A loop cancellation based active damping solution for constant power instability in vehicular power systems

In recent years, electric propulsion systems have increasingly been used in land, sea and air vehicles. The vehicular power systems are usually loaded with tightly regulated power electronic converters which tend to draw constant power. Since the constant power loads (CPLs) impose negative incremental resistance characteristics on the feeder system, they pose a potential threat to the stability of vehicular power systems. This effect becomes more significant in the presence of distribution lines between source and load in large vehicular power systems such as electric ships and more electric aircrafts. System transients such as sudden drop of converter side loads or increase of constant power requirement can cause complete system instability. Most of the existing research work focuses on the modeling and stabilization of DC vehicular power systems with CPLs. Only a few solutions are proposed to stabilize AC vehicular power systems with non-negligible distribution lines and CPLs. Therefore, this paper proposes a novel loop cancellation technique to eliminate constant power instability in AC vehicular power systems with a theoretically unbounded system stability region. Analysis is carried out on system stability with the proposed method and simulation results are presented to validate its effectiveness.

Generation of catalytically active materials from a liquid metal precursor

A facile route to prepare catalystically active materials from a galinstan liquid metal alloy is introduced. Sonicating liquid galinstan in alkaline solution or treating it in reducing media results in the creation of solid In/Sn rich microspheres that show catalytic activity toward both potassium ferricyanide and 4-nitrophenol reduction.

Probabilistic load flow for distribution systems with uncertain PV generation

Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF techniques are not suitable for distribution systems and suffer from several drawbacks such as computational burden (Monte Carlo, Conventional convolution), sensitive accuracy with the complexity of system (point estimation method), requirement of necessary linearization (multi-linear simulation) and convergence problem (Gram–Charlier expansion, Cornish Fisher expansion). In this research, Latin Hypercube Sampling with Cholesky Decomposition (LHS-CD) is used to quantify the over-voltage issues with and without the voltage control algorithm in the distribution network with active generation. LHS technique is verified with a test network and real system from an Australian distribution network service provider. Accuracy and computational burden of simulated results are also compared with Monte Carlo simulations.

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.