PMU Placement for Power System Observability Using Binary Particle Swarm Optimization

A binary particle swarm optimization (BPSO) based methodology for the optimal placement of phasor measurement units (PMUs) for complete observability of a power system is presented in this paper. The objectives of the optimization problem are to minimize the total number of PMUs required, and to maximize the measurement redundancy at the power system buses. Simulation results on the IEEE 14-bus and 30-bus test systems are presented in this paper

Optimal Control of Class of Non-Linear Plants using Artificial Immune Systems: Application of the Clonal Selection Algorithm

The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear plants which are affine in control. The clonal selection algorithm is adapted for optimal control. A new mutation operator that operates on real values and one that aids in fast convergence is developed in this paper. AIS is used to obtain constant coefficient Kalman gain matrices. The validation and evaluation of the results thus obtained are carried out by comparing with standard and the widely used State Dependent Algebraic Riccati Equation (SDARE) method for the non-linear plants. In case of non-linear systems with hard state constraints, the SDARE formulation requires the use of mathematically involved expressions to incorporate these state constraints. However, the modified clonal selection algorithm developed in this paper has been used with hardly any changes to incorporate the hard state constraints and obtain the Kalman gain matrix

Adaptive Load Frequency Control of Nigerian Hydrothermal System Using Unsupervised and Supervised Learning Neural Networks

This work presents a novel load frequency control design approach for a two-area power system that relies on unsupervised and supervised learning neural network structure. Central to this approach is the prediction of the load disturbance of each area at every minute interval that is uniquely assigned to a cluster via unsupervised learning process. The controller feedback gains corresponding to each cluster center are determined using modal control technique. Thereafter, supervised learning neural network (SLNN) is employed to learn the mapping between each cluster center and its feedback gains. A real time load disturbance in either or both areas activates the appropriate SLNN to generate the corresponding feedback gains. The effectiveness of the control framework is evaluated on the Nigerian hydrothermal system. Several far-reaching simulation results obtained from the test system are presented and discussed to highlight the advantages of the proposed approach

Self-Healing Control with Multifunctional Gate Drive Circuits for Power Converters

Many commercial and military transport systems have fault diagnostic functions implemented to help protect the device when a severe fault occurs. However, most present systems do not contain prognostics capability which would allow operators to observe an unhealthy system component in its pre- fault condition. In industry applications, scheduled downtime can result in considerable cost avoidance. The next technology step is self-healing system components which observe not only potential problems, but can also take steps to continue operation under abnormal conditions - whether due to long-term normal wear-and-tear or sudden combat damage. In this paper, current and voltage information using the double-layer gate drive concept is fed to intelligent networks to identify the type of fault and its location. These intelligent networks are based on unsupervised and supervised learning networks (self-organizing maps and learning vector quantization networks respectively). The proposed concept allows the reconfiguration of the electric machinery system for continued normal operation of the machine. This paper presents an intelligent health monitoring and self-healing control strategy for a multi-phase multilevel motor drive under various types of faults

Robust Tuning of Modern Power System Stabilizers using Bacterial Foraging Algorithm

IEEE Std 421.5, revised by the IEEE excitation system subcommittee introduced a new type of power system stabilizer model, the multiband power system stabilizers (IEEE PSS4B). Although it requires two input signals, like the widely used IEEE PSS2B, the underlying principle of the new IEEE PSS4B makes it sharply different. This paper presents a method based on Bacterial Foraging Algorithm (BFA) to simultaneously tune these modern power system stabilizers (PSSs) in multimachine power system. Simulation results of multi-machine power system validate the efficiency of this approach. the proposed method is effective for the tuning of multi-controllers in large power systems

ASIRI : an ocean–atmosphere initiative for Bay of Bengal

Author Posting. © American Meteorological Society, 2016. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 97 (2016): 1859–1884, doi:10.1175/BAMS-D-14-00197.1.Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes.This work was sponsored by the U.S. Office of Naval Research (ONR) in an ONR Departmental Research Initiative (DRI), Air–Sea Interactions in Northern Indian Ocean (ASIRI), and in a Naval Research Laboratory project, Effects of Bay of Bengal Freshwater Flux on Indian Ocean Monsoon (EBOB). ASIRI–RAWI was funded under the NASCar DRI of the ONR. The Indian component of the program, Ocean Mixing and Monsoons (OMM), was supported by the Ministry of Earth Sciences of India.2017-04-2

The formation and fate of internal waves in the South China Sea

Internal gravity waves, the subsurface analogue of the familiar surface gravity waves that break on beaches, are ubiquitous in the ocean. Because of their strong vertical and horizontal currents, and the turbulent mixing caused by their breaking, they affect a panoply of ocean processes, such as the supply of nutrients for photosynthesis1, sediment and pollutant transport2 and acoustic transmission3; they also pose hazards for man-made structures in the ocean4. Generated primarily by the wind and the tides, internal waves can travel thousands of kilometres from their sources before breaking5, making it challenging to observe them and to include them in numerical climate models, which are sensitive to their effects6,7. For over a decade, studies8-11 have targeted the South China Sea, where the oceans' most powerful known internal waves are generated in the Luzon Strait and steepen dramatically as they propagate west. Confusion has persisted regarding their mechanism of generation, variability and energy budget, however, owing to the lack of in situ data from the Luzon Strait, where extreme flow conditions make measurements difficult. Here we use new observations and numerical models to (1) show that the waves begin as sinusoidal disturbances rather than arising from sharp hydraulic phenomena, (2) reveal the existence of >200-metre-high breaking internal waves in the region of generation that give rise to turbulence levels >10,000 times that in the open ocean, (3) determine that the Kuroshio western boundary current noticeably refracts the internal wave field emanating from the Luzon Strait, and (4) demonstrate a factor-of-two agreement between modelled and observed energy fluxes, which allows us to produce an observationally supported energy budget of the region. Together, these findings give a cradle-to-grave picture of internal waves on a basin scale, which will support further improvements of their representation in numerical climate predictions

The formation and fate of internal waves in the South China Sea

Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature 521 (2015): 65-69, doi:10.1038/nature14399.Internal gravity waves, the subsurface analogue of the familiar surface gravity waves that break on beaches, are ubiquitous in the ocean. Because of their strong vertical and horizontal currents, and the turbulent mixing caused by their breaking, they impact a panoply of ocean processes, such as the supply of nutrients for photosynthesis1, sediment and pollutant transport2 and acoustic transmission3; they also pose hazards for manmade structures in the ocean4. Generated primarily by the wind and the tides, internal waves can travel thousands of kilometres from their sources before breaking5, posing severe challenges for their observation and their inclusion in numerical climate models, which are sensitive to their effects6-7. Over a decade of studies8-11 have targeted the South China Sea, where the oceans’ most powerful internal waves are generated in the Luzon Strait and steepen dramatically as they propagate west. Confusion has persisted regarding their generation mechanism, variability and energy budget, however, due to the lack of in-situ data from the Luzon Strait, where extreme flow conditions make measurements challenging. Here we employ new observations and numerical models to (i) show that the waves begin as sinusoidal disturbances rather than from sharp hydraulic phenomena, (ii) reveal the existence of >200-m-high breaking internal waves in the generation region that give rise to turbulence levels >10,000 times that in the open ocean, (iii) determine that the Kuroshio western boundary current significantly refracts the internal wave field emanating from the Luzon Strait, and (iv) demonstrate a factor-of-two agreement between modelled and observed energy fluxes that enables the first observationally-supported energy budget of the region. Together, these findings give a cradle-to-grave picture of internal waves on a basin scale, which will support further improvements of their representation in numerical climate predictions.Our work was supported by the U.S. Office of Naval Research and the Taiwan National Science Council.2015-10-2

The formation and fate of internal waves in the South China Sea

Internal gravity waves, the subsurface analogue of the familiar surface gravity waves that break on beaches, are ubiquitous in the ocean. Because of their strong vertical and horizontal currents, and the turbulent mixing caused by their breaking, they affect a panoply of ocean processes, such as the supply of nutrients for photosynthesis¹, sediment and pollutant transport² and acoustic transmission³; they also pose hazards for man-made structures in the ocean⁴. Generated primarily by the wind and the tides, internal waves can travel thousands of kilometres from their sources before breaking⁵, making it challenging to observe them and to include them in numerical climate models, which are sensitive to their effects[superscript 6,7]. For over a decade, studies[superscript 8–11] have targeted the South China Sea, where the oceans’ most powerful known internal waves are generated in the Luzon Strait and steepen dramatically as they propagate west. Confusion has persisted regarding their mechanism of generation, variability and energy budget, however, owing to the lack of in situ data from the Luzon Strait, where extreme flow conditions make measurements difficult. Here we use new observations and numerical models to (1) show that the waves begin as sinusoidal disturbances rather than arising from sharp hydraulic phenomena, (2) reveal the existence of >200-metre-high breaking internal waves in the region of generation that give rise to turbulence levels >10,000 times that in the open ocean, (3) determine that the Kuroshio western boundary current noticeably refracts the internal wave field emanating from the Luzon Strait, and (4) demonstrate a factor-of-two agreement between modelled and observed energy fluxes, which allows us to produce an observationally supported energy budget of the region. Together, these findings give a cradle-to-grave picture of internal waves on a basin scale, which will support further improvements of their representation in numerical climate predictions