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Voltage rise caused by high levels of distributed generation is manifesting as voltage regulation challenges for many electricity network service providers. In this environment it would be ideal to reduce supply voltage magnitudes, however, many network operators are hesitant to do so due to concerns related to consumer appliance performance at reduced supply voltage magnitudes. Voltage regulation requirements are defined by network standards and network service providers must ensure voltages remain within specified limits. Through an evaluation of domestic appliance performance when supplied at various voltage magnitudes, this paper examines the impact of varying voltage levels on residential appliances. Equipment energy demand, operation and actuation were monitored for each applied voltage magnitude. While no equipment failures were recorded, appliance behaviour varied significantly with applied voltage magnitude. Individual appliance conservation voltage reduction (CVR) factors have also been established. The results highlight the importance of good voltage regulation and provide substantiated appliance performance figures for future studies. The outcomes of this paper allow electricity network service providers to understand the implications of supply voltage magnitude on domestic appliance performance, whether it be understating of the impact of higher voltage magnitudes caused by distributed generation or implications of reducing voltage magnitudes to provide headroom for distributed generation integration. [ABSTRACT FROM AUTHOR]

Negative-sequence current is required to be intentionally injected to support the power grid or compensate the imbalanced load in asymmetrical faults utilizing STATCOM. However, the extreme compensation range of negative-sequence current injection becomes complicated when grid voltage becomes asymmetrical. This article presents a novel off-line strategy for negative-sequence current compensation under two typical kinds of asymmetrical grid faults — single-phase voltage drop and double-phase voltage drop, with the following two benefits simultaneously: maximizing negative current compensation capacity; avoiding iterations and reducing computation burdens. In this paper, the mechanism of DC voltage balancing among three phases in STATCOM is analyzed and a new identification method of negative-sequence current compensation range is explored out. To simplify the calculation, this paper takes the ratio of negative-sequence reactive (Iq-) and active (Id-) current as a variable (s). In this way, the relationship between the extreme compensation range, asymmetrical voltage sag depth of power grid h is drawn with MATLAB. Different from the previous iterative method, the off-line identification method is applied to avoid huge iterations. By fitting the curve, the precise ranges of negative-sequence current compensation under different asymmetrical grid faults are approximated as simple polynomials, thus significantly reducing the computation burdens. Simulation and experimental results verify the practicability of the proposed compensation method. [ABSTRACT FROM AUTHOR]

The neutral grounding method is one of the crucial technologies used to ensure the safe and stable operation of distribution networks. With the development of power electronics-based devices, the application of highly controllable inverters to grounding systems has become a new research direction. In this review paper, based on the summary and analysis for the research status, the flexible grounding system is systematically classified according to its control strategy and structure. And then, the following core technologies are summarized: faulted line selection, current component detection, high-resistance ground identification, ground parameter measurement, neutral point voltage control, and fault location. Subsequently, deficiencies of flexible grounding systems are summarized from the following four perspectives: reliability, accuracy, speed, and stability. Finally, some discussions and recommendations for future development and research direction are presented. Especially, the reliability-enhanced hybrid grounding system that combines active inverters and low resistance for high-resistance ground faults is recommended. This paper provides a systematic literature review of the crucial technologies for flexible grounding systems and can be used as a technical reference for future research. [ABSTRACT FROM AUTHOR]

With the advancements of the battery energy storage systems (BESSs), reduction of their manufacturing costs and government subsidies, the BESS uptake is likely to increase rapidly in power distribution networks. This paper investigates the effects of residential BESSs on low-voltage (LV) networks using the actual household load profiles equipped with BESS and solar-photovoltaic (PV) systems. The electricity consumption data collected via smart meters (2200 households with PV/BESS, 1950 households with PV only and 1000 households without a PV or a BESS) at different solar-PV penetration levels and network types are used to simulate real network operating scenarios. A real LV distribution network in Australia is analysed in DIgSILENT PowerFactory under different scenarios, such as, customers with and without a solar-PV/BESS, with a solar-PV but without a BESS, and without a solar-PV, by using both the power flow and quasi-dynamic simulation studies under balanced and the unbalanced network loading conditions. According to the study, customers experience large voltage excursions from solar-PV power exports, which could be resolved by the household BESS, provided that the BESS charging is coordinated with the solar-PV production. Moreover, quasi-dynamic simulation shows that the BESS could reduce the violation of the over-voltage limit during the solar peak hours (midday) by lowering the worst-case feeder voltage by 3%. Finally, extreme-event (high solar PV generation scenario) simulation shows that the implementation of the BESS controller to facilitate charging BESS during afternoon solar-PV export may reduce the negative grid impact and will assist to avoid network upgrades. [ABSTRACT FROM AUTHOR]

Ground faults are the main cause of electrical failure in transmission and distribution systems. In ungrounded distribution networks, it is difficult to detect where a first ground fault has happened as only capacitive currents are available. Also, it is important to trip only the faulty line in order to ensure the system's reliability. Directional residual overcurrent relays are the standard solution for these systems, but their difficult commissioning and high costs make it not trivial. This paper introduces a new selective and directional protection method to determine the faulty line in ungrounded medium voltage networks with three or more feeders. The method evaluates the residual currents in the feeders coupled to the same busbars in combination with a reference current created by the sum of a combination of residual currents of all feeders. Both simulation and laboratory results validate this new method, which is easy to start up, as it does not need previous configurations for its implementation, and it presents an economical solution to this problem. [ABSTRACT FROM AUTHOR]

The increasing penetration of distributed renewable energy sources drastically alters the dynamic characteristics of distribution networks (DNs). Therefore, several equivalent models have been recently proposed, to analyze more accurately the complex behavior of modern DNs. However, relatively simple models are still commonly used in practice for dynamic power system studies. In addition, dynamic equivalent models for DNs are sensitive to different operating conditions and there is lack of systematic understanding of their performance. Scope of this paper is to propose a methodology for identifying the applicability range in terms of accuracy and generalization capability of several conventional and newly developed equivalent models for the dynamic analysis of modern DNs. A set of metrics is used for the modelling accuracy assessment and a sensitivity analysis framework is introduced to fully quantify the generalization capabilities of DN equivalent models. Based on the above, guidelines and recommendations for the development of robust equivalent models for DN analysis are proposed. [ABSTRACT FROM AUTHOR]

The voltage rise problem due to the reverse power flow is one of the main obstacles to expanding the photovoltaic systems (PVSs) in distribution networks. In this paper, a decentralized control method for coordinated control of on-load tap changer (OLTC) transformers and PV inverters, is proposed for the voltage regulation of radial distribution networks. In this method, the allowable voltage range is divided into several zones, and appropriate corrective actions are adaptively taken according to each zone. To reduce the tension on the OLTC, first, the reactive power capability of the PV inverters is employed for the voltage regulation, and if it is insufficient, OLTC is used as the last solution. In this regard, the unused capacity of PV inverters is utilized for the reactive power compensation, considering the grid codes reactive power requirements. Furthermore, decentralized control based on a signaling method is used for coordination between OLTC and PVSs, which eliminates the need for communication links. Finally, the effectiveness of the proposed method is validated by the simulation results for the IEEE 33-bus distribution network, and the impact of different reactive power control methods on the number of OLTC operation is investigated. [ABSTRACT FROM AUTHOR]

The phase-to-ground admittance in distribution networks is asymmetric. This asymmetry is aggravated by the arc suppression coil, resulting in zero-sequence overvoltage. The magnitude of zero-sequence overvoltage can exceed the line-to-ground voltage, endangering the operation of electrical equipment. Moreover, after the occurrence of a single-line-to-ground fault, the change law of the three-phase voltage is affected by the zero-sequence overvoltage, leading to misjudgment of the fault phase. Accordingly, this paper proposes a fault phase selection method based on active current injection that can adapt to asymmetric distribution networks. The fault phase is selected by injecting current and calculating the equivalent power supply voltage of the faulty line without increasing the ground-fault current. The high sensitivity of the proposed fault phase selection method was verified for high impedance faults through software simulations and prototype experiments. Moreover, the zero-sequence overvoltage can be suppressed by a single-phase flexible arc suppression device during the normal operation of distribution networks. The ground-fault current can be quickly suppressed at different ground-fault locations and resistance values, ensuring the extinguishment of the ground-fault arc. [ABSTRACT FROM AUTHOR]

Utility-scale and small scale wind and solar power installations along with electric vehicle charging stations, and other active sources of energy are increasing at the medium and lower voltage levels in the distribution grid. This situation requires a better understanding of the impact of high penetration of weather-dependent renewable energy sources on the operating conditions of the distribution network at both medium and low voltage levels. Despite the need, a multi-voltage level distribution network model, based on real network data and weather-dependent renewable generation data, has not been presented for distribution grid studies. This paper presents a comprehensive multi-voltage level active distribution network model based on real network data along with load and generation time-series for about a year. The network topology is modelled based on geographical data for various rural, semi-urban, and urban locations. The distribution network is embodied with a large share of renewable generation sources, with generation time-series simulated from meteorological data. The network is also flexible to incorporate other assets such as electric vehicle charging stations, storage, etc. The presented active distribution network model can be used to study, optimize, and control the effects of weather-dependent generation and other network assets in the distribution grid. [ABSTRACT FROM AUTHOR]

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

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

Flexible DC distribution networks have been widely developed because of their advantages of high efficiency, low cost, and easy access to renewable energy. However, as distribution networks have more ends than the two-terminal transmission line, it is more challenging to protect them and locate their faults. Therefore, this paper proposes a modified T-source circuit breaker to protect against DC faults. Based on the proposed circuit breaker, an integral fault location method using double-terminal asynchronous data is proposed. The accuracy of the algorithm is not affected by the fault resistance. There are no differential terms in the algorithm, which greatly reduces the sensitivity to noise. The integral algorithm can remain steady when the voltage and current are zero in oscillation and attenuation periods. This constitutes the main contribution of this paper. Finally, it is verified by simulation and experiment that the proposed circuit breaker can isolate the power source within a short time in the typical DC distribution network. Under a noise of 30 dB for simulation, the location error of the proposed algorithm is <0.4% when the fault resistance is 0.5 Ω–500 Ω. [ABSTRACT FROM AUTHOR]

Due to the complex structures and fault conditions, accurate fault sensing of the underground distribution cables is a difficult task. The distribution automation system (DAS) and fault indicator system (FIS) are only applicable to the severe faults. In addition, the current DAS and FIS are all based on the centralized data processing system (CDS), increasing the communication pressure and data processing time of the main station. Considering the advantages of edge computing, this paper investigates using the grounding line currents to sense the fault in distribution cable networks. First, an edge computing based fault sensing system (ECS) is designed. The equivalent time-domain distribution cable models considering multi-conductor mutual couplings are then established in both normal and fault cases. The time-domain features of the cable grounding line currents prior to and after the fault are analyzed to create the fault detection criterion. Combining the network topology, locations of the measurement units (MUs), and direction factor of the ground line current, a space matrix based algorithm is created to achieve fault cable section location at edge. Finally, a distribution cable network is created by PSCAD/EMTDC. Various simulations are conducted to validate the effectiveness and robustness of the algorithm. [ABSTRACT FROM AUTHOR]

In DC distribution networks, the uncertainties of renewable energies and loads cause frequent voltage fluctuations. In this paper, a voltage regulation strategy based on the combined coordination of centralized optimal control (COC) and adaptive droop control (ADC) is proposed for droop-controlled DC distribution networks. In the COC strategy, the operation reference power of voltage source converters (VSCs) is optimized using the bus injection power measurements to improve the voltage profile and balance the power loading rates of different VSCs. The VSC capacity margin constraint is established to ensure that the capacity margin of each VSC is sufficient to cope with the unexpected fluctuation of loads and renewable energies. Then, an ADC strategy is adopted to handle voltage fluctuation between adjacent two COCs. In the ADC strategy, the operation reference power of the VSCs is further adjusted to recover the voltages. The voltage regulation is achieved based on the relationship among the VSC voltages and the minimum/maximum voltages of the whole network, which does not depend on the information of each nodal voltage and thus real-time network communication is avoided. The simulation results show that the proposed voltage regulation strategies can effectively improve the voltage profile under various uncertain environments. [ABSTRACT FROM AUTHOR]

The line parameters of power distribution systems stored in the dispatching center may have large errors due to the line aging and system operational dynamics. Such line parameter errors may directly affect the state estimation accuracy, and the advanced management functionalities rely on these parameters. This paper proposes an augmented state estimation method of erroneous distribution line parameters considering the presence of phasor measurement units (PMUs). The augmented state-space models under single and multiple measurement snapshots are established separately by combining the parameter state equation with the state-space model of the distribution network. The augmented state estimation based on the improved adaptive unscented Kalman filter (IAUKF) is developed. The proposed method can effectively perceive the process noise statistical parameter of the erroneous parameters during the estimation to accurately estimate line parameters. The proposed solution is validated through simulation experiments using the IEEE 33-bus system and the numerical results demonstrated its accurate parameter estimation performance.Also, the scalability of the proposed algorithm is demonstrated based on the simulation of the 118-bus system with distributed generators. [ABSTRACT FROM AUTHOR]

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

This paper applies the principles of distribution locational marginal pricing (DLMP) to unbalanced three-phase distribution networks. We first propose a linear model for AC optimal power flow derived through a series of approximation and reformulation techniques. Then a scenario-generation algorithm is proposed to properly model the uncertain parameters in the linear model. Through a proposed No U-Turn sampler (NUTS) based algorithm, probability density functions (PDFs) of DLMPs are calculated. These PDFs provide statistical information about the locational and temporal price risks. By means of applications to two IEEE unbalanced test networks, the numerical results show promising performance for the proposed linear model and the NUTS-based algorithm in creating PDFs of DLMPs. DLMP price densities will be increasingly useful as distribution system operators seek flexible, low risk solutions from embedded generators and aggregators of distributed energy resources. [ABSTRACT FROM AUTHOR]

Accurate estimates of network parameters are essential for modeling, monitoring, and control in power distribution systems. In this paper, we develop a physics-informed graphical learning algorithm to estimate network parameters of three-phase power distribution systems. Our proposed algorithm uses only readily available smart meter data to estimate the three-phase series resistance and reactance of the primary distribution line segments. We first develop a parametric physics-based model to replace the black-box deep neural networks in the conventional graphical neural network (GNN). Then we derive the gradient of the loss function with respect to the network parameters and use stochastic gradient descent (SGD) to estimate the physical parameters. Prior knowledge of network parameters is also considered to further improve the accuracy of estimation. Comprehensive numerical study results show that our proposed algorithm yields high accuracy and outperforms existing methods. [ABSTRACT FROM AUTHOR]

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

The nonlinear and nonconvex nature of ac power flow challenges the analysis and optimization of unbalanced distribution networks. To tackle this issue, this paper proposes an online feedback-based linearized power flow model for unbalanced distribution networks with both wye-connected and delta-connected loads. The online feedback-based linearized model is grounded on the first-order Taylor expansion of the branch flow model (BFM), and updates the model parameters via online feedback by leveraging the instantaneous measurements of voltages and load consumption. Exploiting the connection structure of unbalanced radial distribution networks, we also provide a unified matrix-vector compact form of the model. The numerical tests on the IEEE 123-bus test system validate its accuracy and superiority compared with other offline BFM methods. Additionally, we apply the proposed model to the optimal power flow for voltage regulation, which further demonstrates its effectiveness. [ABSTRACT FROM AUTHOR]

With the increasing number of controllable devices in the grid, devices owned by different entities are supposed to cooperatively support the grid operation. To balance the various interests of the customers and the utility, this paper proposes a two-level scheduling algorithm to address voltage regulation by coordinating the customer-owned battery energy storage system (BESS) and utility-owned load tap changers (LTCs) in power distribution systems. The objective is to find the optimal operation scheduling for both BESSs and LTCs that simultaneously maximize the economic payback and satisfy system operation rules. For BESSs, a local optimization problem is formulated in a chance-constrained manner in major consideration of the economic performance. For the utility interest, a Markov decision process (MDP) and a computationally efficient reinforcement learning (RL) algorithm are utilized to solve the optimal tap setting problem. To coordinate BESSs and LTCs, a global voltage adjustment is applied. The effectiveness of the proposed algorithm is validated via simulations on the IEEE 13-node and 34-node distribution test feeders. [ABSTRACT FROM AUTHOR]

This paper proposes a novel reactive power-based control strategy for single-phase PV inverters (PVIs) to simultaneously improve voltage unbalance (VU) and voltage regulation (VR) in low-voltage distribution networks. The proposed strategy relies on communication links between neighboring PVIs to exchange limited data. In this strategy, each PVI finds communication paths between itself and the closest neighboring ones connected to other phases. Then, using the obtained paths and the maximum and the minimum voltage magnitude of the grid, PVIs improve both VU and VR at the same time. The performance of the proposed control strategy is evaluated by various simulation studies using the IEEE European low-voltage test feeder and considering different operational conditions. In addition, the impacts of moving clouds and a failure in the communication links have been assessed. The simulation results exhibit that using the proposed control strategy, the voltage magnitude of all the nodes will remain within the allowed limits and at the same time, the phase voltage unbalance factor will be also significantly improved. [ABSTRACT FROM AUTHOR]

This paper elucidates a new real time energy management framework for radial active unbalance distribution networks (UDNs) by integrating load shedding and conservation voltage reduction (CVR) techniques. In contrast with the shortsighted real time optimization strategies, the proposed technique accounts offline beneficial aspects in real time optimization platform as time coupled stochastic expressions. Those are further simplified to a mixed integer non-convex programming (MINCP) using merger of Queueing theory and Lyapunov optimization process. To solve the complex MINCP portfolio, a consecutive mixed integer linear programming (c-MILP) based solution method is proposed after adopting necessary linear approximations. After demonstrating on modified IEEE 123 bus test network, it is showed that the proposed real time strategy can provide most energy efficient, secure and reliable operation to the UDNs and can accommodate offline advantageous attributes successfully along with the real time load shedding and CVR constraints. Validating the power flow solutions at OpenDSS platform, it is proved that the proposed c-MILP approach possess fast convergence and provide near optimal power flow solutions. Further investigations certify that presence of residential consumers are more beneficial for the networks as they are more sensitive to voltage. [ABSTRACT FROM AUTHOR]

Voltage-to-power sensitivities play a key role in the control and operation of distribution networks. To estimate these sensitivities without network information, data-driven estimation methods have been studied. However, conventional methods do not consider mutual dependency (MD) of the sensitivities and thus the estimation can be inaccurate. Thus, this paper proposes a new data-driven estimation method of the sensitivities, which considers MD of the sensitivities in medium voltage distribution networks. In the proposed method, via MD analysis, the sensitivities are estimated by solving nonlinear least square problems and thus the accurate estimation can be achieved. The effectiveness of the proposed method is verified using the real-time platform. [ABSTRACT FROM AUTHOR]

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

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]

Point cloud based retrieval for place recognition is still a challenging problem since the drastic appearance changes of scenes due to seasonal or artificial changes in the environments. Existing deep learning based global descriptors for the retrieval task usually consume a large amount of computational resources ($e.g$., memory), which may not be suitable for the cases of limited hardware resources. In this paper, we develop an efficient point cloud learning network (EPC-Net) to generate global descriptors of point clouds for place recognition. While obtaining good performance, it can greatly reduce computational memory and inference time. First, we propose a lightweight but effective neural network module, called ProxyConv, to aggregate the local geometric features of point clouds. We leverage the adjacency matrix and proxy points to simplify the original edge convolution for lower memory consumption. Then, we design a lightweight grouped VLAD network to form global descriptors for retrieval. Compared with the original VLAD network, we propose a grouped fully connected layer to decompose the high-dimensional vectors into a group of low-dimensional vectors, which can reduce the number of parameters of the network and maintain the discrimination of the feature vector. Finally, we further develop a simple version of EPC-Net, called EPC-Net-L, which consists of two ProxyConv modules and one max pooling layer to aggregate global descriptors. By distilling the knowledge from EPC-Net, EPC-Net-L can obtain discriminative global descriptors for retrieval. Extensive experiments on the Oxford dataset and three in-house datasets demonstrate that our method achieves good results with lower parameters, FLOPs, GPU memory, and shorter inference time. Our code is available at https://github.com/fpthink/EPC-Net. [ABSTRACT FROM AUTHOR]

Accurate faulty phase detection under single-line-to-ground (SLG) fault is the basis of the emerging voltage-based fault arc suppression technology. Most conventional faulty phase recognition criteria assume the distributed line-to-ground parameters are symmetrical, therefore suffering invalidity in actual distribution networks especially under high-resistance ground-fault conditions. This paper firstly analyzes the magnitude and phase angle variation models of the phase-to-ground voltages before and after the SLG fault. Considering the asymmetrical distributed parameters and the line impedance, the specific phase-to-ground voltage variation rules corresponding to SLG fault on each phase are then discussed. Based on the voltage variation rules, a robust and practical method for faulty phase identification is proposed, which does not need the distributed parameters. Finally, the correctness of the variation rules and the availability of the proposed method is verified by simulation. Comparative study shows the proposed method has better accuracy and applicability with the conventional methods when the asymmetry and ground-fault resistance are high. [ABSTRACT FROM AUTHOR]

The work presented in this paper describes a multi-issue negotiation protocol between active consumers and a management platform in order to establish load coordination in a highly congested network. The multi-issue negotiation protocol considers simultaneously the consumption interval, the price, and the size of the energy packages, which is the main contribution of this work. Regarding the implementation methodology, the proposed algorithms have been implemented using MATLAB classes that allow emulating the behaviour of a multi-agent system in which each vehicle is an agent that interacts with the platform, which is another agent. In the present work, and without loss of generality, the algorithm is applied to coordinate the charging of electric vehicles (EVs) in a distribution network in which building loads represent critical loads. The algorithm is tested in a realistic environment, and its stability and performance are evaluated. Furthermore, the description of the algorithm is provided in a generic form, and it could be applied to any other scenario. [ABSTRACT FROM AUTHOR]

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

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

This paper presents a distribution system operator (DSO) framework for wholesale and retail market participation of distributed energy resources (DERs) aggregators. The DSO coordinates aggregators’ energy and regulation offers as well as end-users’ energy consumption through the unbalanced retail market and submits balanced energy and regulation offers to the wholesale market on behalf of all the aggregators and end-users within its territory. Various kinds of DER aggregators including demand response aggregators (DRAGs), energy storage aggregators (ESAGs), electric vehicle (EV) charging stations (EVCSs), dispatchable distributed generation aggregators (DDGAGs), and renewable energy aggregators (REAGs) are modeled. To handle unbalanced distribution grids with single-phase aggregators, a linearized unbalanced power flow is tailored to model operating constraints of the distribution grid with various aggregators. A market settlement approach is proposed for the DSO, which coordinates with wholesale market clearing process and ensures the DSO’s non-profit characteristic. It is proved that at the wholesale-DSO coupling substation, the total payment received/compensated by the DSO under the wholesale price is identical to that under three single-phase retail prices for each phase at the substation. Case studies are performed on the modified IEEE 33-node and 240-node distribution test systems to investigate the market outcomes of the proposed DSO. [ABSTRACT FROM AUTHOR]

The output of renewable generation depends on the real-time weather conditions and changes rapidly; so the economic operating point of the power system varies over time. This paper aims to find the explicit mapping from variable renewable power to optimal power flow solutions. To this end, we propose a parametric distribution optimal power flow (P-DOPF) method, which gives the optimal dispatch strategy and power flow status as analytical functions of the renewable output. With the established distribution optimal power flow problem based on the relaxed Distflow model, the first step is to perform a global polyhedral approximation on the second-order cone constraints to develop a linearized formulation. The second step is to obtain the P-DOPF model by treating renewable power output as parameters; then, the P-DOPF problem gives rise to a multi-parametric linear program (mp-LP). Third, we prove that the optimal solution and optimal value of the P-DOPF are piecewise linear functions of the parameters and we design an adaptive-sampling algorithm to construct the optimal value and optimal solution functions, as well as the partition of the parameter set, subject to a given error tolerance; this algorithm is not influenced by model degeneracy, a common difficulty of existing mp-LP algorithms. The P-DOPF framework provides an explicit real-time control policy of generators in response to the renewable output. Case studies on the IEEE 33 and 69-bus systems verify the effectiveness and performance of the proposed method; by comparison, the proposed method outperforms the established affine policy method in computational efficiency and optimality by 24.5% and 4.62%, respectively. [ABSTRACT FROM AUTHOR]

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multi-period bilevel optimization problem to find the ODR strategy. The objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy. [ABSTRACT FROM AUTHOR]

This paper presents a framework to determine the feasible dispatch limits of solar photovoltaic (PV) generation in the unbalanced distribution network considering the interconnection of electric vehicles (EVs) and associated uncertainties. The proposed framework determines the lower and upper dispatch limits of PV generation considering the worst-case realization of a) the minimum and maximum storage capacity of EVs, b) the minimum and maximum power dispatch of EVs, c) the lower and upper bounds for the arrival and departure times, and d) the available energy at arrival and departure times. The unbalanced operation of the distribution network as well as the uncertainty in the maximum PV generation and demand forecasts were considered. The problem formulation and solution approach are validated using the modified IEEE 34-bus and IEEE 123-bus distribution systems. The impacts of the budget of uncertainty and the vehicle-to-grid operation mode of EV clusters were addressed in the case studies. It is shown that integrating EVs with charging capability will increase the lower dispatch limit or increase the upper dispatch limit of the PV generation. Moreover, the increase in the budget of uncertainty will reduce the difference between the upper and lower dispatch limits by increasing the lower dispatch or decreasing the upper dispatch limit of the PV generation. Finally, it is shown that the vehicle-to-grid capability will reduce the total lower dispatch limit or increase the total upper dispatch limit of the PV generation in the operation horizon. [ABSTRACT FROM AUTHOR]

Reliability is an essential factor in distribution networkt expansion planning. However, standard distribution reliability assessment techniques rely on quantifying the impact of a pre-specified set of events on service continuity through the simulation of component outages, one at a time. Due to such a simulation-based nature, the incorporation of reliability into distribution network expansion planning has customarily required the application of heuristic and metaheuristic approaches. Recently, alternative mixed-integer linear programming (MILP) models have been proposed for distribution network expansion planning considering reliability. Nonetheless, such models suffer from either low computational efficiency or over-simplification. To overcome these shortcomings, this paper proposes an enhanced MILP model for multistage reliability-constrained distribution network expansion planning. Leveraging an efficient, yet accurate reliability evaluation model, proposing a customized technique for effectively imposing radial operation, as well as utilizing pragmatic measures to model reliability-related costs are the salient features of this work. In this respect, practical reliability-related costs are considered based on reliability incentive schemes and the revenue lost due to undelivered energy during customer outages. The proposed planning approach is tested on four networks with 24, 54, 86, and 138 nodes to illustrate its efficiency and applicability. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden. A distribution network with two 20 kV feeders and 8 DG units was used to validate the control performance of the proposed coordinated voltage control scheme. [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]

Faults with line breaks occur more and more frequently and are difficult to detect by relay protection device in small-current grounding distribution networks. However, faults with line breaks are more likely to cause security accidents such as fires, overvoltages and electric shocks. Considering the low cost and high reliability of collecting data on the low-voltage (LV) side in distribution networks, this paper proposes a method for distinguishing between faults with line breaks and short-circuit faults on the medium-voltage (MV) side. Voltage amplitude and phase on the LV side of distribution transformer (DT) are analyzed through symmetrical component method. The amplitudes are used to identify two-phase faults with line breaks (TPFs-LBs) and two-phase short-circuit faults (TPFs-SCs); while the phases are selected to distinguish single-line-to-ground faults with line breaks (SLGFs-LBs) from single-line-to-ground faults (SLGFs). The effects of network parameters, operation conditions and external factors on the proposed method have been discussed. Simulation results verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Phase balancing of American-type three-phase distribution circuits is one of the classical problems faced by distribution system operators and planners. In this paper, a mixed-integer non-linear programming problem is formulated to minimize the number of phase connection changes in existing circuits to reach the desired phase balancing. The proposed algorithm uses geographical information system models of distribution circuits to build a reduced model and realistic load profiles offered by smart meters, or measurements at the distribution transformers to characterize the demand. The formulation is validated in highly unbalanced distribution circuits with thousands of single-phase customers. The results show that it is possible to rebalance large-scale circuits by moving a few single-phase laterals and loads. In addition, the application of the proposed method, based on loading conditions at different hours of the day, pointed out the same places to make the changes. [ABSTRACT FROM AUTHOR]

This paper studies the distribution network impacts of frequency containment services derived from domestic-scale devices. Risk metrics considering the likelihood and severity of violations are proposed, given uncertainty in the location of these devices. A novel linearization approach is proposed to enable detailed simulations of large-scale networks, capturing MV–LV coupling in European-style networks of over 100 000 nodes. The approach combines a novel factorization of the power flow Jacobian matrix and an efficient linearization update step. The first of these innovations improves the scalability and practicality of the linearization, reducing the memory and computational requirements by as much as twenty times, whilst the latter reduces the median linearization error by at least 50% in all networks studied. It is demonstrated that rapid voltage change (RVC) and overvoltage constraints could limit the uptake of these devices to just a fraction of one percent of customers if the response is not managed. Sensitivity analysis demonstrates that both the likelihood and severity of constraint violations increases rapidly with the size of the devices used for frequency response. [ABSTRACT FROM AUTHOR]

In order to effectively improve the role of battery energy storage system in power system, this paper studies the optimal scheduling strategy of BESS in power grid. Firstly, taking the minimum power exchange cost between power grid and the penalty cost of node voltage deviation as the objective function, an optimal scheduling model of BESS in distribution grid based on mixed integer programming is proposed. Secondly, when BESS tracks the scheduling instruction, the life attenuation of each BESS is inconsistent due to the difference of operation conditions. A scheduling method considering the state of health (SOH) of BESS is proposed. Finally, the SOC and total charge and discharge capacity of each BESS are analyzed, and the change characteristics of SOC under different SOH conditions (0.8, 0.85, 0.9, 0.95, 1.0) are verified effectively, which indirectly verifies that this scheduling method can effectively reduce the scheduling loss. [ABSTRACT FROM AUTHOR]

To enhance the operating security and stability of the cross-linked polyethylene power cable based urban distribution network due to conventional cable joint (CCJ) faults, this paper presents a novel superconducting fault current limitation scheme by using a superconducting cable joint (SCJ). The basic principle, circuit modeling, conceptual design and distribution network integrated with the SCJ are presented in detail. The comparative study without and with the proposed SCJ scheme and comprehensive evaluation are carried out. The simulation results obtained under symmetrical and asymmetrical CCJ faults show that the harmful large fault grid currents can be limited effectively and the fault grid voltage can be well improved. Thus the high temperature electric arc in the fault location caused by CCJ faults can be safely controlled. And large area power failure in actual power system can be avoided. [ABSTRACT FROM AUTHOR]

This paper presents a simple yet effective method for locating faults in radial distribution networks where impedance-based methods are known to have limitations, especially in the presence of inverter-based power sources (IBPS). The proposed approach utilizes the Discrete Wavelet Transform (DWT) to capture the first arrival times of the fault-generated traveling waves. It is assumed that a digital fault recorder (DFR) exists at the terminal node of every lateral, as well as the beginning and end of the main feeder. The detailed derivation of the fault location method is presented, and illustrative fault scenarios are simulated to experimentally verify the proposed algorithm's performance under very diverse conditions. It is shown that the proposed approach performs successfully irrespective of the unknown fault impedance, inception angle, and type. [ABSTRACT FROM AUTHOR]

A distributed zero-sequence-current (ZSC) carrier signal injection via current transformer (CT) is proposed for underground cable single-phase-to-ground fault location in neutral isolated medium voltage (MV) distribution networks. High-frequency ZSC carrier signal is directly injected to a high-voltage underground cable of an energized distribution network via CT. The injected carrier signal travels along the cable to the receiving center in the substation, and is processed for quick fault line selection and fault location. No external power supplies or signal generators are needed due to the self-contained nature of the injector. The device can be constructed as a sleeve to be mounted around the underground power cable. This permits economical retrofitting to existing installations of power line communication (PLC) devices. In this paper, the operational principle and the application considerations for such an injection device and fault location tricks are explained, followed by the theory behind the proposed technique. Finally, MATLAB based numerical simulations are performed and a low-voltage prototype is tested to verify the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper proposes a new and comprehensive approach for optimal sizing and placement of a wind farm (WF) in a radial distribution network (RDN) while considering several factors associated with its reliability, operation, economics and environment impact. The consideration of the reliability aspect is essential to correctly assess the impacts of forced outages of wind turbines in the field. In this context, a sequential Monte Carlo simulation-based technique has been formulated to evaluate the performance of the WF with varying capacities at different locations in the RDN. Additionally, the capability of the WF to perform Volt-Var and Volt-Watt control has been capitalized on to provide voltage support to the grid in compliance with international standards (IEEE 1547-2018). Finally, a combination of Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution has been used to assess and determine the optimal size and location of the WF, based on a selected set of performance criteria, namely cumulative violations of the steady-state voltage range, cumulative losses in RDN, cumulative violations of the line thermal rating, levelized cost of energy, and reduction in carbon emission. The proposed approach has been validated considering different modes of voltage control on the standard 33-bus RDN system. [ABSTRACT FROM AUTHOR]

In recent years, with the expansion of urban scale and construction of energy infrastructure, more cities construct underground cables to replace overhead lines from the perspective of environment and safety. Thus, more distributed capacitive current flows back to distribution networks under fault conditions and affects the accuracy of fault locating. This paper proposes an iterative modification method of capacitive current to decrease the uncertainty of complex equations with micro synchronous phasor measurement unit (μPMU) data. Firstly, the initial fault location is calculated by using phasor measurement data without the shunt effect of grounding capacitance. Then, the capacitive current is estimated by the initial fault location distance, and the location result is modified by an iterative strategy. Finally, after iteration modification, a more accurate real number solution for complex equations can be obtained for complicated distribution networks with the uncertain capacitive current. The simulation results of a real underground distribution network and a modified IEEE 33 node test feeder in MATLAB/Simulink show that the proposed algorithm has higher accuracy than the traditional methods which do not have the iterative modification method of capacitive current under different fault locations, fault resistances, fault types and the neutral point grounding modes. [ABSTRACT FROM AUTHOR]

Topology identification and parameter estimation form the basis for the operation and control of the distribution network with little or no observability. This paper proposes a method to estimate the admittance matrix for open-loop distribution networks based only on active/reactive power injection and voltage magnitude data. We derive the linear relationship between the admittance matrix and the measurements based on decoupled linear power flow (DLPF) equations. A total least squares regression method is proposed based on analysis of the characteristics of the open-loop grid admittance matrix. Case studies on the IEEE 33-bus system demonstrate the proposed method's effectiveness, accuracy, and efficiency. [ABSTRACT FROM AUTHOR]

With the large-scale integration of distributed generators (DGs), the coupling relations between transmission network (TN) and distribution networks (DNs) are getting closer. Coordinating the black-start processes of TN and DNs is beneficial to improving restoration efficiency. Therefore, a distributed black-start optimization method for global transmission and distribution (T&D) network is proposed in this paper. Firstly, a black-start optimization model of global T&D network is established to minimize the outage costs. Then, it is decomposed into the TN black-start optimization sub-problem and several DN black-start optimization sub-problems based on the analytical target cascading (ATC). The mixed integer quadratic programming (MIQP) is used for sub-problem modeling. The models take into account the restoration operations of different grid components at each black-start time step. The transmission control center (TCC) and distribution control centers (DCCs) only need to exchange partial information including the boundary power at each time step for distributed coordination, to obtain the coordinated black-start scheme for T&D network. Finally, the effectiveness of the proposed model and method is validated using a global T&D network case. [ABSTRACT FROM AUTHOR]

To improve the accuracy of faulty feeder selection based on zero sequence current mutation, distribution networks with inverter-interfaced distributed generators (IIDGs) are analyzed in detail. It is found that the IIDGs cannot be completely equivalent to a positive sequence current source due to their boosting increments. Thereby, a more accurate IIDG current estimation model based on the Gauss-Seidel method that considers the control strategy at the moment of fault is established. Moreover, a real-time estimation algorithm is introduced for faulty feeder detection to adjust the compensation degree of the Petersen coil. On this basis, this paper proposes a novel faulty feeder detection approach using the zero-sequence current space relative distance between the increments of each feeder and an estimation of the faulty path generated by Kalman filtering (KAF). The feasibility of the proposed approach is demonstrated in both a PSCAD/EMTDC simulation and a MATLAB experimental laboratory. The test results indicate that the proposed approach can achieve a high speed when employed for different fault conditions. [ABSTRACT FROM AUTHOR]