Project neptune: Improved operation of water distribution networks

Water service providers (WSPs) in the UK have statutory obligations to supply drinking water to all customers that complies with increasingly stringent water quality regulations and minimum flow and pressure criteria. At the same time, the industry is required by regulators and investors to demonstrate increasing operational efficiency and to meet a wide range of performance criteria that are expected to improve year-on-year. Most WSPs have an ideal for improving the operation of their water supply systems based on increased knowledge and understanding of their assets and a shift to proactive management followed by steadily increasing degrees of system monitoring, automation and optimisation. The fundamental mission is, however, to ensure security of supply, with no interruptions and water quality of the highest standard at the tap. Unfortunately, advanced technologies required to fully understand, manage and automate water supply system operation either do not yet exist, are only partially evolved, or have not yet been reliably proven for live water distribution systems. It is this deficiency that the project NEPTUNE seeks to address by carrying out research into 3 main areas; these are: data and knowledge management; pressure management (including energy management); and the associated complex decision support systems on which to base interventions. The 3-year project started in April of 2007 and has already resulted in a number of research findings under the three main research priority areas (RPA). The paper summarises in greater detail the overall project objectives, the RPA activities and the areas of research innovation that are being undertaken in this major, UK collaborative study. Copyright 2009 ASCE.

Enhanced supply chain tracking based on the EPC network: A Bayesian approach

Supply chain tracking information is one of the main levers for achieving operational efficiency. RFID technology and the EPC Network can deliver serial-level product information that was never before available. However, these technologies still fail to meet the managers' visibility requirements in full, since they provide information about product location at specific time instances only. This paper proposes a model that uses the data provided by the EPC Network to deliver enhanced tracking information to the final user. Following a Bayesian approach, the model produces realistic ongoing estimates about the current and future location of products across a supply network, taking into account the characteristics of the product behavior and the configuration of the data collection points. These estimates can then be used to optimize operational decisions that depend on product availability at different locations. The enhancement of tracking information quality is highlighted through an example. © 2009 IFAC.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Electronic load interface for improving PV dual-converter system operational margin

An electronic load interface (ELI) for improving the operational margin of a photovoltaic (PV) dual-converter system under dynamic conditions is presented. The ELI - based on a modified buck-boost converter - interfaces the output of the converters and the load system. It improves the operational margin of the PV dual-converter system by extending the conditions under which the dual-converter system operates at the maximum power point. The ELI is activated as and when needed, so as minimise system losses. By employing the ELI, utilisation and efficiency of a PV dual-converter system increases. In general, the concept of the ELI can be applied to multi-converter PV systems - such as multi-converter inverters, and multi-converter DC-DC converter systems - for performance and efficiency improvement. © 2013 The Institution of Engineering and Technology.

High photoluminescence quantum efficiency InGaN multiple quantum well structures emitting at 380 nm

In this paper we report the design of high room temperature photoluminescence internal efficiency InGaN-based quantum well structures emitting in the near ultraviolet at 380 nm. To counter the effects of nonradiative recombination the quantum wells were designed to have a large indium fraction, high barriers, and a small quantum well thickness. To minimize the interwell and interbarrier thickness fluctuations we used Al0.2In0.005Ga0.795N barriers, where the inclusion of the small fraction of indium was found to lead to fewer structural defects and a reduction in the layer thickness fluctuations. This approach has led us to achieve, for an In0.08Ga0.92N/Al0.2In0.005Ga0.795N multiple quantum well structure with a well width of 1.5 nm, a photoluminescence internal efficiency of 67% for peak emission at 382 nm at room temperature. (c) 2007 American Institute of Physics.

Optical and micro-structural properties of high photoluminescence efficiency InGaN/AlInGaN quantum well structures

We have studied the optical properties of a series of InGaN/AlInGaN 10-period multiple quantum wells (MQW) with differing well thickness grown by metal-organic vapor-phase epitaxy that emit at around 380 nm. The aim of this investigation was to optimise the room temperature internal quantum efficiency, thus the quantum well (QW) thicknesses were accordingly chosen so that the overlap of the electron/hole wave function was maximised. At low temperature, we observed a reduction of the photo luminescence decay time with decreasing well width in line with the theoretical predictions. For a structure with well thicknesses of 1.5 nm, we measured a photoluminescence internal quantum efficiency of 67% at room temperature with a peak emission wavelength of 382 nm. (c) 2006 Elsevier B.V. All rights reserved.

Energy efficiency with natural ventilation: a case study

Application of laboratory analogue modelling of air flow in a naturally ventilated shopping mall is reviewed in this paper. A detailed study of the ventilation was undertaken to establish the principles and to explore how natural ventilation might interact with a localised mechanical ventilation system designed to enhance the cooling of a high density food court area. The case study is used to show how the combination of laboratory modelling and simplified mathematical modelling enables one to rapidly identify the various flow regimes which can occur, to quantify the resultant flows and mean temperatures and to thereby develop appropriate ventilation strategies for the different external conditions which occur through the year.

Efficiency measurement of GaN-based quantum well and light-emitting diode structures grown on silicon substrates

The optical efficiency of GaN-based multiple quantum well (MQW) and light emitting diode (LED) structures grown on Si(111) substrates by metal-organic vapor phase epitaxy was measured and compared with equivalent structures on sapphire. The crystalline quality of the LED structures was comprehensively characterized using x-ray diffraction, atomic force microscopy, and plan-view transmission electron microscopy. A room temperature photoluminescence (PL) internal quantum efficiency (IQE) as high as 58% has been achieved in an InGaN/GaN MQW on Si, emitting at 460 nm. This is the highest reported PL-IQE of a c-plane GaN-based MQW on Si, and the radiative efficiency of this sample compares well with similar structures grown on sapphire. Processed LED devices on Si also show good electroluminescence (EL) performance, including a forward bias voltage of ∼3.5 V at 20 mA and a light output power of 1 mW at 45 mA from a 500 ×500 μm2 planar device without the use of any additional techniques to enhance the output coupling. The extraction efficiency of the LED devices was calculated, and the EL-IQE was then estimated to have a maximum value of 33% at a current density of 4 A cm-2, dropping to 30% at a current density of 40 A cm-2 for a planar LED device on Si emitting at 455 nm. The EL-IQE was clearly observed to increase as the structural quality of the material increased for devices on both sapphire and Si substrates. © 2011 American Institute of Physics.