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Special Feature that lists the names of people involved in the review of technical papers for the IEEE Transactions on Industry Applications and Industry Applications Magazine. [ABSTRACT FROM AUTHOR]

In interconnected power systems, operated by several system operators, the participating areas are strongly dependent on their neighbors. In order to identify the economically efficient generation dispatch in each area, a distributed multi-area optimal power flow (OPF) must be solved. Additionally, installation of an increasing number of HVDC lines to deal with increased power flows from renewable generation is expected to change the power system operation paradigm. The controllability introduced by the HVDC lines should be considered and incorporated in the OPF algorithm. In this paper we introduce a formulation for the distributed solution of the OPF problem in multi-area systems consisting of both HVAC and HVDC lines. We show the applicability of this formulation on two different operating schemes for HVDC grids and we compare their performance with a central solution for the mixed HVAC/HVDC grid. The proposed formulations are based on a linearized solution of the OPF problem. The only data to be exchanged between the areas pertains to the border nodes. [ABSTRACT FROM AUTHOR]

This paper is concerned with a fuzzy analysis of power-flow (PF) involving uncertainties of load demands and network parameters. The crux of this paper is to propose an advanced fuzzy arithmetic. Fuzzy transformation method merges with backward–forward sweep in order to evaluate the contribution and propagation of uncertainty in IEEE 33-bus and 69-bus distribution systems. Results are validated by true intervals and random ranges. To determine true intervals, Global Optimization Problems (GOPs) are defined and solved through derivative-based and free techniques. To estimate random ranges, Monte-Carlo Simulations (MCSs) are employed. Our findings confirm that the sharpness of fuzzy intervals, tractability of computations, and applicability of possibility distributions. Following scenario-based evaluations, this paper discusses new implications of power losses, voltage profiles, optimal re-configuration, feeder extension, and reactive power compensation so that results would be beneficial to system planners and operators. Altogether, this paper provides a blueprint for a new way to handle uncertainties in a wide variety of power system problems without global optimization, linearization, and randomized simulations. [ABSTRACT FROM AUTHOR]

This paper introduces a new consensus-based control scheme for distributed power systems to solve the distributed economic dispatch (DED) problem. With the development of renewable energy, smart grid, and microgrid, more and more distributed generators will be connected to power systems. Thus the distributed control schemes become more and more important for power systems to control and manage the distributed equipment. Therefore, some consensus-based methods are published previously to solve the DED problem. But the challenge to apply the consensus-based method is to meet the power balance constraint without the centralized facility, since the value of power mismatch is hard to be obtained for a distributed control system. To solve the problem, this paper proposes the method to combine the frequency control methods with the consensus protocol from graph theory to develop the DED control method, so that the real power between the load and the generation can be balanced during the economic dispatch. With this method, a totally distributed optimal control scheme is obtained. The PI frequency controller and neural network frequency controller are employed to develop the DED control method. Then the communication failure problem is considered in this paper. The robust DED control method is proposed to improve the robustness of this distributed control method, allowing the system to stay at the optimal dispatching even if the communication is failed. In addition, the model of transmission line losses is incorporated in the DED problem to reduce the line losses. Finally, several case studies are given in this paper to verify the proposed method. [ABSTRACT FROM AUTHOR]

Fast and accurate power-flow methods are of great importance, especially in near real-time optimal operation of power systems. This importance will be even more highlighted in the presence of more repetitions of power-flow calculations, which cause more computational complexities in optimization problems. As a solution, in this paper, a novel fast and accurate approach of linear power-flow formulation is proposed. Principles of the proposed approach are based on dividing power-flow calculations into base and variable parts. To this aim, at first, system modeling of base and variable parts are presented. For the base-part modeling, utilizing a nonlinear power-flow, an accurate base power-flow (BPF) is extracted. Afterwards, by linearizing the power system around the BPF, variable-part model which is the result of a linear fitting process, is obtained. Then, it is shown that the variable-part of the operating point is always a function of the obtained base-part and variable-part models. In this paper, by focusing on the stochastic application of the proposed approach, different uncertainties in a distribution system are considered. Finally, numerical results carried out in the Matlab environment, for a IEEE 34-bus standard distribution system and then a 1486-bus case study, verify the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

After any major blackout, recreating the exact scene is one of the crucial but foundation steps in postmortem analysis. This helps in identifying and understanding the exact causes and sequence of events to avoid such failures in the future. Rather, power system restoration demands critical skills which involves deployment of appropriate strategies based on information about various factors, notably the extent and duration of the blackout, location of black-started units, interconnections with neighbouring systems, generator capabilities, and selecting appropriate restoration paths. The actual execution of the restoration plan consists of many surprises of unique nature and a lot of learning’s to avoid future occurrences of such incidents. The restoration efforts and failure of Mumbai grid failure on October 12, 2020, are highlighted in this paper. The paper first proposes formulating the dynamic models to get a better insight of the restoration process in the event of critical issues during this incident. The various challenges faced in systematic recovery of such a large system and lessons learnt from it forms focus of the paper. The paper also discusses factors not covered in existing literature, such as weather, fuel availability, and water mass oscillations which plays an important role in the restoration. [ABSTRACT FROM AUTHOR]

Closed-form determination of fault current limiter (FCL) impedance for symmetrical faults was reported previously using a mathematically rigorous method. In this paper, extensions of the method to asymmetrical faults are presented. Single line-to-ground faults and line-to-line faults are studied. As shown in this paper, although the material corresponding to asymmetric faults use the same basic concepts described before, the different nature of asymmetrical faults and application of symmetrical components theory lead to a different formulation. Also, the graphical representation of asymmetrical faults is as contour plots instead of the circle diagrams for three-phase faults. A three-bus and the IEEE 39-bus systems are used to illustrate the virtues of the method for the proper selection of FCLs impedance. Results demonstrate that the FCL designed, as shown in this paper, works properly for asymmetrical faults. The new formulation and graphical representation for asymmetrical faults are compatible with traditional power system short-circuit analysis software. An example with both symmetrical and asymmetrical faults is presented to illustrate how a full FCL impedance design can be achieved with the method. [ABSTRACT FROM AUTHOR]

This paper considers distribution systems with a high penetration of distributed, renewable generation and addresses the problem of incorporating the associated uncertainty into the optimal operation of these networks. Joint chance constraints, which satisfy multiple constraints simultaneously with a prescribed probability, are one way to incorporate uncertainty across sets of constraints, leading to a chance-constrained optimal power flow problem. Departing from the computationally heavy scenario-based approaches or approximations that transform the joint constraint into conservative deterministic constraints; this paper develops a scalable, data-driven approach which learns operational trends in a power network, eliminates zero-probability events (e.g., inactive constraints), and accurately and efficiently approximates bounds on the joint chance constraint iteratively. In particular, the proposed framework improves upon the classic methods based on the union bound (or Boole’s inequality) by generating a much less conservative set of single chance constraints that also guarantees the satisfaction of the original joint constraint. The proposed framework is evaluated numerically using the IEEE 37-node test feeder, focusing on the problem of voltage regulation in distribution grids. [ABSTRACT FROM AUTHOR]

Communication systems introduce uncertainties that directly impact power system management. Quantitative analysis of such impact is essential for power system reliability and resilience. This paper establishes rigorous relationships between communication packet delivery ratio and errors on optimal load tracking and allocation (OLTA) in DC microgrids (MGs). By modeling channel uncertainties using packet delivery ratio and communication network topologies, impact of communication packet loss on the distributed OLTA algorithm for DC MGs is studied. It is shown that communication packet loss directly affects the convergence rate of the distributed OLTA algorithm under intermittent renewable generations. The results of this paper quantitatively characterize a practical criterion for securing reliability of OLTA solutions under communication uncertainty. Simulation studies using a real-world DC MG are conducted to validate the theoretical findings. [ABSTRACT FROM AUTHOR]

This paper investigates the potential contribution that interconnectors can provide to efficiently support the security of interconnected power systems. The proposed modelling setup introduces a radical paradigm shift in the operation of the interconnectors and in their interactions with multiple markets. To the best of our knowledge, this is the first paper that models a simultaneous allocation of the interconnector capacity for the exchange of energy and of inertia-dependent primary frequency response. The benefits and impact of this new methodology are evaluated with typical market indicators (e.g., social welfare and interconnector revenues) under two different paradigms: a centralized approach where the interconnectors are operated to minimize the system operational cost and a market-based framework where the interconnectors are privately-owned assets with self-interested objectives. By modelling the interconnectors as “price-maker”, the proposed work quantifies the potential inefficiencies of market solutions while considering key elements such as capacity withdrawing. A case study of the GB-France systems assesses the value of interconnectors on system efficiency and security under the considered paradigms. [ABSTRACT FROM AUTHOR]

With the development of Internet technology, information has become an increasingly important asset for the operation and planning of power systems. However, the existing studies and practices pay little attention to information value evaluation, i.e., the potential for information to be converted into actual economic benefits. To this end, this paper designs an information market framework and proposes a generalized information valuation model to help price data in smart grids efficiently. Here we analyze the information value of photovoltaic (PV)-related data in a power system operation problem. Specifically, we examine how additional meteorological and PV power data help to improve day-ahead forecasting accuracy, thus enhancing unit commitment (UC). In this paper, information quality is captured by two indices of a set of PV-related data, i.e., Shannon entropy and non-noise ratio. Then a neural network-based engine is employed to predict day-ahead hourly solar power on the premise of input datasets with different information quality. Here we define forecasting accuracy as information utility, and discover an exponential relationship between such utility and information quality. Finally, a two-stage stochastic UC model is formulated to quantify the contributions of different PV-related datasets, in which real-time solar power deviation is penalized. In this instance, the economic value of PV-related data is measured as the operational cost reduction induced by forecasting accuracy improvement, which we find can be estimated by information quality. Case studies based on the IEEE 30- and 118-bus systems validate the effectiveness of the proposed paradigm and method. [ABSTRACT FROM AUTHOR]

This paper deals with the short-circuit analysis of distribution systems dominated by Voltage Source Converters (VSCs). A novel methodology has been proposed in this paper for short-circuit calculation of power systems populated with VSCs where the control modes and potential current-saturated operation of power converters are considered. The studied distribution system has been modeled using an element-based steady-state formulation that includes the converter equations in both normal operation and fault scenarios. Then, equilibrium points of the studied distribution system are identified by solving the established systems of equations for different potential current-saturation states of the VSCs. The methodology identifies possible solutions involving different saturation states of different converters. The proposed methodology is applied to a specific case study of a distribution system penetrated with VSCs in both grid-forming and grid-following control. The short-circuit analysis results indicate that VSCs operation shows a significant impact on the short-circuit equilibrium points of the studied system. In addition, multiple equilibrium points may exist depending on whether the grid-forming converter is saturated or not. The existence of multiple equilibrium points is validated through dynamic simulations. [ABSTRACT FROM AUTHOR]

With the expansion of system scale and data size in power systems, data-driven methods are gradually becoming widely used. However, compared with traditional methods, data-driven methods face more threats in data security and algorithm security. This paper proposes a black box data injection attack method against data-driven strategies in power systems. To obtain a stealthy attack scheme with the greatest impact, an attack vector generator based on deep convolutional neural networks (DCNN) is designed. The generator includes a node selector, a filter, an encoder, and a decoder. The node selector is used to select the most likely successful attack scheme for the filter, the encoder is used to extract sample features, and the decoder is used to generate disturbances based on the features. The proposed generator is trained with an improved generative adversarial network (GAN) and can generate minimal disturbances in real time based on measurement data from the power grid. The effectiveness of the proposed method is demonstrated with an attack experiment on an online transient stability application. [ABSTRACT FROM AUTHOR]

Economic dispatch with valve-point effect (EDVPE) considered is presented as a more accurate model of the real problem compared to the conventional economic dispatch model. It is basically a non-convex, non-differentiable, and multi-modal optimization model with many local minima. Part I of the paper focuses on the local minimum analysis of the EDVPE. The analysis indicates that a local minimum consists of the singular points, the small convex regions, and the output of a slack unit that is dispatched to balance the load demand. Two types of local minima are identified and the second type could be ignored. To verify the rationality of the analyses, a traverse search has been performed to solve the EDVPE with and without considering the transmission loss on different test systems. All the simulation results support the analysis given in the paper. To effectively solve the EDVPE on a large-scale power system, based on the analysis presented in this paper, a new method, dimensional steepest decline method, is proposed in Part II of the paper. [ABSTRACT FROM PUBLISHER]

A Battery Energy Storage System (BESS) is a reliable resource to provide energy for various power system applications. The BESS can increase the flexibility and reliability of the renewable energy dispatch. Wind energy has the largest contribution among renewable energy resources and its control has become a research focus in power systems area. This paper introduces a novel BESS control to manage the net energy exchange between a wind farm and the grid in an electricity market. A Receding Horizon Control (RHC) scheme is proposed for optimal operation of the BESS in the presence of operational constraints. The proposed method seeks a decision policy to manage operation of the BESS to increase daily profits. Utilizing short-term wind and price forecasts provide valuable information for the BESS controller to obtain the best times to charge batteries, discharge the stored energy, or purchase energy from the DA market. An optimization problem is formulated considering BESS costs and operational constraints. This optimization problem, at each time step, is solved using the RHC scheme. All wind and electricity price data and case studies in this paper are based on MISO energy market data. [ABSTRACT FROM AUTHOR]

This paper studies the robust matrix completion (RMC) problem with the objective to recover a low-rank matrix from partial observations that may contain significant errors. If all the observations in one column are erroneous, existing RMC methods can locate the corrupted column at best but cannot recover the actual data in that column. Low-rank Hankel matrices characterize the additional correlations among columns besides the low-rankness and exist in power system monitoring, magnetic resonance imaging (MRI) imaging, and array signal processing. Exploiting the low-rank Hankel property, this paper develops an alternating-projection-based fast algorithm to solve the nonconvex RMC problem. The algorithm converges to the ground-truth low-rank matrix with a linear rate even when all the measurements in a constant fraction of columns are corrupted. The required number of observations is significantly less than the existing bounds for the conventional RMC. Numerical results are reported to evaluate the proposed algorithm. [ABSTRACT FROM AUTHOR]

Understanding smart grid cyber attacks is key for developing appropriate protection and recovery measures. Advanced attacks pursue maximized impact at minimized costs and detectability. This paper conducts risk analysis of combined data integrity and availability attacks against the power system state estimation. We compare the combined attacks with pure integrity attacks—false data injection (FDI) attacks. A security index for vulnerability assessment to these two kinds of attacks is proposed and formulated as a mixed integer linear programming problem. We show that such combined attacks can succeed with fewer resources than FDI attacks. The combined attacks with limited knowledge of the system model also expose advantages in keeping stealth against the bad data detection. Finally, the risk of combined attacks to reliable system operation is evaluated using the results from vulnerability assessment and attack impact analysis. The findings in this paper are validated and supported by a detailed case study. [ABSTRACT FROM AUTHOR]

Vacuum interrupter is widely used in the medium-voltage power system. Controlling the arc by the magnetic field is an effective method to improve the breaking capacity. The transverse magnetic field (TMF) forces the constricted arc to rotate to reduce local overheating. In this paper, three kinds of TMF contacts, which are Swastika-type contact, cup-shaped contact, and double-TMF contact that combines Swastika-type and cup-shaped contacts coaxially, are investigated in a demountable vacuum chamber with a high-speed camera. The arc voltage and current are also recorded. The experiments were conducted with circuit currents from 5 to 20 kA (root mean square) with a frequency of 50 Hz. There are four current levels in the experiment, which are 5, 10, 15, and 20 kA, and at least three tests are taken for each current level. The results showed that under low current (I = 10 kA), the arc of the three TMF contacts did not rotate. Under high current (I = 20 kA), it was observed that the arc of Swastika-type and double-TMF contacts rotated in the gap. The arc speed of double-TMF contacts is higher than that of Swastika-type contacts. The cup-shaped contacts have the highest arc voltage and noise among the three TMF contacts. The Swastika-type contacts were eroded most seriously. The simulation results show the force distribution of the arc on different locations. The resultant force makes the arc rotate counterclockwise. [ABSTRACT FROM AUTHOR]

Development of smart grid technologies has created a promising atmosphere for smart cities and energy trading markets. Especially, traditional electricity consumers evolve into prosumers who produce as well as consume electricity in modern power electric systems. In this evolution, the electric power industry has tried to introduce the notion of local energy markets for prosumers. In the local energy market, prosumers purchase electricity from distributed energy generators or the other prosumers with surplus electricity via a local power exchange center. For this purpose, this paper proposes joint geometric clustering and truthful auction schemes in the local energy markets. The proposed clustering scheme is designed for distribution fairness of the distributed energy generator for serving prosumers, where the scheme is inspired by expectation and maximization based unsupervised learning. Moreover, this paper proposes an auction mechanism for truthful electricity trading in a local energy market. In order to guarantee truthful electricity trading, the proposed auction mechanism is constructed based on the Vickrey–Clarke–Groves auction, which was proven to guarantee truthful operations. The Hungarian method is also considered in addition to the auction. The simulation results for the auction verify that the utilities of local market energy entities are maximized when the prosumers are truthful. [ABSTRACT FROM AUTHOR]

This paper proposes to replace controlled islanding, which is a defense mechanism against cascading failures, by tree partitioning whereby some of the tie-lines connecting the clusters are still connected in such a way that the cluster-level graph forms a tree. Tree-partitioning prevents line failures from spreading between clusters, similarly as for islanding, but keeps the clusters connected. That results in three main advantages. Power transfers between the clusters can still take place, helping to balance each cluster and limiting any necessary load shedding. Fewer lines are cut, which reduces the shock to the system. There is no need to re-synchronize the clusters after the emergency. This paper offers a simple graph-theoretic justification for tree-partitioning, rather than one based on the spectral analysis of network Laplacian proposed in the literature. It also proposes a two-stage methodology, which utilizes spectral clustering for splitting a network into tree-connected clusters. Test results performed on the 118 node IEEE test network have confirmed the usefulness of the methodology. [ABSTRACT FROM AUTHOR]

The increasing integration of variable renewable energy increases the demand for a power system’s frequency regulation resources. The decreasing share of controllable power generators makes the frequency regulation resources insufficient. Simultaneously, distributed energy resources (DER) on the distribution network side, such as storage devices, electric vehicles, and controllable building energy systems, have excellent potential to provide frequency support. However, power system dispatchers cannot control these resources in the same manner as conventional power sources. These sources have power output uncertainties and cannot directly access power system communication networks. This paper proposes a cloud-edge collaboration and wireless communication coordination framework to facilitate DER frequency regulations. The cloud balances the power uncertainty of controllability in edges together with computing burden, wire, and wireless communication loads. Also, the edges adjust storage’s power outputs to achieve frequency regulations and covering PV power fluctuations. A numerical case study demonstrates the effectiveness of the proposed method. The solution holds 95.5% frequency regulation adjustable power capacity of theoretical maximum on average. Meanwhile, the computing costs reduce by 36.3%, and wire communication only operates in 0.35% of a day as a supplement (reduces by 99.65%). [ABSTRACT FROM AUTHOR]

The increasing prevalence of technologies such as advanced metering and controls and continuously variable power electronic devices are enabling a radical shift in the way frequency regulation is performed in the bulk power system. This is a welcome development in light of the increase of unpredictable and variable generation. The idea of active participation of loads in frequency markets is not new, but the rapidly changing landscape of the power grid requires new techniques for successful integration of new types of resources; this paper works towards that end. Previously, it has been shown that residential HVAC systems can be aggregated and used to provide frequency regulation by utilizing their thermal energy capacity and flexibility of energy consumption. The virtual battery model—a first-order linear dynamical model—was analytically shown to be an accurate and simple model to capture the flexibility of residential HVAC systems. This paper presents a technique for creating the same battery-type models for many other types of systems, which can be much more complex. Our technique is based on stress testing detailed software models of physical systems. A realistic case study involving the terminal building of a small airport is presented as evidence of the effectiveness of the proposed techniques. [ABSTRACT FROM PUBLISHER]

In this paper, detectability analysis is studied and extended to guide selection of measurements for the dynamic state estimation (DSE) of a synchronous machine. To make sure that the DSE converges, past studies suggested that enough measurements must be available to make the system observable. In this paper, the convergence condition is relaxed via detectability analysis to reduce the number of required measurements. Because the objective of the DSE is to estimate the current states as time progresses, it is shown that a DSE observer can converge not only for an observable system but also for an unobservable system if the eigenvalues corresponding to the unobservable states are stable. Simulation results using the IEEE 10-machine, 39-bus system show that the unscented-Kalman-filter-based DSE can converge when measurements are chosen such that the unobservable states have stable eigenvalues. In comparison with observability analysis, the proposed application of detectability analysis can reduce the number of measurements required for the existence of a DSE observer. [ABSTRACT FROM AUTHOR]

The increasing penetration of wind power may deteriorate power system frequency performance. This paper proposes a novel virtual filter (VF) approach for a grid-connected wind energy conversion system to mitigate power system frequency fluctuations. The principle is to modify the traditional wind power controller to emulate a physical energy storage system to smooth the wind power output. The VF proposed in this paper is tuned as a band-stop filter to selectively reject the power system frequency-sensitive components in wind power output. Therefore, the power system frequency fluctuations can be correspondingly reduced with only a small amount loss of wind energy. The advantages of the proposed VF are: 1) no need for a physical deployment of energy storage system, 2) no need for power system frequency signal and communication channel, and 3) ability to selectively filter the power system frequency sensitive components. Simulation results verified the outstanding performance of the proposed VF in system frequency fluctuation mitigation, while with less wind energy loss comparing with existing method. [ABSTRACT FROM AUTHOR]

Maintaining an accurate power system model is crucial for a variety of applications such as electricity markets. In this paper, the cyber security issue induced by critical parameters in electricity market operations is investigated. Critical parameters are a set of model parameters the errors of which cannot be detected due to the lack of local measurements. In this paper, it is first proven that the criticality property of parameters is independent from system operating points, i.e., the maliciously injected errors will always remain undetectable. Then, the cyber attack against critical parameters is formulated as a bilevel programming problem in search of the optimal attack strategy or the worst situation faced by the system operators. An effective algorithm for solving this problem is also provided. Simulation results verify that by injecting undetectable errors into critical model parameters, the locational marginal prices in electricity markets can be significantly distorted, which leads to financial benefits for the attackers. [ABSTRACT FROM AUTHOR]

DC shipboard power systems have been considered as a promising solution for stricter environmental regulations on ships due to their main benefits in fuel savings with variable speed engines and easy integration of energy storage systems. In order to employ the dc solution in the shipboard power systems, the dc power systems have to be protected from a system fault with protection selectivity to minimize impacts of the fault or to avoid other undesirable situations in the system. For low-voltage dc shipboard power systems, a three-level protection has been proposed: 1) fast action (first)—bus separation by solid-state dc bus-tie switch; 2) medium action (second)—feeder protection by high-speed fuse; and 3) slow action (third)—generator–rectifier fault controls. This paper proposes a new method by means of additional bus capacitance added in main dc buses to help reliable operation of the three-level protection. The principle of the proposed method is introduced and the sizing of the additional bus capacitance is addressed in this paper. With the modeling of the dc shipboard power systems, the analyses of voltage drops for the bus separation failure and fault clearing time for the feeder protection are carried out to verify the proposed method. The results show that the proposed method not only mitigates the voltage drop for the bus separation failure, but also achieves the selectivity and the sensitivity for the feeder protection. [ABSTRACT FROM AUTHOR]

In this part of the paper (Part II), available technical solutions to minimize or prevent wildfires caused by power networks are reviewed in more detail. These methods include fundamental changes to power system equipment, periodic checkups and maintenance, identification of faults via voltage/current waveforms, changes to protection and relaying settings and coordination, and installation of new power system apparatus. The strengths and drawbacks of each method are discussed. The discussion section brainstorms some future possible solutions that smart-grid technologies can enable. The paper concludes that there has neither been enough research in universities nor enough investment by industry to develop viable preventive solutions for wildfires that initiate from the daily operation of electrical power grids. This, in the authors’ opinion, is the crucial time for investment in research and development to tackle the lethal wildfire problem while electric power networks offer “the lowest hanging fruits to pick.” [ABSTRACT FROM AUTHOR]

As the share of renewables in the grid increases, the operation of power systems becomes more challenging. The present paper proposes a method to formulate and solve chance-constrained optimal power flow while explicitly considering the full nonlinear ac power flow equations and stochastic uncertainties. We use polynomial chaos expansion to model the effects of arbitrary uncertainties of finite variance, which enables to predict and optimize the system state for a range of operating conditions. We apply chance constraints to limit the probability of violations of inequality constraints. Our method incorporates a more detailed and a more flexible description of both the controllable variables and the resulting system state than previous methods. Two case studies highlight the efficacy of the method, with a focus on satisfaction of the ac power flow equations and on the accurate computation of moments of all random variables. [ABSTRACT FROM AUTHOR]

This paper utilizes the Newton Raphson (NR) iterative algorithm to solve a detailed heat balance equation for overhead transmission conductors, for the purpose of calculating a Dynamic Line Rating or temperature-dependent impedance using real-time or forecasted weather data. Provided ambient weather conditions, conductor parameters and electrical current passing through the conductor, a starting guess is formed and the iterative solution method arrives upon a solution within a preset solution tolerance. A simple method to approximate the Rayleigh Number / Nusselt Number and Reynolds Number / Nusselt Number relationships is proposed to ensure successful convergence. The paper performs a thorough, numeric electrothermal conductor simulation to demonstrate proper solution convergence. This exercise identifies a minimum conductor temperature rise necessary for the solution method to converge successfully. Error related to the minimum starting conductor temperature rise, and error introduced by the approximated air property functions is illustrated. The temperature solution method is compared with several well-known thermal models. [ABSTRACT FROM AUTHOR]

This paper proposes a modeling approach for characterizing the probability of wildfire ignition caused by faults on power distribution systems. The proposed model serves as a starting point in research literature to illustrate, from an analytical perspective, the many factors that influence wildfire ignitions in power distribution systems. This paper presents the series of events that leads to power-system-related wildfire ignitions, and characterizes the wildfire ignition probability as a combination of the probability that a fault occurs along a power distribution line segment, and the probability that the fault results in the sustained ignition of a vegetation fuel bed surrounding the line. The proposed model integrates a variety of data including environmental conditions, power system protection settings, and power system line flows. A case study is performed on a test 33-bus distribution system using observed historical weather data from a high-threat fire district in California. The California case study is utilized to investigate the effects of three primary factors (wind speed, line congestion, and protection settings) on wildfire ignition probability. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy, such as wind power, has brought great challenges to the power system operation due to its uncertainty. Flexibility, which measures the ability of power system to deal with the uncertainties, is critical for power system to adapt to the new era of renewable energy. The rising electrical demand of the water distribution system (WDS) creates opportunities for power system to leverage the flexibility provided by WDS. This paper investigates the water-energy relationship between these two systems and makes full use of the water pumps and tanks in the WDS to enhance the power system flexibility. Current WDS designs did not consider well the role WDS plays in the power system. This hinders the WDS from being fully used by power system to provide flexibility. An optimization model is proposed to determine the optimal tank size of WDS, which may provide the maximum available flexibility of power system. The effect of tank size on water quality is also investigated to ensure that the supplied water quality is not compromised. Moreover, a Benders-based heuristic algorithm is proposed to find the optimization solution more efficiently and to protect the data of each energy system. Results of case study highlight the merit of the proposed optimization design and the advantage of using WDS to provide flexibility for power system. [ABSTRACT FROM AUTHOR]

Due to the development of cyber-physical systems for modernizing power grids, vulnerability assessment has become an emerging focus in power system security studies. With the increasing deployment of cyber-enabled technologies in power systems, modern power system is prevalently exposed to a wide gamut of cybersecurity threats. Thus, there is an urgent need to develop effective cyber risk management mechanisms to mitigate the growing cyberthreats. Recently cyber insurance is emerging as a promising financial instrument for cyber risk management of critical infrastructures such as power grids. In this paper, a new cyber-insurance design framework is proposed to hedge against the risk of massive monetary losses due to potential cyberthreats. Traditionally, insurance companies serve as third-party risk-bearers offering aggregate design of the insurance policy which may stipulate high premiums. However, unusual loss patterns may still lead to excess financial risk for insurance companies. In this paper, coalitional insurance is introduced as a promising alternative or supplement to the traditional insurance plans provided by insurance companies. Under the proposed cyber-insurance model, several transmission operators form an insurance coalition, where the coalitional premiums are derived considering system vulnerabilities and loss distributions. The indemnity which covers the loss of TOs complies with the budget sufficiency. Overall, this study proposes a novel coalitional platform based cyber-insurance design that estimates the insurance premiums via cybersecurity modeling and reliability implication analysis. [ABSTRACT FROM AUTHOR]

This paper deals with the hierarchical control architecture of meshed multi-terminal dc networks. The key difference with previous works is that the customarily adopted centralized secondary control is replaced by a fully-distributed, agent-based approach, in which the nodes of the network cooperate and self-coordinate in order to bring the network to an optimal operating state. The paper covers the theoretical aspects and shows how, by setting the problem as a general consensus problem and by making use of modern optimization techniques such as the alternating direction of multipliers, the optimal power flow problem of a dc grid can be solved in a distributed manner. The proposed method is validated on a network with 27 nodes obtained by properly adapting a 30 bus ac network. [ABSTRACT FROM AUTHOR]

Although Switched Reluctnace Motors have many advantages, vibration is known as their most severe drawback acting as an impediment limiting their widespread use in industrial and domestic applications. Through electromechanical relationships, it is shown that the first-order time derivative of applied phase voltage and second-order time derivative of radial force directly affect the amplitude of generated vibration, especially at the beginning of demagnetization instance. Therefore, a set of criteria is stated in this paper meeting which ensures having low vibration intensity. In this paper, three types of demagnetization voltages are proposed which comprehensively meet the stated criteria. These voltages share the same characteristics contributing to the vibration reduction in Switched Reluctance Motor. Two vital parameters of Synchronous Counter and Coefficient are included in the proposed demagnetization voltages which must be meticulously chosen in order to be effective. Noticeable contribution of the proposed methods to the vibration alleviation is validated through simulation and experimental tests conducted under different working conditions. [ABSTRACT FROM AUTHOR]

This paper demonstrates that false data injection (FDI) attacks are extremely limited in their ability to cause physical consequences on $N-1$ reliable power systems operating with real-time contingency analysis (RTCA) and security constrained economic dispatch (SCED). Prior work has shown that FDI attacks can be designed via an attacker-defender bi-level linear program (ADBLP) to cause physical overflows after re-dispatch using DCOPF. In this paper, it is shown that attacks designed using DCOPF fail to cause overflows on $N-1$ reliable systems because the system response modeled is inaccurate. An ADBLP that accurately models the system response is proposed to find the worst-case physical consequences, thereby modeling a strong attacker with system level knowledge. Simulation results on the synthetic Texas system with 2000 buses show that even with the new enhanced attacks, for systems operated conservatively due to $N-1$ constraints, the designed attacks only lead to post-contingency overflows. Moreover, the attacker must control a large portion of measurements and physically create a contingency in the system to cause consequences. Therefore, it is conceivable but requires an extremely sophisticated attacker to cause physical consequences on $N-1$ reliable power systems operated with RTCA and SCED. [ABSTRACT FROM AUTHOR]

A semi-analytical formulation is presented in this paper for the probability computation of branch current in multiphase systems. The developed formula is derived based on the linear power flow model in rectangular coordinates. The system uncertainty injections can be renewable energy resources or loads and are modeled using a Gaussian mixture model (GMM). The developed formula can be used to compute the line current violation probability as well as integrate into optimal power flow problem as chance-constraint relaxation. The proposed formula is first compared with the Matlab embedded numerical integration function to show its performance. Besides, the semi-analytical formula is validated and compared with the Monte Carlo simulation method using the IEEE 123-bus system, EPRI Ckt5, and Ckt7 systems. [ABSTRACT FROM AUTHOR]

The wide implementation of information and communication technologies (ICT) cause power system operations exposed to cyber-attacks. Meanwhile, the tendency of integrated multi energy vectors has worsened this issue with multiple energy coupled. This paper proposes a two-stage risk-averse mitigation strategy for water-energy systems (WESs), incorporating power, natural gas and water systems against false data injection attacks (FDIA) under water-energy nexus. The FDIA on individual sub-systems is modelled through hampering false data integrity to the systems. An innovative two-stage risk-averse distributionally robust optimization (RA-DRO) is proposed to mitigate uneconomic operation and provides a coordinated optimal load shedding scheme for the nexus system security. A coherent risk measure, Conditional Value-at-Risk is incorporated into the RA-DRO to model risk. A Benders decomposition method is used to solve the original NP-hard RA-DRO problem. Case studies are demonstrated on a WES under water-energy nexus and results show that the effectiveness of the method to mitigate risks from potential FDIA and renewable uncertainties. This research provides WES operators an economic system operation tool by optimally coordinating energy infrastructures and implementing reasonable load shedding to enhance cybersecurity. [ABSTRACT FROM AUTHOR]

Concerns about the cybersecurity and resilience of power systems have heightened in electric utilities and regulatory agencies over the past decade mainly because of the unpredictable target, location and scale of cyberattacks and the potential severity of consequences. The cybersecurity of pilot protection is paramount in bulk power systems considering their prevalence and the crucial role they play in protecting critical assets and preventing large system disturbances and major blackouts. This paper investigates the resilience of pilot protection using a co-simulation platform based on OPAL-RT simulator and Riverbed Modeler. It is demonstrated that software-defined networking for operational technology (OT SDN) significantly improves the resilience of pilot protection to false data injection (FDI) attacks compared to traditional networks. Moreover, the resilience of OT SDN based pilot protection to denial of service (DoS) attack against the SDN controller is investigated both in the proactive and reactive modes of operation. The simulation results verified the resilience of OT SDN controller in OT SDN based pilot protection to DoS attacks in the proactive mode of operation. [ABSTRACT FROM AUTHOR]

The use of synchronized measurement technology leads to a more reliable and secure operation of the power system. Phasor calculation is needed for all buses where a phasor measurement unit is installed, and fast and precise estimation is necessary for accurate monitoring, protection and control. The Prony algorithm is one promising method due to its capability to estimate phasor adaptively with changing frequency. The algorithm projects the signal on $L$ exponentially damped sine functions, where $L$ is the order of the Prony. However, the order under different conditions should be adapted automatically to reduce computation time. To adaptively specify the order, the empirical mode decomposition (EMD) method is proposed in this paper to be combined with the Prony and named EMD-Prony. The EMD decomposes a signal into finite single oscillatory modes, representing the number of modes in the signal. EMD is also used as a pre-processing step to filter noise from an input signal of Prony. Therefore, EMD is proposed here as an assistant of Prony in a phasor estimation. Finally, the proposed method is tested on the benchmark signals proposed in the IEEE standard, signals obtained from a simulated power system, and measured data from a real-world power system. [ABSTRACT FROM AUTHOR]

In many power systems, the increased penetration of inverter-based renewable generation will cause a decrease in kinetic energy storage, leading to higher frequency excursions after a power disturbance. This is the case of the future Nordic Power System (NPS). The look-ahead study reported in this paper shows that the chosen units participating in Frequency Containment Reserves (FCR) cannot keep the frequency above the prescribed threshold following the outage of the largest plant. This analysis relies on a detailed model of the Northern European grid. The latter is compared to the classical single-mass equivalent, and the impact of voltage-dependent loads is assessed in some detail. Next, the paper focuses on emergency power control of the HVDC links that connect the NPS to the rest of the European grid, which can supplement or even replace part of the FCR. The proper tuning of that control is discussed. Finally, the analysis is extended to the HVDC links connecting the future North Sea Wind Power Hub under two configurations, namely low and zero inertia. The impact of outages in the latter sub-system is also assessed. The material to simulate the system with industrial software is made publicly available. [ABSTRACT FROM AUTHOR]

Unified power flow controller (UPFC) gains growing application in power systems due to its power flow regulation ability. However, there is still a dilemma in the incorporation of UPFC into security-constrained economic dispatch (SCED). The modeling of UPFC involves nonlinear and nonconvex operational constraints, which is difficult to solve efficiently and accurately. Conventional methods adopted Taylor expansion or sensitivity analysis to realize the convexification of UPFC models, which leads to a loop structure and is subject to initial point choice. In this paper, a novel three-terminal injected UPFC model is proposed. In the proposed model, the voltage source variables are eliminated completely. Instead, only power injection variables are introduced to equivalently describe physical characteristics and constraints of UPFC. The nonlinear and nonconvex operational constraints of UPFC are transformed into mixed integer second-order cone form. Moreover, compared with conventional UPFC models, the control characteristic of UPFC is considered in a more accurate and practical manner in the proposed SCED, which helps to prevent potential risks of power flow over-limit under N-1 contingencies. Simulation results show the effectiveness and efficiency of the established solution. [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]

High renewable energy penetration increases the electricity seasonal imbalance in the long-term timescale. Power system planning needs to consider the optimal configuration of various flexibility resources and electricity balance in different timescales. The coupling of multiple timescales largely increases the computation complexity of the power system planning problem. Thus, this paper presents an efficient source-grid-storage co-planning model which incorporates a year-round hourly operation simulation. To improve the computation efficiency of the planning model, from the temporal scale, a self-adaptive compact panorama time series (CPTS) model is applied, which greatly reduces the number of variables related to short-term decisions. From the spatial scale, a network-constrained relaxed clustered unit commitment (NC-RCUC) model is introduced, which significantly reduces the number of variables related to unit commitment decisions. Case studies on the modified Garver’s 6-node system and HRP-38 system prove the validation and efficiency of the proposed model (“HRP” stands for high renewable penetration). The studies on the China power grid in 2035 demonstrate the future planning results of generation, transmission and storage in China power systems based on the proposed model. [ABSTRACT FROM AUTHOR]

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation issues in the detection of FDIAs in smart grids. Inspired by federated learning, a FDIA detection method based on secure federated deep learning is proposed in this paper by combining Transformer, federated learning and Paillier cryptosystem. The Transformer, as a detector deployed in edge nodes, delves deep into the connection between individual electrical quantities by using its multi-head self-attention mechanism. By using federated learning framework, our approach utilizes the data from all nodes to collaboratively train a detection model while preserving data privacy by keeping the data locally during training. To improve the security of federated learning, a secure federated learning scheme is designed by combing Paillier cryptosystem with federated learning. Through extensive experiments on the IEEE 14-bus and 118-bus test systems, the effectiveness and superiority of the proposed method are verified. [ABSTRACT FROM AUTHOR]

Currently, the architecture of Line Current Differential Relays (LCDRs) is designed to respond to internal faults on the protected line using local and remotely-communicated current measurements. However, this architecture cannot distinguish between real faults and cyber-induced attacks whose goal is to cause false tripping of the line protected by the LCDR. In this paper, we propose an Anomaly-Based Scheme (ABS) for detecting false-tripping attacks against LCDRs, in the form of relay attacks, replay attacks, general false-data-injection attacks, and time-synchronization attacks. The ABS employs the Isolation Forest algorithm, which is trained on features determined from local current measurements to confirm real faults and differentiate them from false-tripping attacks. No trip command will be issued unless the sensed fault is confirmed as a non-attack by the ABS. The performance of the proposed ABS is tested and validated using the IEEE 9-bus benchmark in PSCAD/EMTDC environment. Simulation results show that the proposed ABS: (i) can accurately detect different categories of cyberattacks, (ii) does not negatively impact the accuracy of the fault-detection function, and (iii) is robust to the change in the power system’s operating point. [ABSTRACT FROM AUTHOR]

This paper proposes a collaborative machine learning-based framework to detect cyber-attacks in a power system, leading to deviation in the state variable behavior. Based on the proposed architecture, three different machine learning-based methods, i.e., visualization, classification, and clustering, are employed and compared to find the best one in the FDIA detection process. To this end, pre-processing is employed in the first stage. In the second stage, the patterns of the state vectors are transferred into features. Hence, 24 statistical features, including measures of central tendency, variability, measures of shape, and position, are extracted to find various properties. Then, in the third stage, a supervised algorithm is employed to rank and find the most crucial features in FDIA. In the fourth stage, an unsupervised dimensionality reduction technique (PCA) is applied to reduce the feature space. In the fifth and last stage, visualization, classification, and clustering-based methods are developed to detect FDIA. To simulate an attack, it is assumed that an intruder decreases or increases the state vectors at different buses with various attack parameters (i.e., 0.90, 0.95, 0.96, 0.97, 0.98, 1, 1.02, 1.03, 1.04, 1.05, and 1.10). The proposed method effectiveness is assessed on the New York Independent System Operator (NYISO) data applied to the IEEE 14-bus system. The results presented in the paper from different scenarios (i.e., phase angle ($\theta $), voltage magnitude ($V_{m}$), measurements, and multiple attacks) on a real-world dataset demonstrate that the collaborative optimized PCA-Density-based machine learning technique can detect most of the attack samples with good performance scores (i.e., recall, precision, F1) and outperforms the other investigated methods. Moreover, it is general and adaptable enough to cover the situation where either the system characteristics or the attack behavior changes. [ABSTRACT FROM AUTHOR]

The structure stability of the diameter-expanded conductor with fewer inner wires is the principal limitation in its large-scale use at present. As the traditional design method cannot be adopted to solve this problem, the instability properties of the diameter-expanded conductors were studied in this paper. To perform this analysis, different typical diameter-expanded conductors with fewer inner wires were chosen for the sheave tests under different working conditions at first. Then the simulation model as well as the instability criterion was established to analyze the influence factors of the structure stability. Finally, the synchronous stringing tests were carried out to assess the correctness of the model proposed. The results showed that the weakened support of the inner layer(s) and the local buckling of the external wires are the main causes of the wire jumping phenomenon. Therefore, a reasonable increase in the outmost wire's gap and decrease in the inner wire's gap are feasible to improve the load-carrying ability of the diameter-expanded conductor. [ABSTRACT FROM AUTHOR]

A large class of three-phase electrical power systems possess symmetry conditions that make it possible to describe their behavior using single-input single-output transfer functions with complex coefficients. In such cases, an extended root locus method can be used to design control laws, even though the actual systems are multi-input multi-output. In this paper, the symmetric conditions for a large class of power systems are analyzed. Then, the root locus method is revisited for systems with complex coeffcients and used for the analysis and control design of power systems. To demonstrate the benefits of the approach, this paper includes two examples: 1) a doubly fed induction machine and 2) a three-phase LCL inverter. [ABSTRACT FROM PUBLISHER]

This paper investigates a procedure of coordinated tuning of power system decentralized damping controllers based on reduced-order model (ROM). In the paper, the cross-gramian technique is applied to obtain an equivalent ROM for power systems. Once the controllers' locations are selected appropriately, the critical modes are approximated well in the reduced model. The controllers are designed on ROM using search algorithm and then tested on the unreduced system to demonstrate their availability. The benefit of adopting ROM is to decrease the complexity of objective function computation. The proposed method is tested on power systems with 4-machine and 156-machine to validate its efficiency. [ABSTRACT FROM AUTHOR]

The ever-increasing integration of variable wind energy requests for a power system with high flexibility. In this paper, we formulate the real-time economic dispatch problem as a multi-stage robust program to leverage flexible resources, especially energy storage systems, in a broader timescale, and also to avoid the risk of high costs in critical scenarios. The multi-stage robust program is decomposed to the dynamic programming form and the fast robust dual dynamic programming (FRDDP) algorithm is developed to solve it efficiently. To tackle the nonconvexities caused by the inter-temporal constraints of ESSs, an estimation-correction method is developed, and measures of the approximation accuracy are presented. Comprehensive case studies comprising units up to 1371 are carried out to verify the effectiveness of the proposed model. Numerical results show that compared with the existing ones, the proposed multi-stage robust model achieves lower cost under the worst-case scenario and shows better scalability in large-scale systems. [ABSTRACT FROM AUTHOR]