Adaptive edge analytics for distributed networked control of water systems

Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.

Solvable model for distribution networks on random graphs

We propose a simple model that captures the salient properties of distribution networks, and study the possible occurrence of blackouts, i.e., sudden failings of large portions of such networks. The model is defined on a random graph of finite connectivity. The nodes of the graph represent hubs of the network, while the edges of the graph represent the links of the distribution network. Both, the nodes and the edges carry dynamical two state variables representing the functioning or dysfunctional state of the node or link in question. We describe a dynamical process in which the breakdown of a link or node is triggered when the level of maintenance it receives falls below a given threshold. This form of dynamics can lead to situations of catastrophic breakdown, if levels of maintenance are themselves dependent on the functioning of the net, once maintenance levels locally fall below a critical threshold due to fluctuations. We formulate conditions under which such systems can be analyzed in terms of thermodynamic equilibrium techniques, and under these conditions derive a phase diagram characterizing the collective behavior of the system, given its model parameters. The phase diagram is confirmed qualitatively and quantitatively by simulations on explicit realizations of the graph, thus confirming the validity of our approach. © 2007 The American Physical Society.

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.

Statistical mechanics of distribution networks

This thesis presents an analysis of the stability of complex distribution networks. We present a stability analysis against cascading failures. We propose a spin [binary] model, based on concepts of statistical mechanics. We test macroscopic properties of distribution networks with respect to various topological structures and distributions of microparameters. The equilibrium properties of the systems are obtained in a statistical mechanics framework by application of the replica method. We demonstrate the validity of our approach by comparing it with Monte Carlo simulations. We analyse the network properties in terms of phase diagrams and found both qualitative and quantitative dependence of the network properties on the network structure and macroparameters. The structure of the phase diagrams points at the existence of phase transition and the presence of stable and metastable states in the system. We also present an analysis of robustness against overloading in the distribution networks. We propose a model that describes a distribution process in a network. The model incorporates the currents between any connected hubs in the network, local constraints in the form of Kirchoff's law and a global optimizational criterion. The flow of currents in the system is driven by the consumption. We study two principal types of model: infinite and finite link capacity. The key properties are the distributions of currents in the system. We again use a statistical mechanics framework to describe the currents in the system in terms of macroscopic parameters. In order to obtain observable properties we apply the replica method. We are able to assess the criticality of the level of demand with respect to the available resources and the architecture of the network. Furthermore, the parts of the system, where critical currents may emerge, can be identified. This, in turn, provides us with the characteristic description of the spread of the overloading in the systems.

An assessment of the performance of high density polyethylene copolymers for natural gas distribution pipes

The total thermoplastics pipe market in west Europe is estimated at 900,000 metric tonnes for 1977 and is projected to grow to some 1.3 million tonnes of predominantly PVC and polyolefins pipe by 1985. By that time, polyethylene for gas distribution pipe and fittings will represent some 30% of the total polyethylene pipe market. The performance characteristics of a high density polyethylene are significantly influenced by both molecular weight and type of comonomer; the major influences being in the long-term hoop stress resistance and the environmental stress cracking resistance. Minor amounts of hexene-1 are more effective than comonomers lower in the homologous series, although there is some sacrifice of density related properties. A synergistic improvement is obtained by combining molecular weight increase with copolymerisation. The Long-term design strength of polyethylene copolymers can be determined from hoop stress measurement at elevated temperatures and by means of a separation factor of approximate value 22, extrapolation can be made to room temperature performance for a water environment. A polyethylene of black composition has a sufficiently improved performance over yellow pigmented pipe to cast doubts on the validity of internationally specifying yellow coded pipe for gas distribution service. The chemical environment (condensate formation) that can exist in natural gas distribution networks has a deleterious effect on the pipe performance the reduction amounting to at least two decades in log time. Desorption of such condensate is very slow and the influence of the more aggressive aromatic components is to lead to premature stress cracking. For natural gas distribution purposes, the design stress rating should be 39 Kg/cm2 for polyethylenes in the molecular weight range of 150 - 200,000 and 55 Kg/cm2 for higher molecular weight materials.

Reconfiguration of distribution network into islanded microgrids considering development of distributed energy resources

This paper discusses the potentiality of reconfiguring distribution networks into islanded Microgrids to reduce the network infrastructure reinforcement requirement and incorporate various dispersed energy resources. The major challenge would be properly breaking down the network and its resultant protection and automation system changes. A reconfiguration method is proposed based on allocation of distributed generation resources to fulfil this purpose, with a heuristic algorithm. Cost/reliability data is required for the next stage tasks to realise a case study of a particular network.

Predicting practical benefits of dynamic asset ratings of 33kv distribution transformers

This paper reports potential benefits around dynamic thermal rating prediction of primary transformers within Western Power Distribution (WPD) managed Project FALCON (Flexible Approaches to Low Carbon Optimised Networks). Details of the thermal modelling, parameter optimisation and results validation are presented with asset and environmental data (measured and day/week-ahead forecast) which are used for determining dynamic ampacity. Detailed analysis of ratings and benefits and confidence in ability to accurately predict dynamic ratings are presented. Investigating the effect of sustained ONAN rating compared to a dynamic rating shows that there is scope to increase sustained ratings under ONAN operating conditions by up to 10% higher between December and March with a high degree of confidence. However, under high ambient temperature conditions this dynamic rating may also reduce in the summer months.

Review on protection issues of low-voltage distribution network with multiple powerelectronic-converter-interfaced distribution energy resources

The realisation of an eventual low-voltage (LV) Smart Grid with a complete communication infrastructure is a gradual process. During this evolution the protection scheme of distribution networks should be continuously adapted and optimised to fit the protection and cost requirements at the time. This paper aims to review practices and research around the design of an effective, adaptive and economical distribution network protection scheme. The background of this topic is introduced and potential problems are defined from conventional protection theories and new Smart Grid technologies. Challenges are identified with possible solutions defined as a pathway to the ultimate flexible and reliable LV protection systems.

A study of the drying of single droplets in free-flight

The literature relating to evaporation from single droplets of pure liquids and the drying of solution and slurry droplets, and of droplet sprays has been reviewed. The heat and mass transfer rates for individual droplets suspended in free-flight, were investigated using a specially-designed vertical wind tunnel, to simulate conditions in a spray drier. The technique represented a unique alternative method for investigating evaporation from unrestrained single droplets with variable residence times. The experiments covered droplets of pure liquid allowbreak (water, isopropanol) allowbreak and of significantly different solutions (sucrose, potassium sulphate) over a range of temperatures of 37oC to 97oC, initial concentrations of 5 to 40wt/wt% , and initial drop sizes of 2.8 to 4.6mm. Drop behaviour was recorded photographically and dried particles were examined by Scanning Electron Microscopy. Correlations were developed for mass transfer coefficients for pure water droplets in free-flight; (i) experiencing oscillations, rotation and deformation, Sh = -105 + 3.9 [Ta - Td/Tamb]0.18Re0.5Sc033 for Re approx. > 1380 (ii) when these movements had ceased or diminished, Sh = 2.0 + 0.71 [Ta - Td/Tamb]0.18Re0.5Sc033 for Re approx. < 1060. Data for isopropanol drops were correlated resonably well by these equations. The heat transfer data showed a similar transition range. The drying rate curves for drops of sucrose and potassium sulphate solution exhibited three distinct stages; an initial increase in the drying rate as drop temperature reduced to the wet-bulb temperature, a short constant-rate period and a falling-rate period characterised by formation of a crust which controlled the mass transfer rate. Due to drop perturbation the rates in the high Re number region were up to 5 times greater than predicted from theory for spherical droplets. In the case of sucrose solution a `skin' formed over the drop surface prior to crust formation. This provided an additional resistance to mass transfer and resulted in extended drying times and a smooth crust of low porosity. The relevance of the results to practical spray drying operations is discussed.

Interval data without sign restrictions in DEA

Conventional DEA models assume deterministic, precise and non-negative data for input and output observations. However, real applications may be characterized by observations that are given in form of intervals and include negative numbers. For instance, the consumption of electricity in decentralized energy resources may be either negative or positive, depending on the heat consumption. Likewise, the heat losses in distribution networks may be within a certain range, depending on e.g. external temperature and real-time outtake. Complementing earlier work separately addressing the two problems; interval data and negative data; we propose a comprehensive evaluation process for measuring the relative efficiencies of a set of DMUs in DEA. In our general formulation, the intervals may contain upper or lower bounds with different signs. The proposed method determines upper and lower bounds for the technical efficiency through the limits of the intervals after decomposition. Based on the interval scores, DMUs are then classified into three classes, namely, the strictly efficient, weakly efficient and inefficient. An intuitive ranking approach is presented for the respective classes. The approach is demonstrated through an application to the evaluation of bank branches. © 2013.

Application of automatic load transfer on feeder utilisation balance

This paper looks at how automatic load transfer may be used as a possible planning tool to help deliver faster connections for customers. A trial on an area of overhead line Network is presented to show how improvements in % feeder utilisation may be realised by changing the location of the open point. The reported Network data is compared to calculated data under two different configurations over a two week trial period. The results show that ALT open point determination in the presence of generation is different from a load only circuit and that the open points may not be fixed with time. Looking at improvements in Network headroom may not be conducive to other improvements in the network such as loss reduction or improving voltage profiles.

Weather forecasting to predict practical dynamic asset rating of overhead lines

This paper describes the potential of pre-setting 11kV overhead line ratings over a time period of sufficient length to be useful to the real-time management of overhead lines. This forecast is based on short and long term freely available weather forecasts and is used to help investigate the potential for realising dynamic rating benefits on the electricity network. A comparison between the realisable benefits in ratings using this forecast data, over the period of a year has been undertaken.

On the hydrothermal stability of MCM-41. Evidence of capillary tension-induced effects

MCM-41's limited hydrothermal stability has been often related to the hydrolysis of Si-O-Si bonds due to the low degree of condensation, its thin walls or a combination of them. In this work, evidence for an additional factor is provided; a physical effect that occurs during the drying of the hydrothermally treated calcined material due to the intense capillary stress exerted in water. Depending on both physical (i.e. mechanical) and chemical (i.e. hydrolysis) resistances, the structure undergoes differently. Three MCM-41 samples with different degree of condensation were investigated. The most remarkable results are found with un-aged TEOS based material, which gets fully disordered and shrunk for all applied hydrothermal temperatures in water. Comparison between water and a low-surface-tension-solvent drying revealed that capillarity is responsible for the loss of ordering (and shrinkage) at moderate hydrothermal temperatures. The material's structure is hexagonal and shrinkage-free under the low-surface-tension-solvent route. At a high hydrothermal temperature, hydrolysis is extensive and responsible for the loss of ordering. The other remarkable finding regards the aged MCM-41 mesostructure that maintains the hexagonal features at all applied temperatures in water, and it is more stable against capillarity at high temperature. The Na-metasilicate based material is mechanically very stable and gets disordered at high temperature due to hydrolysis.

CDMA multiuser detection, neural networks, and statistical mechanics

A novel approach, based on statistical mechanics, to analyze typical performance of optimum code-division multiple-access (CDMA) multiuser detectors is reviewed. A `black-box' view ot the basic CDMA channel is introduced, based on which the CDMA multiuser detection problem is regarded as a `learning-from-examples' problem of the `binary linear perceptron' in the neural network literature. Adopting Bayes framework, analysis of the performance of the optimum CDMA multiuser detectors is reduced to evaluation of the average of the cumulant generating function of a relevant posterior distribution. The evaluation of the average cumulant generating function is done, based on formal analogy with a similar calculation appearing in the spin glass theory in statistical mechanics, by making use of the replica method, a method developed in the spin glass theory.

A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties