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Metasurface holography has aroused immense interest in producing holographic images with high quality, higher-order diffraction-free, and large viewing angles by using a planar artificial sheet consisting of subwavelength nanostructures. Despite remarkable progress, dynamically tunable metasurface holography in the visible band has rarely been reported due to limited available tuning methods. In this work, we propose and numerically demonstrate a thermally tunable vanadium dioxide (VO2) nanofin based binary-phase metasurface, which generates holographic information in the visible varying with temperature. The insulator-to-metal phase transition in VO2 nanofins allows two independent binary-phase holograms generated by machine learning to be encoded in the respective phases of VO2 and switched under thermal regulation. By elaborately designing the dimensions and compensated phase of VO2 nanofins, high-quality images are reconstructed at corresponding temperatures under appropriate chiral illumination. In contrast, much poorer images are produced under inappropriate chiral illumination. We further demonstrate the advantage of applying the VO2 phase-compensated metasurface in high-security digital encryption, where two desired character combinations are read out with appropriate excitations and temperatures, whereas one identical fraudulent message is received with inappropriate excitations. Our design approach offers a new and efficient method to realize tunable metasurfaces, which is promisingly adopted in dynamic display, information encryption, optical anti-counterfeiting, etc.

To reduce greenhouse emission and achieve sustainability in the electric power industry, improved efficiency and energy conservation are key to finding a sound solution. Energy conservation through voltage reduction (CVR) is one such program. To implement effective CVR programs, load models are of utmost importance in determining proper feeders and methods to implement the CVR programs. Exponential and polynomial load models stand out as the most widely adopted models. The polynomial load model, often referred to as the ZIP (constant impedance, current and power) model, is especially notable for its ability to represent the relationship between the applied voltage and power consumption. This paper sheds light on the limitations of commonly used ZIP load model estimation methods and highlights the significance of using ap-propriate measurement samples and understanding the true nature of the load. Two distinct ZIP load models, i.e., the regular ZIP (RegZIP) and the Non-traditional ZIP (NTZIP) models, have been used for ZIP parameter estimation. The RegZIP load model consumes equal or more power when voltage increases, while the NTZIP model consumes equal or less power when voltage increases. It is emphasized that the RegZIP is an existing load model and the NTZIP is an artificial load model this research created for comparison purposes. The intention of this paper is not to propose any new load model, but to investigate the implications of choosing the wrong model and the impacts of measurement errors of voltage and power data. The research has shown that the two different models can fit the same measurement data equally well for some measured data. The results have demonstrated that simply using certain methods such as the optimization method for estimating load model parameters using unfiltered real time measurements may yield misleading and unreliable results. Wrong load models will inevitably lead to wrong CVR assessment. Identifying the correct measurement samples, obtained during natural or staged events causing substantial voltage variations, is critically important in calculating load parameters and ensure the soundness of the obtained results. The accurate load parameters will be important in the assessment of CVR program effectiveness and will ensure that power system analysis applications that utilize the load models will provide reliable results. [ABSTRACT FROM AUTHOR]

Metasurface holography has aroused immense interest in producing holographic images with high quality, higher-order diffraction-free, and large viewing angles by using a planar artificial sheet consisting of subwavelength nanostructures. Despite remarkable progress, dynamically tunable metasurface holography in the visible band has rarely been reported due to limited available tuning methods. In this work, we propose and numerically demonstrate a thermally tunable vanadium dioxide (VO2) nanofin based binary-phase metasurface, which generates holographic information in the visible varying with temperature. The insulator-to-metal phase transition in VO2 nanofins allows two independent binary-phase holograms generated by machine learning to be encoded in the respective phases of VO2 and switched under thermal regulation. By elaborately designing the dimensions and compensated phase of VO2 nanofins, high-quality images are reconstructed at corresponding temperatures under appropriate chiral illumination. In contrast, much poorer images are produced under inappropriate chiral illumination. We further demonstrate the advantage of applying the VO2 phase-compensated metasurface in high-security digital encryption, where two desired character combinations are read out with appropriate excitations and temperatures, whereas one identical fraudulent message is received with inappropriate excitations. Our design approach offers a new and efficient method to realize tunable metasurfaces, which is promisingly adopted in dynamic display, information encryption, optical anti-counterfeiting, etc. [ABSTRACT FROM AUTHOR]

ZIP load modeling has been used in various power system applications. The aggregate load modeling is common practice in utility companies. However, little research has been done on the theoretical formulation of the aggregate load and on various factors that affect accurate estimation of the parameters. This paper proposes new methods to systematically formulate the aggregate ZIP load model using the single ZIP load model and comprehensively examines the factors that may affect aggregate ZIP load estimation. Moreover, novel analysis of reactive power ZIP parameter calculation considering different compensating device modeling is presented. ZIP parameter estimation methods including least squares method, optimization method, and neural network method have been used in this paper to estimate ZIP parameters. The proposed new method was illustrated using the IEEE 13-bus and 34-bus systems built in OpenDSS. In addition, the ZIP parameter estimation is also performed using field data, and the conservation through voltage reduction (CVR) factor is further computed based on the estimated ZIP load model. The results provide guidance on calculation and interpretation of CVR estimates. Note that this paper was first presented at PAC world conference 2021 which provides no published conference proceedings. [ABSTRACT FROM AUTHOR]

Accurate fault location in distribution systems greatly shortens maintenance time and improves reliability. This paper presents novel methods to pinpoint fault location and identify possible bad measurements for enhanced accuracy. It is assumed that network parameters and topology of the distribution network are available. The methods are applicable to a single fault as well as simultaneous faults and are applicable to both balanced and unbalanced networks. The methods utilize synchronized voltage and current phasor measurements to locate the fault. The methods are validated by simulation studies using the modified IEEE 34-Node Test System. Case studies have demonstrated that the methods are suitable for distribution systems with high penetration of distributed generations. [ABSTRACT FROM AUTHOR]

This paper presents a new composite approach based on wavelet-transform and ANN for islanding detection of distributed generation (DG). The proposed method first uses wavelet-transform to detect the occurrence of events, and then uses artificial neural network (ANN) to classify islanding and non-islanding events. Total harmonic distortion and voltage unbalance are extracted as feature inputs for ANN classifier. The performance of the proposed method is tested by simulations for two typical distribution networks based on MATLAB/Simulink. The results show that the developed method can effectively detect islanding with low misclassification. The method has the advantages of small non-detection zone and robustness against noises. [ABSTRACT FROM AUTHOR]

This paper presents a new method for optimizing the operation of a microgrid, which minimizes the operating cost or maximizes solar generation of the microgrid. The microgrid consists of loads, storage devices, and distributed generations. The generation cost, capacity, ramp up and down rate, and minimum up and down time for each generator are considered. Characteristics of storage devices including charging and discharging rate, capacity, and charging and discharging efficiency are modelled. The microgrid can sell or buy electricity from the area electrical power system. A novel method for modeling system reserve requirement with storage devices is presented. The optimal schedule of generation and storage resources in the microgrid including on or off status of generators and optimal dispatch, and charging and discharging status and rate of storage devices is determined. The paper provides versatile strategies through different optimization formulations such as optimal storage sizing for operators to reduce solar generation curtailment due to duck curve phenomena. In this research, without losing generality, the simulation horizon is 24 hours day ahead, and simulation resolution is one hour. The optimization problem is formulated as a mixed integer linear programming problem. Case study results are reported. [ABSTRACT FROM AUTHOR]

Partial discharge location in gas insulated switchgears is important for timely identifying incipient problem and taking remedial actions to prevent later catastrophic breakdowns. This paper presents a new system including sensing terminals and hand-held intelligent terminals to locate partial discharge. Sensing terminals, housing the sensors, are attached to outside enclosure walls of the switchgear to collect acoustic signals, which are transmitted wirelessly to the hand-held terminals. The acoustic vibration caused by the discharge will propagate from the source, resulting in the highest intensity at the sensor closest to the discharge. By examining the signal signatures of the distributed sensors, the location of the partial discharge can be derived. The system is applied in both staged simulation environment and actual factory high voltage tests. The results have demonstrated that the system developed is highly effective in locating partial discharge in gas insulated switchgears and is suitable for practical applications. [ABSTRACT FROM AUTHOR]

This paper presents a new method for locating faults on radial distribution systems utilizing local voltage and current measurements. The method considers feeder shunt capacitances, is applicable to any type of faults, is suitable for unbalanced networks and does not require fault type information. The method is also independent of source impedance. Analytical analysis is utilized to obtain a generic performance equation for any type of faults, which reduces or eliminates iterative steps to reach the fault location. A process to trim down multiple estimates due to laterals is discussed. Evaluation studies based on simulated data have demonstrated the effectiveness of the proposed solution. [ABSTRACT FROM AUTHOR]

This paper presents the tools and exercises used during the Kentucky Smart Grid Roadmap Initiative in a collaborative electric grid planning process involving state regulators, public utilities, academic institutions, and private interest groups. The mandate of the initiative was to assess the existing condition of smart grid deployments in Kentucky, to enhance understanding of smart grid concepts by stakeholders, and to develop a roadmap for the deployment of smart grid technologies by the jurisdictional utilities of Kentucky. Through involvement of many important stakeholder groups, the resultant Smart Grid Deployment Roadmap proposes an aggressive yet achievable strategy and timetable designed to promote enhanced availability, security, efficiency, reliability, affordability, sustainability and safety of the electricity supply throughout the state while maintaining Kentucky's nationally competitive electricity rates. The models and methods developed for this exercise can be utilized as a systematic process for the planning of coordinated smart grid deployments. [ABSTRACT FROM AUTHOR]

Transmission lines are essential components of electric power grids. Diverse power system applications and simulation based studies require transmission line parameters including series resistance, reactance, and shunt susceptance, and accurate parameters are pivotal in ensuring the accuracy of analyses and reliable system operation. Commercial software packages for performing power system studies usually have their own databases that store the power system model including line parameters. When there is a physical system model change, the corresponding component in the database of the software packages will need to be modified. Manually updating line parameters are tedious and error-prone. This paper proposes a solution for streamlining the calculation of line parameters and updating of their values in respective software databases. The algorithms used for calculating the values of line parameters are described. The software developed for implementing the solution is described, and typical results are presented. The proposed solution is developed for a utility and has a potential to be put into use by other utilities. [ABSTRACT FROM AUTHOR]

This paper presents a novel fault location method for transmission lines. The proposed method extends an existing method to locate faults by employing voltage and current measurements at one bus, which can be the bus of the faulted line or be far away from the faulted line. The method is applicable if a loop exists that encloses the faulted line, and the bus, of which the voltage is used, and the branch, of which the current is used. The during-fault positive-sequence bus impedance matrix is derived. Then superimposed voltages and currents due to the fault are expressed as a function of fault location and related transfer and driving point impedances. Consequently, the fault location can be evaluated using the obtained measurements. The distributed parameter line model is adopted to consider the shunt capacitances of the line. The proposed method is independent of fault resistance and fault type. Simulation studies have been carried out based on a 27-bus power system, and promising results have been achieved. [ABSTRACT FROM AUTHOR]

This article presents a novel fault location algorithm for parallel transmission lines for scenarios where only limited synchronized voltage and current measurements are available. Existing methods usually request measurements at the faulted line to be available. However, this may not always be the case due to the limited number of recording devices placed in a power system. The proposed method makes the most of available measurements and does not require the measurements to be captured from the faulted line. The pre-fault and during-fault bus impedance matrices for the positive-sequence network are derived. Synchronized bus voltages and branch currents are then expressed as a function of fault location and line parameters. As a result, fault location can be estimated using the obtained measurements. The distributed parameter line model is adopted to fully consider the shunt capacitances of the line. To eliminate the influence of bad measurements, optimal estimation theory is adopted for enhanced accuracy of the fault location estimate. Simulation studies have been carried out based on a 27-bus power system, and encouraging results have been achieved. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive neuro-fuzzy inference system and a set of novel features for classification of power quality disturbances. The most common types of disturbances including flickers, harmonics, impulses, notches, outages, sags, swells, and switching transients are considered in this research. The proposed method employs voltage waveforms for analysis. The features are extracted utilizing the signal processing techniques such as the windowed discrete Fourier transform and S-transform. Evaluation studies based on both simulated and field data are reported. [ABSTRACT FROM AUTHOR]

In electric power systems, not all fault conditions remain unchanged during faults. An evolving fault has one characteristic initially and changes to a different condition subsequently. Locating evolving faults is challenging due to the change in fault type shortly after the fault initiation. This paper presents a new approach for estimating the locations of evolving faults on transmission lines. By using sparse wide area voltage measurements, this method is able to accurately locate evolving faults without requiring measurements from either end of the faulted line. There is no need to detect whether a fault is an evolving fault or not. Fault type information is not a necessity either, and the change of fault phases does not affect the estimation accuracy. In addition, the algorithm is applicable to both single-circuit and double-circuit lines, and the transmission lines can be either transposed or untransposed. Distributed parameter line model is adopted to fully consider the shunt capacitances of the transmission lines. Electromagnetic Transient Program (EMTP) is employed to simulate transmission system, and quite accurate results have been achieved. [ABSTRACT FROM AUTHOR]

Promptly locating faults in distribution systems plays an essential role in restoring services. Presence of laterals may lead to multiple solutions by impedance-based method. One possible way for quickly identifying the faulted feeder section is to utilize the overcurrent information provided by the switching devices installed in the system. This article presents an enhanced method that identifies the faulted feeder section based on the information from switching devices and the network structure. The proposed method is general, applicable to presence of a single-fault or multi-faults, and suitable for single- or multi-source networks. The advantages over existing methods are elimination of iterative steps for multi-source systems. Case studies have demonstrated that the method is effective in identifying the faulted section. [ABSTRACT FROM AUTHOR]