This paper presents a measurement-based method to determine distributed energy resource (DER) active- and reactive-power setpoints that minimize bus voltage deviations from prescribed reference values, bus active- and reactive-power deviations from desired setpoints, as well as cost of DER outputs. Central to the proposed method is the estimation of a linear sensitivity model from synchronized voltage and power-injection data collected from distribution-level phasor measurement units installed at only a subset of buses in the distribution system. As new measurements become available, the linear sensitivity model is updated via the recursive weighted partial least-squares estimation method, which is shown to be effective for data sets with high collinearity. The estimated sensitivity model is then embedded as an equality constraint in a convex quadratic optimization problem, which can be solved via, e.g., the alternating direction method of multipliers. Numerical simulations involving the IEEE 33-bus distribution test system illustrate key benefits of the proposed method, which are that it (i) eliminates the need for an accurate offline system model, (ii) adapts to online network-topology and operating-point changes, and (iii) is robust against delays potentially attributed to communication, computation, and actuation. Additional numerical simulations involving larger test systems demonstrate computational scalability.

The accurate detection and identification of intermittent cable faults are helpful in improving the reliability of the distribution system. This paper proposes intermittent fault detection and identification for distribution networks based on machine-learning (ML) techniques. For this reason, the IEEE 33 bus system is simulated in the radial and mesh topologies by considering all possible single- and three-phase electrical faults and limitations to collect high-resolution voltage and current waveforms. Moreover, this simulation investigates and considers various cases including low-impedance faults (LIFs) and high-impedance faults (HIFs) with a short and long duration. The collected data from the simulation are used for high-impedance intermittent fault detection, classification, and branch identification using eight supervised learning methods. A comparison between the accuracy and error of these ML classifiers shows that gradient booster (GB) and K-nearest neighbors (KNN) have the best performance for all three objectives. However, GB has a very high computation time compared to KNN.

This paper presents a distributed measurement-based method to determine distributed energy resource (DER) active- and reactive-power setpoints that minimize bus voltage deviations from prescribed references, bus active- and reactive-power deviations from desired values, as well as cost of DER outputs. The proposed method partitions the system into multiple areas and performs per-area computations in parallel, thus mitigating scalability concerns of centralized implementations. A linear sensitivity model for each area is first estimated from measurements via the recursive weighted partial least-squares algorithm. The estimated sensitivity models are then embedded in an optimization problem, the structure of which is amenable to decomposition into per-area subproblems. The subproblems are solved in parallel using consensus-based alternating direction method of multipliers to obtain optimal DER setpoints. Both the estimation and optimization tasks require only the exchange of information at boundary buses among adjacent areas. Numerical simulations involving the IEEE 33-bus distribution test system illustrate the ability of the proposed method to determine optimal DER setpoints that adapt to operating-point changes in a distributed fashion. Additional numerical simulations involving the IEEE 123-bus system demonstrate computational scalability and the application to multi-phase systems in a practical scenario.

Deviations of the electron function velocity distribution from Maxwellian behavior in the high energy range have been extensively studied during the past two decades. A brief review of the experimental techniques and findings on the subject is given in this paper. There are indications that the electron distribution function in thermonuclear plasmas could be significantly different from the Maxwellian one even near the thermal velocity range when particular circumstances occur. These reasons motivate a renewed effort in the measurements that could detect low energies distortions, among which is the new Oblique Electron Cyclotron Emission diagnostics that has entered operations during 2006 experimental campaign at JET and aims to resolve relatively small differences in the ECE spectra taken at three toroidal angles. Such measurements allow insight into the characteristics of the electron distribution function. First results of such experimental system are discussed in this paper, along with emission simulations.

This paper presents a measurement-based method to calculate distribution locational marginal prices (DLMPs) toward establishing real-time electricity markets that help to support reliable and efficient operation of distribution systems. The calculation of DLMPs typically relies on an accurate and up-to-date distribution network model, but this may not be available in practice. Instead, central to the proposed method is the online estimation of linear sensitivity models that map bus voltages to power injections and to line power flows using only synchrophasor measurements collected at buses interfacing market participants and in lines of interest. The estimated linear models replace the nonlinear power flow constraints in a multi-period look-ahead optimal power flow (OPF) problem, thus obviating the need for an offline distribution network model in obtaining DLMPs as the optimal Lagrange multipliers of the linear sensitivity constraints. Moreover, the modified OPF problem with linear constraints is a convex quadratic programming problem, for which computationally efficient solvers are readily available. The resulting DLMPs also embed costs due to potential congestion in certain lines monitored by synchrophasor measurements. Numerical simulations demonstrate the effectiveness, adaptability, and scalability of the proposed measurement-based method to establish a real-time market for distributed generation, energy storage devices, and flexible loads.