Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.

The Conditional Phase-type distribution: Graphical Models for Continuous Non-Normal Data:The Conditional Phase-type (C-Ph) distribution:

Conditional Gaussian (CG) distributions allow the inclusion of both discrete and continuous variables in a model assuming that the continuous variable is normally distributed. However, the CG distributions have proved to be unsuitable for survival data which tends to be highly skewed. A new method of analysis is required to take into account continuous variables which are not normally distributed. The aim of this paper is to introduce the more appropriate conditional phase-type (C-Ph) distribution for representing a continuous non-normal variable while also incorporating the causal information in the form of a Bayesian network.

Driven optomechanical systems for mechanical entanglement distribution

We consider the distribution of entanglement from a multimode optical driving source to a network of remote and independent optomechanical systems. By focusing on the tripartite case, we analyse the effects that the features of the optical input states have on the degree and sharing structure of the distributed, fully mechanical, entanglement. This study, which is conducted looking at the mechanical steady state, highlights the structure of the entanglement distributed among the nodes and determines the relative efficiency between bipartite and tripartite entanglement transfer. We discuss a few open points, some of which are directed towards the bypassing of such limitations.

Impact of Heat Pump Load on Distribution Networks

Heat pumps can provide domestic heating at a cost that is competitive with oil heating in particular. If the electricity supply contains a significant amount of renewable generation, a move from fossil fuel heating to heat pumps can reduce greenhouse gas emissions. The inherent thermal storage of heat pump installations can also provide the electricity supplier with valuable flexibility. The increase in heat pump installations in the UK and Europe in the last few years poses a challenge for low-voltage networks, due to the use of induction motors to drive the pump compressors. The induction motor load tends to depress voltage, especially on starting. The paper includes experimental results, dynamic load modelling, comparison of experimental results and simulation results for various levels of heat pump deployment. The simulations are based on a generic test network designed to capture the main characteristics of UK distribution system practice. The simulations employ DIgSlILENT to facilitate dynamic simulations that focus on starting current, voltage variations, active power, reactive power and switching transients.

Experimental Distribution of Entanglement with Separable Carriers

The key requirement for quantum networking is the distribution of entanglement between nodes. Surprisingly, entanglement can be generated across a network without direct transfer - or communication - of entanglement. In contrast to information gain, which cannot exceed the communicated information, the entanglement gain is bounded by the communicated quantum discord, a more general measure of quantum correlation that includes but is not limited to entanglement. Here, we experimentally entangle two communicating parties sharing three initially separable photonic qubits by exchange of a carrier photon that is unentangled with either party at all times. We show that distributing entanglement with separable carriers is resilient to noise and in some cases becomes the only way of distributing entanglement through noisy environments.

Network Usage Determination for Transmission Cost Allocation using a Transformer Analogy

This study presents a new method for determining the transmission network usage by loads and generators, which can then be used for transmission cost/loss allocation in an explainable and justifiable manner. The proposed method is based on solid physical grounds and circuit theory. It relies on dividing the currents through the network into two components; the first one is attributed to power flows from generators to loads, whereas the second one is because of the generators only. Unlike almost all the available methods, the proposed method is assumption free and hence it is more accurate than similar methods even those having some physical basis. The proposed method is validated through a transformer analogy, and theoretical derivations. The method is verified through application to the IEEE 30 bus system and the IEEE 118 test system. The results obtained verified many desirable features of the proposed method. Being more accurate in determining the network usage, in an explainable transparent manner, and in giving accurate cost signals, indicating the best locations to add loads and generation, are among the many desirable features.

On-off based charging strategies for EVs connected to a Low Voltage distributon network

The development of appropriate Electric Vehicle (EV) charging strategies has been identified as an effective way to accommodate an increasing number of EVs on Low Voltage (LV) distribution networks. Most research studies to date assume that future charging facilities will be capable of regulating charge rates continuously, while very few papers consider the more realistic situation of EV chargers that support only on-off charging functionality. In this work, a distributed charging algorithm applicable to on-off based charging systems is presented. Then, a modified version of the algorithm is proposed to incorporate real power system constraints. Both algorithms are compared with uncontrolled and centralized charging strategies from the perspective of both utilities and customers. © 2013 IEEE.

Integrating petrography, mineralogy and hydrochemistry to constrain the influence and distribution of groundwater contributions to baseflow in poorly productive aquifers: Insights from Gortinlieve catchment, Co. Donegal, NW Ireland

Identifying groundwater contributions to baseflowforms an essential part of surfacewater body characterisation. The Gortinlieve catchment (5 km2) comprises a headwater stream network of the Carrigans River, itself a tributary of the River Foyle, NW Ireland. The bedrock comprises poorly productive metasediments that are characterised by fracture porosity. We present the findings of a multi-disciplinary study that integrates new hydrochemical and mineralogical investigations with existing hydraulic, geophysical and structural data to identify the scales of groundwater flow and the nature of groundwater/bedrock interaction (chemical denudation). At the catchment scale, the development of deep weathering profiles is controlled by NE-SW regional scale fracture zones associated with mountain building during the Grampian orogeny. In-situ chemical denudation of mineral phases is controlled by micro- to meso-scale fractures related to Alpine compression during Palaeocene to Oligocene times. The alteration of primary muscovite, chlorite (clinochlore) and albite along the surfaces of these small-scale fractures has resulted in the precipitation of illite, montmorillonite and illite/montmorillonite clay admixtures. The interconnected but discontinuous nature of these small-scale structures highlights the role of larger scale faults and fissures in the supply and transportation of weathering solutions to/from the sites of mineral weathering. The dissolution of primarily mineral phases releases the major ions Mg, Ca and HCO3 that are shown to subsequently formthe chemical makeup of groundwaters. Borehole groundwater and stream baseflow hydrochemical data are used to constrain the depths of groundwater flow pathways influencing the chemistry of surface waters throughout the stream profile. The results show that it is predominantly the lower part of the catchment, which receives inputs from catchment/regional scale groundwater flow, that is found to contribute to the maintenance of annual baseflow levels. This study identifies the importance
of deep groundwater in maintaining annual baseflow levels in poorly productive bedrock systems.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Improvisation, Indeterminacy and Game-Mediated Participation in Network Music Performance

This chapter focuses on the relationship between improvisation and indeterminacy. We discuss the two practices by referring to play theory and game studies and situate it in recent network music performance. We will develop a parallel with game theory in which indeterminacy is seen as a way of articulating situations where structural decisions are left to the discernment of the performers and discuss improvisation as a method of play. The improvisation-indeterminacy relationship is discussed in the context of network music performance, which employs digital networks in the exchange of data between performers and hence relies on topological structures with varying degrees of openness and flexibility. Artists such as Max Neuhaus and The League of Automatic Music Composers initiated the development of a multitude of practices and technologies exploring the network as an environment for music making. Even though the technologies behind “the network” have shifted dramatically since Neuhaus’ use of radio in the 1960’s, a preoccupation with distribution and sharing of artistic agency has remained at the centre of networked practices. Gollo Föllmer, after undertaking an extensive review of network music initiatives, produced a typology that comprises categories as diverse as remix lists, sound toys, real/virtual space installations and network performances. For Föllmer, “the term ‘Net music’ comprises all formal and stylistic kinds of music upon which the specifics of electronic networks leave considerable traces, whereby the electronic networks strongly influence the process of musical production, the musical aesthetic, or the way music is received” (2005: 185).

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.