discussed for a test-system emulating a reals system in China-Northwestern-grid with high VRE penetration divided in five regional areas, of which the most promising one for BEST implementation is identified. [ABSTRACT FROM AUTHOR]

Modal decomposition of measurement equations has already been shown to simplify the formulation and resulting computational complexity of three-phase state estimation of systems where all the transmission lines are three-phase and fully transposed. When there are non-transposed and/or mixed-phase lines, modal decomposition can no longer fully decouple the three-phase measurement equations. This paper addresses the above shortcoming by proposing a simple yet practical solution based on the commonly used numerical compensation techniques. Thus, it enables application of the powerful decoupling approach to any type of three-phase networks which may contain non-transposed or mixed-phase lines and are fully observable by PMUs. The proposed procedure modifies the measurement set by deriving additive terms that compensate for the neglected unsymmetrical effects. It will be shown that unbalanced systems including non-transposed and mixed-phase elements, can still be transformed into three decoupled subsystems and solved in parallel by the proposed approach. Performance of the proposed algorithm is validated against several IEEE test cases. [ABSTRACT FROM AUTHOR]

Transmission line failures in power systems propagate non-locally, making the control of the resulting outages extremely difficult. In this work, we establish a mathematical theory that characterizes the patterns of line failure propagation and localization in terms of network graph structure. It provides a novel perspective on distribution factors that precisely captures Kirchhoff's Law in terms of topological structures. Our results show that the distribution of specific collections of subtrees of the transmission network plays a critical role on the patterns of power redistribution, and motivates the block decomposition of the transmission network as a structure to understand long-distance propagation of disturbances. In Part I of this paper, we present the case when the post-contingency network remains connected after an initial set of lines are disconnected simultaneously. In Part II, we present the case when an outage separates the network into multiple islands. [ABSTRACT FROM AUTHOR]

Transmission line failure in power systems prop-agate non-locally, making the control of the resulting outages extremely difficult. In Part II of this paper, we continue the study of line failure localizability in transmission networks and characterize the impact of cut set outages. We establish a Simple Path Criterion, showing that the propagation pattern due to bridge outages, a special case of cut set failures, are fully determined by the positions in the network of the buses that participate in load balancing. We then extend our results to general cut set outages. In contrast to non-cut outages discussed in Part I whose subsequent line failures are contained within the original blocks, cut set outages typically impact the whole network, affecting the power flows on all remaining lines. We corroborate our analytical results in both parts using the IEEE 118-bus test system, in which the failure propagation patterns exhibit a clear block-diagonal structure predicted by our theory, even when using full AC power flow equations. [ABSTRACT FROM AUTHOR]

Large blackouts in power grids are often the consequence of uncontrolled failure cascades. The ability to predict the failure cascade process in an efficient and accurate manner is important for power system contingency analysis. In this paper, we propose to apply the influence model for the prediction and screening of failure cascades in large scale DC and AC power networks. Then, the trained influence model is applied to some large power grids with thousands of buses and transmission lines. The prediction performance is evaluated in four different aspects, from the global perspective of the overall failure size to the individual information regarding the link failure time. The results show that under limited training samples, the proposed framework is capable of predicting the failure cascade size with a 7% error rate, the final state of links with a 10% error rate, and the failure time within 1 time unit for both the DC and AC model. One major advantage of the proposed method is that it can reduce the computational time of the failure cascade prediction by a few orders of magnitude with limited compromise in accuracy, as compared to the power flow based contingency analysis. Another important feature of the proposed method is that the trained influence parameters can reveal the critical initial contingencies. This information is very helpful for identifying the worst contingency scenarios for system operators. [ABSTRACT FROM AUTHOR]

In this paper, we propose a topology-cognizant optimal power flow (OPF) paradigm with additional safety constraints for multi-terminal direct current (MTDC) grids. The resulting formulation is concerned with the optimization of controller set-points, i.e., voltage and power levels at each bus, and the switching status of transmission lines that collectively referred to as grid topology. A pair of additional safety constraints are integrated into the problem formulation to prevent voltage violations caused by power fluctuations in between two controller set-point updates. Searching for a grid topology that offers more efficient operation leads to a mixed-integer nonlinear program (MINLP) which is computationally challenging due to: i) Non-convex power flow equations, (ii) Non-convex converter loss equations, and iii) Binary variables accounting for the operational status of transmission lines. Non-convexities of power flows and converter loss equations are tackled by means of a mixed-integer second-order cone programming (MISOCP) relaxation, while the optimal switching status of transmission lines are determined via a branch-and-bound search. Numerical results for the modified IEEE 14, 30, and 57-bus systems are used to verify the merits of the proposed method. Furthermore, this method is experimentally validated using the CIGRE B4 DC grid benchmark in a real-time hardware-in-the-loop platform. [ABSTRACT FROM AUTHOR]

This paper presents a two-stage stochastic planning model for transmission systems and distributed energy resources (DERs) considering power system resiliency. The model takes into account both normal and emergency conditions as well as the duration of each condition. The proposed model is formulated as a mixed-integer linear program to minimize the total investment cost of transmission lines and DERs, expected values of generators’ operation cost in normal and emergency situations, and load shedding cost in emergency condition. The emergency scenarios are considered as moderate, severe, and complete damage states, which have different recovery times for transmission assets. The Benders decomposition technique is utilized to solve the optimization problem. Numerical results are demonstrated based on the IEEE 118-bus test system. [ABSTRACT FROM AUTHOR]

Large-scale integration of renewable generation, usually interfaced to the network through power electronics, has led to drastic changes in power system dynamics. This paper presents novel insights into stability properties of such systems. For that purpose, a high-fidelity dynamic model of a generic low-inertia power system has been developed. The full-order, state-of-the-art control schemes of both synchronous and converter-based generators are included, with the latter differentiating between grid-forming and grid-following mode of operation. Furthermore, the dynamics of transmission lines and loads are captured in the model. Using modal analysis techniques such as participation factors and parameter sensitivity, the most vulnerable segments of the system are determined and the adverse effects of timescale coupling and control interference are investigated. More precisely, this work characterizes the maximum permissible penetration levels of inverter-based generation as well as the nature of the associated unstable modes and the underlying dynamics. Finally, potential directions for improving the system stability margin under different generation portfolios are proposed for several benchmark systems. [ABSTRACT FROM AUTHOR]

This paper intends to address the dynamic repair scheduling of electric power transmission systems based on look-ahead strategy approximation. The objective is to minimize system functionality loss during the restoration stage after disruptive events. A series of decisions regarding which damaged component to be repaired has to be made successively considering currently available information of repair time and its uncertainty in the future. To achieve this goal, the dynamic repair scheduling problem is represented as a stochastic Markovian decision process (MDP). To overcome the computational complexity of MDP derived from exponentially growing state space, the cost-to-go function is approximated by a look-ahead strategy based on repair importance ordering. Stage-dependent coefficients are used to balance the approximated functionality loss at different decision stages. The tradeoff between the efficiency and optimality can be achieved by adjusting the look-ahead depth and the updating policy of look-ahead strategy. The IEEE-14 and 118-bus systems were used for performance evaluation of the proposed method and comparison with various approaches. The results show that it can produce decisions close to the best-known solutions within small amount of time. [ABSTRACT FROM AUTHOR]

This paper describes the design and implementation of a proof-of-concept Pacific dc Intertie (PDCI) wide area damping controller and includes system test results on the North American Western Interconnection (WI). To damp inter-area oscillations, the controller modulates the power transfer of the PDCI, a ±500 kV dc transmission line in the WI. The control system utilizes real-time phasor measurement unit (PMU) feedback to construct a commanded power signal which is added to the scheduled power flow for the PDCI. After years of design, simulations, and development, this controller has been implemented in hardware and successfully tested in both open and closed-loop operation. The most important design specifications were safe, reliable performance, no degradation of any system modes in any circumstances, and improve damping to the controllable modes in the WI. The main finding is that the controller adds significant damping to the modes of the WI and does not adversely affect the system response in any of the test cases. The primary contribution of this paper, to the state of the art research, is the design methods and test results of the first North American real-time control system that uses wide area PMU feedback. [ABSTRACT FROM AUTHOR]

Composite power system reliability evaluation is computationally time-consuming because the optimal power flow (OPF) with the least load curtailment is calculated for a large number of samples. Most current studies of probabilistic simulation methods focus on sampling techniques to improve the sampling efficiency and decrease the calculations of the OPF. This paper proposes a fast reliability evaluation method that accelerates the calculation of the OPF using multi-parametric linear programming (MPLP). In this paper, the sampled transmission line statuses are considered by the transmission line status dictionary (TLSD). We match the line status of each sample with the scenarios in the TLSD. For matching samples, the generation status and the sampled load are treated as MPLP parameters of the DC-OPF evaluation model. A dynamic learning algorithm is applied to solve the MPLP problem. Case studies are conducted on both IEEE Reliability Test Systems and a provincial power system in China. The results show that the proposed method improves the evaluation efficiency by 23–30 times compared with the normal DC-OPF-based model. [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]

Independent system operators (ISOs) are responsible for the secure and economic operation of the power systems. Accordingly, ISOs should solve an optimal power flow to minimize the operating cost of a system while meeting the system's security constraints. However, transmission congestion could drastically limit more economical generating units from being dispatched in the power system operation. In this paper, a decentralized transmission switching is introduced in the operation of multi-area power systems to manage the congestion both on regional transmission lines and tie lines while considering credible contingencies. Our proposed methodology relies on a decentralized optimization methodology. Thus, regional control centers in areas would be able to locally manage the congestion within their regional networks as well as tie lines connecting them to their neighboring areas. Several testing systems are studied in this paper to test the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Utilization of abundant measurements provided by supervisory control and data acquisition (SCADA) system has attracted increasing attention. Real-time estimation of transmission line parameters, utilizing voltage and power flow measurements provided by remote terminal units (RTUs) located at two substations across the line, has been investigated, recently. This paper improves this approach by introducing a novel exact linear reformulation of the problem, which can be solved in closed form. The distributed-parameter model of long transmission lines is considered and its parameters are estimated in a non-iterative manner using RTU measurements. The method is also extended to estimate transformer series impedance and tap position by SCADA measurements, linearly. As such, the disadvantages associated with the previous iterative approach, e.g. concern over convergence, for transmission line parameters are avoided. Moreover, the novel technique for estimating transformer parameters allows to determine the tap position as well as updated transformer series impedance. Furthermore, a thorough analysis is presented to take the measurement accuracy into account. Simulation results for different transmission lines and transformers in the IEEE 118-bus test system are reported, where the result indicate successful performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Instrument transformers (ITs) once installed in the field are seldom calibrated. We propose two tests to detect systematic errors in capacitive voltage transformers (CVTs) and current transformers (CTs). The first test, a direct test, compares the mid-point voltage estimated from both ends of a transmission line using PMU data. The second test, an indirect test, analyzes the deviation of the estimated positive sequence line parameter values from the design values. Subsequently, we propose a robust method to simultaneously determine the positive sequence line parameters and IT calibration factors. Special care is given to numerical sensitivity of the method to the noise in the data and we show by Monte Carlo simulations that the proposed approach is accurate and robust. A noteworthy feature of this paper are the case studies based on field PMU data for short, medium, and long length lines of 400 kV and 765 kV. It clearly demonstrates the stability of both line parameters and IT calibration factors and hence justifies the claims. [ABSTRACT FROM AUTHOR]

This paper analytically derives the small-disturbance stability limit of a grid-connected wind farm with multiple PMSGs in the timescale of DC voltage dynamics. The derived stability limit reveals the mechanism about how the dynamics of DC voltage control and the PLLs may jointly affect the small-disturbance stability of the wind farm. Flagging the impact of PMSGs by a computational function, the stability limit indicates that decreasing value of flagging function or/and increasing maximum eigenvalue of network reactance matrix implies increased instability risk. Particularly, increasing the loading conditions and number of PMSGs in the wind farm or/and the length of transmission line connecting the wind farm with main grid may make the wind farm more prone to the loss of small-disturbance stability. Although the stability limit is derived under the assumption of identical dynamics of PMSGs, the derived small-disturbance stability limit can be applied to approximately assess the small-disturbance stability of the wind farm in the timescale of DC voltage dynamics, where dynamics of PMSGs may be either similar or considerably different. The approximate small-disturbance stability assessment is simple because the assessment does not need to establish the parametric model of the wind farm. [ABSTRACT FROM AUTHOR]

A recent proactive defense mechanism, named as moving-target-defense (MTD), has been proposed as a prevailing topic that is capable of actively changing transmission line reactance to preclude cyberattacks. However, the MTD strategy has seldom been studied for the unbalanced AC distribution system in the existing literature. Towards the end, this paper proposes a deeply-hidden MTD (DH-MTD) to elaborately hide both the self and mutual reactance of each phase at the transmission line installed with D-FACTS devices. Both the branch and injection power phasor measurement functions are integrated into DH-MTD in the cyberattack scenario and under the normal operating condition, while the system voltage stability is ensured. The proposed DH-MTD model is solved using a nonlinear least square (NLS) method based on the trust-region algorithm due to the non-Gaussian noise assumption. Also, we cope with the MTD allocation (MTDA) problem using a data-driven normalized PDF peak residual (NPPR) index. The effectiveness of the proposed DH-MTD method is demonstrated in the unbalanced IEEE 123-bus distribution system against both branch and node cyberattacks. [ABSTRACT FROM AUTHOR]

Cascading failure simulation data contain many fault chains (FCs), which can present cascading failure propagation paths. In cascading failure process, some component outages play dominating roles in propagation, indicating the common characteristics among different FCs. The commonness is embodied as combinations of components which are vulnerable to trip and cause serious blackout consequences. In addition, a component outage will increase the outage probability of relevant components and induce dependent outage in subsequent stage. Such relevance between two components can be called component outage causality. A combination of sequential component outages with outage causalities, which exists in different FCs and leads to system load loss, can be regarded as a cascading failure pattern (CFP). Statistical characteristics of FCs indicate that CFPs are variously distributed in different FCs, can present propagation paths and cause different impacts on system blackouts. This paper proposes a cascading failure pattern (CFP) identification method based on sequential pattern mining approach. The proposed method focuses on mining CFPs from massive FCs, quantifies the influence of CFP on system blackout and identifies the critical ones. The proposed method is verified with FCs data on IEEE 39-bus and 118-bus test systems. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-stage model of zonal electricity markets with day-ahead market clearing and real-time re-dispatch and balancing that accounts for transmission line switching at both stages. We show how the day-ahead problem with switching can be formulated as an adaptive robust optimization problem with mixed integer recourse and present a new algorithm for solving the adversarial max-min problem that obeys the structure of an interdiction game. We apply the model on a realistic instance of the Central Western European system and comment on the impacts of both proactive and reactive transmission switching on the operating costs of the system. Part I presents day-ahead models of a short-term zonal electricity market with switching, and describes our algorithmic approach for solving these models efficiently. Part II describes variants of the real-time model, and presents the results of our case study on the Central Western European market. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-stage model of zonal electricity markets with day-ahead market clearing, and real-time re-dispatch and balancing that accounts for transmission line switching at both stages. We show how the day-ahead problem with switching can be formulated as an adaptive robust optimization problem with mixed integer recourse, and present a new algorithm for solving the adversarial max-min problem that obeys the structure of an interdiction game. We apply the model on a realistic instance of the Central Western European system, and comment on the impacts of both proactive, and reactive transmission switching on the operating costs of the system. Part I presents day-ahead models of a short-term zonal electricity market with switching, and describes our algorithmic approach for solving these models efficiently. Part II describes variants of the real-time model, and presents the results of our case study on the Central Western European market. [ABSTRACT FROM AUTHOR]

During major power system disturbances, when multiple component outages occur in rapid succession, it becomes crucial to quickly identify the transmission interconnections that have limited power transfer capability. Understanding the impact of an outage on these critical interconnections (called saturated cut-sets) is important for enhancing situational awareness and taking correct actions. This paper proposes a new graph theoretic approach for analyzing whether a contingency will create a saturated cut-set in a meshed power network. A novel feature of the proposed algorithm is that it lowers the solution time significantly making the approach viable for real-time operations. It also indicates the minimum amount by which the power transfer through the critical interconnections should be reduced so that post-contingency saturation does not occur. Robustness of the proposed algorithm for enhanced situational awareness is demonstrated using the IEEE-118 bus system as well as a 17,000+ bus model of the Western Interconnection (WI). Comparisons made with different approaches for power system vulnerability assessment prove the utility of the proposed scheme for aiding power system operations during extreme exigencies. [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]

This paper investigates the modal repulsion happened in the sub-synchronous resonance between a synchronous generator and series-compensated transmission line. The investigation is based on the closed-loop model of the series-compensated power system consisted of the torsional and electrical open-loop subsystems. Analytical explanation is presented to show how the SSO modal repulsion is formed as the result of moving close and apart between two open-loop SSO modes. Analysis is carried out to indicate that the peak of the SSO modal repulsion occurs when the two open-loop SSO modes from the torsional and electrical subsystem are closest to each other on the complex plane, which is referred to as the open-loop modal coupling. Estimation on the peak, i.e., the maximum damping degradation of the SSO modes, is derived in the paper. Subsequently, a method of open-loop modal analysis is proposed. Applications of the proposed method of open-loop modal analysis to study the SSOs caused by the DFIGs under the condition of the modal repulsion in the power system are demonstrated and evaluated by example power systems. The concept of modal repulsion explains why the grid connection of the DFIGs may bring about the SSO instability risk in the power system. [ABSTRACT FROM AUTHOR]

Network-constrained market clearing procedures in pool-based electricity markets of hydropower systems have traditionally neglected the constraints associated with physical and operating aspects of hydroelectric generation (hydraulic constraints). Such constraints are generally taken into account by means of expost procedures, which may lead to suboptimal results regarding social welfare function. This paper proposes a network-constrained auction model for hydrothermal systems that represents the hydraulic constraints in detail. The objectives of the paper are twofold: the analysis of the impact of hydraulic constraints on market clearing prices and on generation/consumption scheduling and the analysis of the influence of strategic offering of hydro plants in the operation of a hydraulic cascade. As some of the hydraulic constraints are nonlinear and intertemporal, linearization techniques are applied, resulting in a mixed-integer linear programming problem. [ABSTRACT FROM PUBLISHER]