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This paper presents an optimization framework for sequential reconfiguration using an assortment of switching devices and repair process in distribution system restoration. Compared to existing studies, this paper considers types, capabilities and operational limits of different switching devices, making it applicable in practice. We develop a novel multi-phase method to find the optimal sequential operation of various switching devices and repair faulted areas. We consider circuit breakers, reclosers, sectionalizers, load breaker switches, and fuses. The switching operation problem is decomposed into two mixed-integer linear programming (MILP) subproblems. The first subproblem determines the optimal network topology and estimates the number of steps to reach that topology, while the second subproblem generates a sequence of switching operations to coordinate the switches. For repairing the faults, we design an MILP model that dispatches repair crews to clear faults and replace melted fuses. After clearing a fault, we update the topology of the network by generating a new sequence of switching operations, and the process continues until all faults are cleared. To improve the computational efficiency, a network reduction algorithm is developed to group line sections, such that only switchable sections are present in the reduced network. The proposed method is validated on the IEEE 123-bus and 8500-bus systems. [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]

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

This paper proposes a novel data driven framework for detecting topology transitions in a distribution network. The framework analyzes data from phasor measurement units (PMUs) and relies on the fact that changes in network topology results in changes in the structure and admittance of the network. Using voltage and current phasors recorded by PMUs, the proposed method approximates network parameters using an ensemble-based deep learning model and thus, it does not require any knowledge of network parameters and load models. Using the prediction error of the proposed model, a connectivity matrix which shows the status of switches is constructed. In contrast to other methods, this proposed framework does not require a library of voltage and current transients associated with possible network transitions. It can also detect simultaneous switching actions and is robust to noise and load variations. The model yields a lower error detection rate, and its performance is validated using a modified version of the IEEE 33 bus network and a real feeder located in Queensland, Australia, under full and partial observability conditions. The proposed model has also been compared with another data driven method in terms of inference time and error detection rates. [ABSTRACT FROM AUTHOR]

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

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

This paper presents a methodology and set of validation criteria for the systematic creation of synthetic power system test cases. The synthesized grids do not correspond to any real grid and are, thus, free from confidentiality requirements. The cases are built to match statistical characteristics found in actual power grids. First, substations are geographically placed on a selected territory, synthesized from public information about the underlying population and generation plants. A clustering technique is employed, which ensures the synthetic substations meet realistic proportions of load and generation, among other constraints. Next, a network of transmission lines is added. This paper describes several structural statistics to be used in characterizing real power system networks, including connectivity, Delaunay triangulation overlap, dc power flow analysis, and line intersection rate. The paper presents a methodology to generate synthetic line topologies with realistic parameters that satisfy these criteria. Then, the test cases can be augmented with additional complexities to build large, realistic cases. The methodology is illustrated in building a 2000 bus public test case that meets the criteria specified. [ABSTRACT FROM AUTHOR]

The reliable operation of a power distribution system relies on a good prior knowledge of its topology and its system state. Although crucial, due to the lack of direct monitoring devices on the switch statuses, the topology information is often unavailable or outdated for the distribution system operators for real-time applications. Apart from the limited observability of the power distribution system, other challenges are the nonlinearity of the model, the complicated, unbalanced structure of the distribution system, and the scale of the system. To overcome the above challenges, this paper proposes a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system. Specifically, by using the very limited number of measurements available that are associated with the forecast load data, we efficiently recover the full Bayesian posterior distributions of the system topology under both normal and outage operation conditions. This is performed through an adaptive importance sampling procedure that greatly alleviates the computational burden of the traditional Monte-Carlo (MC)-sampling-based approach while maintaining a good estimation accuracy. The simulations conducted on the IEEE 123-bus test system and an unbalanced 1282-bus system reveal the excellent performances of the proposed method. [ABSTRACT FROM AUTHOR]

DC grid has become an important application in power transmission. However, the exist works only have the method to obtain the droop coefficient in a radial topology. Also, this droop coefficient is for V-I droop control. There is no such like method to obtain the droop coefficient for the P-V droop control. This paper proposed a new method for a complex dc grid to obtain the droop coefficients. Firstly, based on the converter control strategies, the types of converter were classified. It will help to find out which kinds of converter can be participated into the dc-side voltage control. Secondly, a virtual node was defined, and the matrix of the dc grid was reshaped to fit the new added virtual node by using the proposed simplification method. An example was shown how this method worked. After that a new method of calculating the P-V droop coefficient was proposed. Finally, a simulation model was investigated to verify if the proposed method can operate in a real system. The results showed that the simplification method can ensure the mathematical relationships of the dc system. And simulations show good performances of the droop coefficient calculation method. [ABSTRACT FROM AUTHOR]

The proliferation of distributed energy resources (DERs), located at the Distribution System Operator (DSO) level, bring new opportunities as well as new challenges to the operations within the grid, specifically, when it comes to the interaction with the Transmission System Operator (TSO). To enable interoperability, while ensuring higher flexibility and cost-efficiency, DSOs and the TSO need to be efficiently coordinated. Difficulties behind creating such TSO-DSO coordination include the combinatorial nature of the operational planning problem involved at the transmission level as well as the nonlinearity of AC power flow within both systems. These considerations significantly increase the complexity even under the deterministic setting. In this paper, a deterministic TSO-DSO operational planning coordination problem is considered and a novel decomposition and coordination approach is developed. Within the new method, the problem is decomposed into TSO and DSO subproblems, which are efficiently coordinated by updating Lagrangian multipliers. The nonlinearities at the TSO level caused by AC power flow constraints are resolved through a dynamic linearization while guaranteeing feasibility through “ $l_1-$ proximal” terms. Numerical results based on the coordination of the 118-bus TSO system with up to 32 DSO 34-bus systems indicate that the method efficiently overcomes the computational difficulties of the problem. [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]

To analyze oscillation phenomenon caused by the interaction between converters and an AC grid, the impedance/admittance analysis method is a popular solution, in which each electrical component is represented by an external impedance/admittance matrix and a lumped matrix is formed for stability analysis. However, for converter-integrated power systems considering typical collector subsystems (e.g., the radial and the ring collector subsystems in wind farms and PV stations), the impedance network reduction to form the lumped impedance/admittance matrix (LIM/LAM) becomes complicated particularly for a ring collector subsystem, which affects the efficiency of the oscillation analysis. To address this problem, this paper proposes a method that can transform a typical topology of collector subsystems into a pure-parallel topology so that lumped admittance matrix is much easier to be derived. Algorithm complexity analysis confirms its computational advantages. A fifty-converter system is used to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Accurate grid topology information is of paramount importance for routine power system operations, while the growing availability of synchrophasor data offers the opportunity to identify topology changes in real time. Identification of bus split events, where the substation becomes electrically disconnected, is becoming increasingly important for maintaining the security of power systems. This paper aims to provide an efficient modeling and monitoring framework for bus split events by using a concise bus-branch representation. The linear sensitivity analysis is first performed to quickly evaluate the grid-wide impact of such events. Furthermore, the synchrophasor data enabled identification problem is formulated by matching the changes in bus phase angles (and possibly line flows). To address the resultant bilinear multiplication involving the binary connectivity variables, the McCormick relaxation technique is leveraged to attain an equivalent mixed-integer linear program reformulation that is efficiently solvable. Numerical studies on the IEEE 14-bus and 300-bus systems demonstrate the validity and efficiency of the proposed identification algorithm towards real-time implementation. [ABSTRACT FROM AUTHOR]

A state estimation framework that eliminates the need for a topology processor is presented in this paper. By retaining switching devices (SDs) in the network model, this approach allows estimation of their statuses. Consequently, topology error detection becomes part of the SE process. Since this approach requires expansion of bus-branch models with SDs, the conventional state estimation formulation is accordingly modified to avoid numerical issues due to extremely small (large) impedance values of open (closed) switching devices. The scalability of the proposed framework is achieved by parallel processing, which is implemented after partitioning the system into zones. The measurement overhead is kept minimal by utilizing two optimal measurement placement algorithms and taking advantage of KCL-based virtual measurements. Case studies presented show that the proposed method can identify concurrent bad data and topology errors. The improvements in computation times due to parallel processing are demonstrated through simulations on the IEEE 300-bus system with and without zone-partitioning. [ABSTRACT FROM AUTHOR]

This paper presents the modeling of some protective relays commonly used in generation and transmission systems, and their integration in three-phase RMS dynamic simulation tool. The three-phase models of the network and the power apparatuses, utilizing phase frame representation, enlarges the possibility to better represent the protection systems, since the relays involving ground and neutral circuitry can be modeled. The network can be modeled with a node-breaker topology representation, facilitating the integration of protecting relays and the switchgear. The relay modeling framework can also be used in positive-sequence RMS dynamic simulation tools with few adjustments in the measured quantities. Simulation results in realistic small and large-scale systems showing the performance of the proposed relay modeling framework and a comparison with an EMT tool are presented. [ABSTRACT FROM AUTHOR]

The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed-integer nonlinear program and, hence, hard to solve. In this paper, we propose a heuristic algorithm that is based on the recently developed convex relaxation of the ac optimal power flow problem. The algorithm is computationally efficient and scales linearly with the number of redundant lines. It requires neither parameter tuning nor initialization for different networks. It successfully computes an optimal configuration on all four networks we have tested. Moreover, we have proved that the algorithm solves the feeder reconfiguration problem optimally under certain conditions for the case where only a single redundant line needs to be opened. We also propose a more computationally efficient algorithm and show that it incurs a loss in optimality of less than 3% on the four test networks. [ABSTRACT FROM PUBLISHER]

This paper presents a method to optimize equipment investments in multizonal transmission systems, considering spatial properties of the areas of focus. Together with a probabilistic technique for assessing nodal injection capability, the method in the paper completes the methodology of a long term transmission system planning tool. Transmission topology, line route and technology are optimized through iterative application of linear integer programming and Dijkstra's shortest path algorithm. By optimizing the transmission route, the spatial properties of the area of focus are taken into account, which in turn can significantly influence the installation costs of transmission equipment. The optimization method considers both AC and DC technology and takes the N-1 security criterion into account. [ABSTRACT FROM PUBLISHER]

This paper proposes an automatic algorithm for the on-line implementation of a robust static state estimator on large power systems. The proposed algorithm maximizes the number of outliers and cyber-attacks that the estimator can resist while giving reliable estimates. The large power system is decomposed in several islands or subsystems, and a highly robust regression estimator, namely the least trimmed squares estimator (LTS), is implemented on each island to detect bad data. Executing the estimators in parallel will greatly reduce the computation time of the robust static state estimator. The introduced method is compared with two cycle detection graph-theory approaches, namely depth-first search (DFS) and minimum spanning tree (MST), which have been adapted here for power state estimation. Simulations on IEEE 14, 30, 57, 118, 145, and 300 bus systems show the superior performance of the proposed algorithm over the adapted DFS and MST. The algorithm could reduce significantly the number and size of cycles in the system. Furthermore, the number of detected outliers, and attacks is maximized while the observability of the system is ensured. Attacks or outliers on both measurements, and topology of the grid are detected as well. [ABSTRACT FROM AUTHOR]

Topology identification (TI) is a key task for state estimation (SE) in distribution grids, especially the one with high-penetration renewables. The uncertainties, initiated by the time-series behavior of renewables, will almost certainly lead to bad TI results without a proper treatment. These uncertainties are analytically intractable under conventional framework—they are usually jointly spatial-temporal dependent, and hence cannot be simply treated as white noise. For this purpose, a hybrid framework is suggested in this paper to handle these uncertainties in a systematic and theoretical way; in particular, big data analytics are studied to harness the jointly spatial-temporal statistical properties of those uncertainties. With some prior knowledge, a model bank is built first to store the countable typical models of network configurations; therefore, the difference between the SE outputs of each bank model and our observation is capable of being defined as a matrix variate—the so-called random matrix. In order to gain insight into the random matrix, a well-designed metric space is needed. Auto-regression (AR) model, factor analysis (FA), and random matrix theory (RMT) are tied together for the metric space design, followed by jointly temporal-spatial analysis of those matrices which is conducted in a high-dimensional (vector) space. Under the proposed framework, some big data analytics and theoretical results are obtained to improve the TI performance. Our framework is validated using IEEE standard distribution network with some field data in practice. [ABSTRACT FROM AUTHOR]

Traditional cyberattack strategies on the electricity market only consider bypassing bad data detections. However, our analysis shows that experienced market operators can detect abnormal locational marginal prices (LMPs) under the traditional attack model during real-time (RT) operations, because such attack model ignores the characteristics of the LMP itself and leads to price spikes that can be an easy-to-detect signal of abnormality. A detection approach based on the concept of critical load level (CLL) is used to help operators identify risky periods when operators would be prone to overlooking abnormal LMPs. During safe periods, the abnormal LMPs are identified according to the operator's experience, while in risky CLL intervals, a N-x cyber contingency analysis is proposed to help independent system operators (ISOs) detect abnormal LMPs. Further, this paper constructs a new type of cyberattack strategy capable of not only bypassing bad data detection in the state estimation stage but also disguising the compromised LMPs as regular LMPs to avoid market operators’ alerts in a realistic scenario wherein the attacker has imperfect information on system topology. Finally, the proposed analysis method and the attack strategy are evaluated through numerical studies on the PJM 5-bus system and the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

Voltage source converter (VSC) based multi -terminal HVDC (VSC-MTDC) systems have emerged as flexible collector systems for multi-area interconnected AC/DC hybrid grids with high share of volatile renewables energy. However, it remains an open question as how to exploit the flexible and cooperative regulation of multiple VSC stations and enhance secure operation on the premise of information privacy protection of multiple independent dispatch areas. This paper proposed an Analytical Target Cascading (ATC)-based three-layer decentralized optimization approach on flexible operation of VSC-MTDC hybrid systems. The low layer is a chance-constrained stochastic optimal power flow (SOPF) problem for AC grids. To guard against the secure operation risk by a VSC's random unipolar atresia fault, a modified loss of load probability index (MLOLP) is proposed to improve the day-ahead generation-reserve scheme. The middle layer and the high layer are a multiperiod OPF problem for VSC stations and the MTDC grid, respectively, where a detailed power regulation model is built to fully exert the flexible cooperation of multiple VSC stations. Two case systems are tested to verify the effectiveness and superiority of the proposed flexible operation hierarchy. [ABSTRACT FROM AUTHOR]

This paper develops a long term transmission expansion optimization methodology taking the probabilistic nature of generation and demand, spatial aspects of transmission investments and different technologies into account. The developed methodology delivers a stepwise investment plan to achieve the optimal grid expansion for additional transmission capacity between different zones. In this paper, the optimization methodology is applied to the Spanish and French transmission systems for long term optimization of investments in interconnection capacity. [ABSTRACT FROM PUBLISHER]

The ancillary services that could be provided by the distributed generators and the energy storage systems are expected to give great added value to the microgrid-based smart grid topologies. These services must be integrated into the control system of the microgrids. In this paper, the pseudo-state-of-charge concept is introduced to improve energy storage management. Additionally, a noninvasive-to-the-inverter PV-plant control strategy, based on the remote control of PV-strings actuators, is presented and applied on a microgrid-based smart grid topology. The operation of the microgrid with the improved control infrastructure and the iterative algorithm is compared, in terms of reliability, to a microgrid with a different control strategy and topology. The experimental results highlight the advantages of the developed strategy. [ABSTRACT FROM AUTHOR]

Topology design is a critical task for the reliability, economic operation, and resilience of distribution systems. This paper proposes a distributionally robust optimization (DRO) model for designing the topology of a new distribution system facing random contingencies (e.g., imposed by natural disasters). The proposed DRO model optimally configures the network topology and integrates distributed generation to effectively meet the loads. Moreover, we take into account the uncertainty of contingency. Using the moment information of distribution line failures, we construct an ambiguity set of the contingency probability distribution, and minimize the expected amount of load shedding with regard to the worst-case distribution within the ambiguity set. As compared with a classical robust optimization model, the DRO model explicitly considers the contingency uncertainty and so provides a less conservative configuration, yielding a better out-of-sample performance. We recast the proposed model to facilitate the column-and-constraint generation algorithm. We demonstrate the out-of-sample performance of the proposed approach in numerical case studies. [ABSTRACT FROM AUTHOR]

In this paper, we model topology control through transmission switching as a recourse action in the day-ahead operation of power systems with large-scale renewable generation resources. We prove that transmission switching could only reduce the linear objective value of direct current optimal power flow when congestion exists. However, we also show, through a simple example, that unit commitment cost could be reduced by transmission switching even in the absence of congestion. To solve the stochastic unit commitment with topology control within reasonable computational time, we proposed a heuristic that first decomposes a practical system into zones and then solves the problem for each zone in parallel. The benefit of topology control recourse is demonstrated on a network representing the Central European System. We compare the costs of the network with different loading and renewable generation conditions. The cost reduction of the test system can reach 3.34% with heavy load and large-scale renewable generation while in a single zone the cost reduction can be above 7%. [ABSTRACT FROM PUBLISHER]

This paper presents our study results on the correlated assignment of generation, load, or connection buses in a given grid topology and the development of an optimized search algorithm to improve the proposed synthetic grid model, called RT-nestedSmallWorld. A numerical measure, called “bus type entropy”, was proposed in an initial study on this subject to characterize the correlation of bus type assignments in realistic grids. In this paper, its definition has been redefined and improved with the help of some newly obtained data of realistic grids so that the scaling property of a real-world grid's entropy value versus the network size can be effectively captured with a curve-fitting approach. With the help of the derived scaling function, we will be able to determine an appropriate target entropy value that a correlated bus type assignment should assume in a specific N-bus grid network. Therefore, our previously proposed synthetic power grid modeling has been enhanced with a direct search procedure for the best bus type assignments in a specific N-bus grid topology, saving the mandatory, but most of the time unattainable, requirement of a set of realistic grid data with a comparable network size for identifying the search target. Finally, the performance of the proposed approach is examined based on some available grid data including the IEEE test cases, the NYISO-2935, the ERCOT-5633, and the WECC-16994 systems. [ABSTRACT FROM PUBLISHER]

This paper proposes a generalized approach of the per unit normalization, named complex per unit normalization (cpu), to improve the performance of fast decoupled power flow methods applied to emerging distribution networks. The proposed approach takes into account the changes envisaged and also already faced by distribution systems, such as high penetration of generation sources and more interconnection between feeders, while considering the typical characteristics of distribution systems, as the high R/X ratios. These characteristics impose difficulties on the performance of both backward-forward sweep and decoupled-based power flow methods. The cpu concept is centred on the use of a complex volt-ampere base, which overcomes the numerical problems raised by the high R/X ratios of distribution feeders. As a consequence, decoupled power flow methods can be efficiently applied to distribution system analysis. The performance of the proposed technique and the simplicity of adapting it to existing power flow programs are addressed in the paper. Different distribution network configurations and load conditions have been used to illustrate and evaluate the use of cpu. [ABSTRACT FROM PUBLISHER]

An electric power distribution system is operated in several distinct radial topologies by opening and closing of system's sectionalizing and tie switches. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). This paper presents a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. Specifically, a minimum weighted least absolute value estimator is proposed that uses the line flow measurements, historical/forecasted load data, and ping measurements and solves a mixed-integer linear program (MILP) to estimate the operational topology and any outaged sections simultaneously. We thoroughly validate the accuracy of the proposed approach using IEEE 123-bus and a 1069-bus three-phase multi-feeder test system with the help of numerous simulations. It is observed that the approach performs well even at high percentages of measurement errors. [ABSTRACT FROM AUTHOR]

Due to the rapid development of distributed renewable generation, an effective risk assessment and early warning mechanism for active distribution networks is of great significance to maintain the system reliability and enhance energy grid resilience. In this paper, a novel risk assessment model is proposed to assess the probability of potential disturbances to the grid and provide accurate advice for trading prosumers’ renewable energy. The model can compute node failure probability (FP) for transmission networks as well as the area FP for distribution networks, while combining the two perspectives by topology analysis. A weather threshold value is first derived to define the extreme weather condition. Then the FP of transmission lines is calculated by joint probability models under four instances of extreme climate. For distribution networks, the weather influence is obtained by applying the Rare Events Logistic Regression model initially. Then the equipment fault related to the geographical feature is captured using feeder taxonomy and hierarchical clustering. Furthermore, the accidental factor as a new parameter is introduced to evaluate the vandalism, vegetation, and operating fault to the grid. Finally, the warning information and advice for customers will be presented after fault chain analysis. The FP for a specific area in Australia is analyzed in case studies to verify the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes a new pricing mechanism for the integration of flexible loads in distribution grids. This price is calculated from an envisioned two-layer local distribution grid market, where flexible load aggregators are price takers and the distribution system operator (DSO) is the market operator. On a day-ahead basis, the DSO runs the local market and clears distribution locational marginal prices (DLMPs). Aggregators purchase energy based on these DLMPs. However, depending upon grid conditions (losses/congestion), the DLMP value increases, causing aggregators to bear high energy procurement cost. To mitigate this issue, a second layer is introduced to compute ex-ante scenario-based Hedging Rights. Through a combination of these two layers, the proposed mechanism 1) improves market competition among the involved entities, 2) maintain the congestion alleviation property of DLMPs, and 3) incorporate the intertemporal energy requirements of flexible loads. The proposed framework is tested on an IEEE benchmark distribution grid. The simulation results show that the proposed pricing mechanism allows aggregators to achieve higher cost-savings, while preserving physical power flow evaluation feature of DLMP. [ABSTRACT FROM AUTHOR]

This paper presents a distributed synchrophasor data management (DSDM) technique for wide-area monitoring systems. The proposed technique focuses on managing voltage/current phasor data measured from a specific target bus by defining neighboring phasor measurement units (PMUs). We developed an algorithm for searching neighboring PMUs by interpreting the power network topology as a graph structure. By exploiting the data of neighboring PMUs, we constructed a multi-channel structure to recover low-quality entries by using the parallel implementation of long short-term memory networks. A successive output decision-making rule automatically determines the final output, considering the occurrence of defective input, data quality of the measured data, and operational conditions. The proposed DSDM can complement existing centralized management techniques by preserving information on local dynamics. In particular, because of the multi-channel structure, DSDM can provide robust responses to defective data in neighboring PMUs, such as an unintended change in a network topology. We verified the effectiveness of the DSDM with real-world synchrophasor data as well as simulated data from the IEEE 68-bus test system. [ABSTRACT FROM AUTHOR]

The knowledge of distribution grid models, including topologies and line impedances, is essential for grid monitoring, control and protection. However, such information is often unavailable, incomplete or outdated. The increasing deployment of smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes a two-stage framework for distribution grid modeling using SM data. In the first stage, the network topology is identified by reconstructing a weighted Laplacian matrix of distribution networks. In the second stage, a least absolute deviations (LAD) regression model is developed for estimating line impedance of a single branch based on the nonlinear (inverse) power flow model, wherein a conductor library is leveraged to narrow down the solution space. The LAD regression model is originally a mixed-integer nonlinear program whose continuous relaxation is still non-convex. Thus, we specially address its convex relaxation and discuss the exactness. The modified regression model is then embedded within a bottom-up sweep algorithm to achieve the identification across the network in a branch-wise manner. Numerical results on the IEEE 13-bus, 37-bus and 69-bus test feeders validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

DC microgrids are prone to small-signal instabilities due to the presence of tightly regulated loads. This paper develops a decentralized stability certificate which is capable of certifying the small-signal stability of an islanded DC network containing such loads. Utilizing a novel homotopy approach, the proposed standards ensure that no system eigenmodes are able to cross into the unstable right half plane for a continuous range of controller gain levels. The resulting “standards” can be applied to variety of grid components which meet the specified, but non-unique, criteria. These standards thus take a step towards offering plug-and-play operability of DC microgrids. The proposed theorems are explicitly illustrated and numerically validated on multiple DC microgrid test-cases containing both buck and boost converter dynamics. [ABSTRACT FROM AUTHOR]

To integrate large-scale islanded onshore wind power with different sizes, this paper proposes an integration system based on the cascaded hybrid HVDC transmission system, which consists of LCC and several MMCs in series connection at the DC side of the rectifier. A large-scale wind farm is connected with one LCC and one MMC while several small-scale wind farms are connected with MMCs directly. Owing to the hierarchical integration arrangement, the operating flexibility can be improved with reduced capacity and the number of step-up interfacing transformers. A resilient DC voltage control is proposed for the integration system to adaptively redistribute power among the converters during wind power fluctuations. Firstly, the topology and operating characteristics of the wind power integration system are introduced. Then, a resilient DC voltage control is proposed to ensure stable operation during wind power curtailments. Finally, a simulation model of the hybrid cascaded HVDC transmission system is built in PSCAD/EMTDC to verify the effectiveness. The research results show that the system provides a new option for long-distance transmission of large-scale islanded wind power. [ABSTRACT FROM AUTHOR]

System operators are required to serve the load in the most cost-effective way while maintaining the integrity of the system and heeding reliability requirements. In the day-ahead market, operators acquire reserves in an attempt to guarantee N-1 reliability; yet, reserve deliverability is not guaranteed. Prior research has shown that the use of transmission switching, or topology control, may help improve reserve deliverability. In this paper, transmission switching is used as a corrective mechanism to help the system achieve N-1-1 reliability, where not only has the system lost a single element, but also it experiences the loss of a second major element after an adjustment period. In an attempt to preserve N-1-1 reliability, for this paper, a day-ahead unit commitment model that acquires supplementary reserves is solved. The day-ahead market solution is then tested for N-1-1 reliability using contingency analysis models with and without transmission switching. The methodology can be employed at the day-ahead time stage to ensure the system has acquired sufficient supplemental reserves. The results demonstrate that not only can corrective transmission switching be beneficial post-contingency without inhibiting the ability to return to N-1 reliability, but it can also help obtain an N-1-1 reliable solution. [ABSTRACT FROM AUTHOR]

This paper formulates a block-layer method for the reliability assessment of distribution systems. The characteristics of the method include: 1) identifying the impact of distribution component reliability on the system and load points using a block-layer structured assessment; 2) incorporating time-dependent failure parameters; and 3) taking account of the topological, seasonal, and meteorological features of the distribution systems under analysis. The proposed method first identifies the three critical parts of the distribution system: main supply, feeder, and secondary substation. It can also include reserve connections and distributed generation. Second, the method frames these parts into the layered structure, each corresponding to the zone of total load curtailment. To verify this reliability technique, this paper simulates distribution feeders assembled in a number of topologies and compares them with the state sampling technique. Data provided by the local utility company are processed to model the equipment and load for the base year. The results show that the proposed method can provide a wide range of partial and system indices. These values assist in the identification of parts of the distribution system and scenarios with low reliability and to determine possible remedial actions. [ABSTRACT FROM AUTHOR]

This paper investigates the fundamental coupling between loads and locational marginal prices (LMPs) in security-constrained economic dispatch (SCED). Theoretical analysis based on multi-parametric programming theory points out the unique one-to-one mapping between load and LMP vectors. Such one-to-one mapping is depicted by the concept of system pattern region (SPR) and identifying SPRs is the key to understanding the LMP-load coupling. Built upon the characteristics of SPRs, the SPR identification problem is modeled as a classification problem from a market participant's viewpoint, and a Support Vector Machine based data-driven approach is proposed. It is shown that even without the knowledge of system topology and parameters, the SPRs can be estimated by learning from historical load and price data. Visualization and illustration of the proposed data-driven approach are performed on a 3-bus system as well as the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

This paper applies a phasor-only state estimator (PSE) to a large power system consisting of two control regions, using synchrophasor data from 56 765/345/230 kV substations. Although the technique has been previously developed, this paper describes a topology processor to determine the redundant clusters of connected buses such that the PSE can be used in real time. This PSE allows corrections for phase biases, transformer taps, and current magnitude scaling. The ability to simultaneously solve the PSE for the two control regions is due to a PMU monitoring a tie-line between these two regions. The results show that with this method, the total vector errors of the measured voltage phasor data in these two control regions average to less than 0.5% under ambient conditions. The PSE also computes virtual phasor measurements on 70 buses that do not have PMUs, including large steam generator and wind-turbine generator substations. [ABSTRACT FROM AUTHOR]

For the popular second-order conic program (SOCP) formulation of AC optimal power flow (OPF) in a radial network, this paper first shows that it does not have the strong duality property in general. Then, through a series of restrictive reformulations, we derive a set of closed-form sufficient conditions on network parameters that ensure its strong duality. Numerical studies on IEEE 33-bus, 69-bus test networks and two real-world distribution systems confirm that non-negligible duality gaps do exist in this SOCP formulation, and also demonstrate the validity of the proposed sufficient conditions on closing the duality gap. Our results provide an analytical tool to ensure the strong duality of the SOCP power flow formulation and to support algorithm developments for its complex extensions. [ABSTRACT FROM AUTHOR]

Previous work on parameter error identification based on normalized Lagrange multipliers has shown that the errors in parameters of branches constituting single- or double-edge cutsets could not be detected or identified without incorporating phasor measurements. In order to address this deficiency, a computationally efficient algorithm has been developed to identify all such cutsets and documented in a recent paper. This paper builds on that work and formulates a strategic phasor measurement placement problem whose objective is to ensure detectability and identifiability of all network parameters in a given system. A practical solution is developed for this problem and simulation results for IEEE 14-, 30- and 57-bus test systems are provided to illustrate its implementation. [ABSTRACT FROM PUBLISHER]

This paper is concerned about the divergence of state estimation solution for multi-area power grids. Such cases typically occur due to a single anomaly in the measurement set or network model, yet will cause failure of the state estimator to provide the solution for the entire system. The objective of our study is to develop an approach that will allow detection, identification, and isolation of the anomaly during the state estimation solution so that a large percentage of the system states can still be estimated, while isolating the anomaly that is causing the divergence of the estimator. The proposed approach is described in detail and its effective utilization for a very large utility system is illustrated by simulations. [ABSTRACT FROM AUTHOR]

A cluster of dc microgrids consisting of multiple interconnected dc microgrids has great potential for improving the reliability and reducing the cost of power generation. In this paper, a distributed coordination control strategy is proposed to overcome a series of problems of centralized control. This control strategy which adopts a hierarchical structure is based on the droop control method, then a modified control formula which achieves multi-objective is introduced to the voltage control and power generation cost control. Besides, a finite-time consensus algorithm is applied to obtain the average value obtained in finite steps. Meanwhile, an estimated connected topology is proposed for better utilisation of the finite-time consensus algorithm and acceleration of the convergence speed. This proposed topology ensures all this control method is a fully distributed one, which does not require the global information previously and has high reliability. By using the MATLAB/Simulink simulation platform, this proposed control strategy is verified in one dc microgrid and a cluster of those containing 4 dc microgrids. The simulation results under different scenarios all indicate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal design algorithm for distributed secondary voltage control in islanded microgrids (MGs), including communication topology and controller gains. First, upon the consensus-based secondary voltage control, the sufficient condition for network connectivity of communication topology is revealed by the reachability matrix. A multi-objective optimization criterion is first proposed for the network design, taking the convergence performance, network-relevant time delays, and communication costs into consideration. After obtaining the Pareto frontier of this multi-objective model, an optimal network is selected to meet the practical requirements. Based on static output feedback, a small-signal dynamic model of an MG installed with a secondary voltage controller is established, where the distributed secondary voltage controller can be converted into an equivalent decentralized controller. Thereby, a linear quadratic regulator is formulated for the near-optimal design of controller parameters. Our approach customizes the optimal design framework of the topology and controller, which have been largely ignored in the existing literatures. Therefore, it promises to improve the performance of distributed secondary control. The effectiveness of the proposed methodology is verified by a simulation study. [ABSTRACT FROM AUTHOR]

This paper considers high voltage direct current (HVDC) links for the primary frequency control of interconnected time-delay power systems with electric vehicles (EVs). Novel distributed control of HVDC links is proposed to minimize the differences in the frequency deviations between the connected power areas. A power system with EVs, HVDC links and multiple time delays is first presented. Then, we propose a new robust distributed HVDC controllers design method to stabilize the closed-loop system with a guaranteed $H_{\infty }$ performance. The design method can be flexibly extended to design static output feedback controllers of various structures to cater for different power system topologies. The performance and usefulness of our proposed controller design method is validated by extensive simulations. [ABSTRACT FROM AUTHOR]

This paper studies the optimal transmission switching (OTS) problem for power systems, where certain lines are fixed (uncontrollable) and the remaining ones are controllable via on/off switches. The goal is to identify a topology of the power grid that minimizes the cost of the system operation while satisfying the physical and operational constraints. Most of the existing methods for the problem are based on first converting the OTS into a mixed-integer linear program (MILP) or mixed-integer quadratic program (MIQP), and then iteratively solving a series of its convex relaxations. The performance of these methods depends heavily on the strength of the MILP or MIQP formulations. In this paper, it is shown that finding the strongest variable upper and lower bounds to be used in an MILP or MIQP formulation of the OTS based on the big- $M$ or McCormick inequalities is NP-hard. Furthermore, it is proven that unless $P=NP$ , there is no constant-factor approximation algorithm for constructing these variable bounds. Despite the inherent difficulty of obtaining the strongest bounds in general, a simple bound strengthening method is presented to strengthen the convex relaxation of the problem when there exists a connected spanning subnetwork of the system with fixed lines. With the proposed bound strengthening method, remarkable improvements in the runtime of the mixed-integer solvers and the optimality gaps of the solutions are achieved for medium- and large-scale real-world systems. [ABSTRACT FROM AUTHOR]

Direct current (DC) network has been recognized as a promising technique especially for shipboard power systems (SPSs). Fast resilience control is required for an SPS to survive after faults. Towards this end, this paper proposes the indices of survivability and functionality based on which a two-phase resilience control method is derived. The on/off status of loads is determined in the first phase to maximize survivability, while the functionality of supplying loads are maximized in the second phase. Based on a comprehensive model of a DC-SPS, the two-phase method renders two mixed-integer non-convex problems. To make the problems tractable, we develop second-order-cone-based convex relaxations, thus converting the problems into mixed-integer convex problems. Though this approach does not necessarily guarantee feasible, hence global, solutions to the original nonconvex formulations, we provide additional mild assumptions, which ensures that the convex relaxations are exact when the line constraints are not binding. In the case of inexactness, we provide a simple heuristic approach to ensure feasible solutions. Numerical tests empirically confirm the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

This paper considers unbalanced multiphase distribution systems with generic topology and different load models, and extends the $Z$ -bus iterative load-flow algorithm based on a fixed-point interpretation of the AC load-flow equations. Explicit conditions for existence and uniqueness of load-flow solutions are presented. These conditions also guarantee convergence of the load-flow algorithm to the unique solution. The proposed methodology is applicable to generic systems featuring i) wye connections; ii) ungrounded delta connections; iii) a combination of wye-connected and delta-connected sources/loads; and iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. Further, a sufficient condition for the nonsingularity of the load-flow Jacobian is proposed. Finally, linear load-flow models are derived, and their approximation accuracy is analyzed. Theoretical results are corroborated through experiments on IEEE test feeders. [ABSTRACT FROM AUTHOR]

Direct-current microgrids (DC-MGs) can operate in either grid-connected or stand-alone mode. In particular, stand-alone DC-MG has many distinct applications. However, the optimal power flow problem (OPF) of a stand-alone DC-MG is inherently non-convex. In this paper, the OPF of DC-MG is investigated considering convex relaxation based on second-order cone programming. Mild assumptions are proposed to guarantee the exactness of relaxation, which only require uniform nodal voltage upper bounds and positive network loss. It is revealed that the exactness of second-order conic (SOC) relaxation of DC networks does not rely on topology or operating mode of DC networks, and an optimal solution must be unique if it exists. If line constraints are considered, the exactness of SOC relaxation may not hold. In this regard, two heuristic methods are proposed to give approximate solutions. Numerical experiments confirm the theoretic results. [ABSTRACT FROM AUTHOR]

This paper is concerned about the identification of network parameter errors, which are known to bias the state estimation solution. Previously proposed parameter error identification techniques implicitly assume the availability of a set of conventional measurements. In this paper, it is first shown that identification of certain parameter errors based on such conventional measurements, no matter how redundant they are, may not always be possible. The paper then describes the need for phasor measurements to overcome this limitation and presents an identification method that requires the use of such measurements. Examples are also included to describe the application of the proposed method to a number of typical topologies and measurement configurations. [ABSTRACT FROM AUTHOR]

This paper introduces a network topology identification (TI) method based on deep neural networks (DNNs) for online applications. The proposed TI DNN utilizes the set of measurements used for state estimation to predict the actual network topology and offers low computational times along with high accuracy under a wide variety of testing scenarios. The training process of the TI DNN is duly discussed, and several deep learning heuristics that may be useful for similar implementations are provided. Simulations on the IEEE 14-bus and IEEE 39-bus test systems are reported to demonstrate the effectiveness and the small computational cost of the proposed methodology. [ABSTRACT FROM AUTHOR]