GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems

YesProposes the application of a genetic algorithm (GA) and simulated annealing (SA) based hybrid approach for the scheduling of generator maintenance in power systems using an integer representation. The adapted approach uses the probabilistic acceptance criterion of simulated annealing within the genetic algorithm framework. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the solution technique are discussed. The results in this paper demonstrate that the technique is more effective than approaches based solely on genetic algorithms or solely on simulated annealing. It therefore proves to be a valid approach for the solution of generator maintenance scheduling problem

A case study of process facility optimization using discrete event simulation and genetic algorithm

Optimization problems such as resource allocation, job-shop scheduling, equipment utilization and process scheduling occur in a broad range of processing industries. This paper presents modeling, simulation and optimization of a port facility such that effective operational management is obtained. A GA base approach has been integrated with the port system model to optimize its operation. A case study of bulk material port handling systems is considered

Generation scheduling using genetic algorithm based hybrid techniques

The solution of generation scheduling (GS) problems involves the determination of the unit commitment (UC) and economic dispatch (ED) for each generator in a power system at each time interval in the scheduling period. The solution procedure requires the simultaneous consideration of these two decisions. In recent years researchers have focused much attention on new solution techniques to GS. This paper proposes the application of a variety of genetic algorithm (GA) based approaches and investigates how these techniques may be improved in order to more quickly obtain the optimum or near optimum solution for the GS problem. The results obtained show that the GA-based hybrid approach offers an effective alternative for solving realistic GS problems within a realistic timeframe

An Evolutionary Generation Scheduling in an Open Electricity Market

YesThe classical generation scheduling problem defines on/off decisions (commitment) and dispatch level of all available generators in a power system for each scheduling period. In recent years researchers have focused on developing new approaches to solve nonclassical generation scheduling problems in the newly deregulated and decentralized electricity market place. In this paper a GA-based approach has been developed for a system operator to schedule generation in a market akin to that operating in England and Wales. A generation scheduling problem has been formulated and solved using available trading information at the time of dispatch. The solution is updated after information is obtained in a rolling fashion. The approach is tested for two IEEE network-based problems, and achieves comparable results with a branch and bound technique in reasonable CPU time

Spinning Strings, Black Holes and Stable Closed Timelike Geodesics

The existence and stability under linear perturbation of closed timelike curves in the spacetime associated to Schwarzschild black hole pierced by a spinning string are studied. Due to the superposition of the black hole, we find that the spinning string spacetime is deformed in such a way to allow the existence of closed timelike geodesics.Comment: 5 pages, RevTex4, some corrections and new material adde

Multiwavelength studies of MHD waves in the solar chromosphere: An overview of recent results

The chromosphere is a thin layer of the solar atmosphere that bridges the relatively cool photosphere and the intensely heated transition region and corona. Compressible and incompressible waves propagating through the chromosphere can supply significant amounts of energy to the interface region and corona. In recent years an abundance of high-resolution observations from state-of-the-art facilities have provided new and exciting ways of disentangling the characteristics of oscillatory phenomena propagating through the dynamic chromosphere. Coupled with rapid advancements in magnetohydrodynamic wave theory, we are now in an ideal position to thoroughly investigate the role waves play in supplying energy to sustain chromospheric and coronal heating. Here, we review the recent progress made in characterising, categorising and interpreting oscillations manifesting in the solar chromosphere, with an impetus placed on their intrinsic energetics.Comment: 48 pages, 25 figures, accepted into Space Science Review

Processing GOTO data with the Rubin Observatory LSST Science Pipelines I: Production of coadded frames

The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy, however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO), whose primary science objective is the optical follow-up of Gravitational Wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near real-time to fully exploit the time-domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this "off-the-shelf" pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to sub-pixel levels, and that measured L-band photometries are accurate to ∼50 mmag at mL∼16 and ∼200 mmag at mL∼18. These values compare favourably to those obtained using GOTO's primary, in-house pipeline, GOTOPHOTO, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic "obs package" that others can build-upon should they wish to use the LSST Science Pipelines to process data from other facilities

From marine bands to hybrid flows: sedimentology of a Mississippian black shale

Organic‐rich mudstones have long been of interest as conventional and unconventional source rocks and are an important organic carbon sink. Yet the processes that deposited organic‐rich muds in epicontinental seaways are poorly understood, partly because few modern analogues exist. This study investigates the processes that transported and deposited sediment and organic matter through part of the Bowland Shale Formation, from the Mississippian Rheic–Tethys seaway. Field to micron‐scale sedimentological analysis reveals a heterogeneous succession of carbonate‐rich, siliceous, and siliciclastic, argillaceous muds. Deposition of these facies at basinal and slope locations was moderated by progradation of the nearby Pendle delta system, fourth‐order eustatic sea‐level fluctuation and localized block and basin tectonism. Marine transgressions deposited bioclastic ‘marine band’ (hemi)pelagic packages. These include abundant euhaline macrofaunal tests, and phosphatic concretions of organic matter and radiolarian tests interpreted as faecal pellets sourced from a productive water column. Lens‐rich (lenticular) mudstones, hybrid, debrite and turbidite beds successively overlie marine band packages and suggest reducing basin accommodation promoted sediment deposition via laminar and hybrid flows sourced from the basin margins. Mud lenses in lenticular mudstones lack organic linings and bioclasts and are equant in early‐cemented lenses and in plan‐view, and are largest and most abundant in mudstones overlying marine band packages. Thus, lenses likely represent partially consolidated mud clasts that were scoured and transported in bedload from the shelf or proximal slope, as a ‘shelf to basin’ conveyor, during periods of reduced basin accommodation. Candidate in situ microbial mats in strongly lenticular mudstones, and as rip‐up fragments in the down‐dip hybrid beds, suggest that these were potentially key biostabilizers of mud. Deltaic mud export was fast, despite the intrabasinal complexity, likely an order of magnitude higher than similar successions deposited in North America. Epicontinental basins remotely linked to delta systems were therefore capable of rapidly accumulating both sediment and organic matter

Physics with the KLOE-2 experiment at the upgraded DAϕ\phiNE

Investigation at a $\phi$--factory can shed light on several debated issues in particle physics. We discuss: i) recent theoretical development and experimental progress in kaon physics relevant for the Standard Model tests in the flavor sector, ii) the sensitivity we can reach in probing CPT and Quantum Mechanics from time evolution of entangled kaon states, iii) the interest for improving on the present measurements of non-leptonic and radiative decays of kaons and eta/eta$^\prime$ mesons, iv) the contribution to understand the nature of light scalar mesons, and v) the opportunity to search for narrow di-lepton resonances suggested by recent models proposing a hidden dark-matter sector. We also report on the $e^+ e^-$ physics in the continuum with the measurements of (multi)hadronic cross sections and the study of gamma gamma processes.Comment: 60 pages, 41 figures; added affiliation for one of the authors; added reference to section

Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream. A problem that arises in real-world applications of learning algorithms for classification is imbalanced data, where a class of objects within the data is underrepresented, leading to a bias for over-represented classes in the ML and DL classifiers. We present a recurrent neural network (RNN) classifier that takes in photometric time-series data and additional contextual information (such as distance to nearby galaxies and on-sky position) to produce real-time classification of objects observed by the Gravitational-wave Optical Transient Observer (GOTO), and use an algorithm-level approach for handling imbalance with a focal loss function. The classifier is able to achieve an Area Under the Curve (AUC) score of 0.972 when using all available photometric observations to classify variable stars, supernovae, and active galactic nuclei. The RNN architecture allows us to classify incomplete light curves, and measure how performance improves as more observations are included. We also investigate the role that contextual information plays in producing reliable object classification