Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Disorder-induced phase transition in a one-dimensional model of rice pile

We propose a one-dimensional rice-pile model which connects the 1D BTW sandpile model (Phys. Rev. A 38 (1988) 364) and the Oslo rice-pile model (Phys. Rev. Lett. 77 (1997) 107) in a continuous manner. We found that for a sufficiently large system, there is a sharp transition between the trivial critical behaviour of the 1D BTW model and the self-organized critical (SOC) behaviour. When there is SOC, the model belongs to a known universality class with the avalanche exponent tau = 1.53. (C) 1999 Elsevier Science B.V. All rights reserved.

Modelling gas storage with compressed air energy storage in a system with large wind penetrations

Installed wind capacity in the European Union is expected to continue to increase due to renewable energy targets and obligations to reduce greenhouse gas emissions. Renewable energy sources such as wind power are variable sources of power. Energy storage technologies are useful to manage the issues associated with variable renewable energy sources and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in electric power systems and can be used in each of the steps of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothening the variability of large penetrations of wind power. Compress Air Energy Storage is one such technology. The aim of this paper is to examine the technical and economic feasibility of a combined gas storage and compressed air energy storage facility in the all-island Single Electricity Market of Northern Ireland and the Republic of Ireland in order to optimise power generation and wind power integration. This analysis is undertaken using the electricity market software PLEXOS ® for power systems by developing a model of a combined facility in 2020.

Coordinated Design of Phase Measurement Unit and Power System Stabilisers in Large Scale Power System

This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

A Scalable General Purpose System for Large-Scale Graph Processing

Graph analytics is an important and computationally demanding class of data analytics. It is essential to balance scalability, ease-of-use and high performance in large scale graph analytics. As such, it is necessary to hide the complexity of parallelism, data distribution and memory locality behind an abstract interface. The aim of this work is to build a scalable graph analytics framework that does not demand significant parallel programming experience based on NUMA-awareness.
The realization of such a system faces two key problems:
(i)~how to develop a scale-free parallel programming framework that scales efficiently across NUMA domains; (ii)~how to efficiently apply graph partitioning in order to create separate and largely independent work items that can be distributed among threads.

Comparison of a centralised and distributed approach for a generic scheduling system

PEGS (Production and Environmental Generic Scheduler) is a generic production scheduler that produces good schedules over a wide range of problems. It is centralised, using search strategies with the Shifting Bottleneck algorithm. We have also developed an alternative distributed approach using software agents. In some cases this reduces run times by a factor of 10 or more. In most cases, the agent-based program also produces good solutions for published benchmark data, and the short run times make our program useful for a large range of problems. Test results show that the agents can produce schedules comparable to the best found so far for some benchmark datasets and actually better schedules than PEGS on our own random datasets. The flexibility that agents can provide for today's dynamic scheduling is also appealing. We suggest that in this sort of generic or commercial system, the agent-based approach is a good alternative.

Cardiovascular disease risk profiles among 'healthy' siblings of patients with early-onset cardiovascular disease:Application of the new SCORE system

BACKGROUND: Cardiovascular disease (CVD) occurs more frequently in individuals with a family history of premature CVD. Within families the demographics of CVD are poorly described. DESIGN: We examined the risk estimation based on the Systematic Coronary Risk Evaluation (SCORE) system and the Joint British Guidelines (JBG) for older unaffected siblings of patients with premature CVD (onset ≤55 years for men and ≤60 years for women). METHODS: Between August 1999 and November 2003 laboratory and demographic details were collected on probands with early-onset CVD and their older unaffected siblings. Siblings were screened for clinically overt CVD by a standard questionnaire and 12-lead electrocardiogram (ECG). RESULTS: A total of 790 siblings was identified and full demographic details were available for 645. The following siblings were excluded: 41 with known diabetes mellitus; seven with random plasma glucose of 11.1 mmol/l or greater; and eight with ischaemic ECG. Data were analysed for 589 siblings from 405 families. The mean age was 55.0 years, 43.1% were men and 28.7% were smokers. The mean total serum cholesterol was 5.8 mmol/l and hypertension was present in 49.4%. Using the SCORE system, when projected to age 60 years, 181 men (71.3%) and 67 women (20.0%) would be eligible for risk factor modification. Using JBG with a 10-year risk of 20% or greater, 42 men (16.5%) and four women (1.2%) would be targeted. CONCLUSIONS: Large numbers of these asymptomatic individuals meet both European and British guidelines for the primary prevention of CVD and should be targeted for risk factor modification. The prevalence of individuals defined as eligible for treatment is much higher when using the SCORE system. © 2007 European Society of Cardiology.

A Simple Triaxial System for Evaluating the Performance of Unsaturated Soils Under Repeated Loading

Unsaturated soils constitute a large proportion of the foundation materials supporting infrastructure throughout the world and they are subject to various loading conditions. This paper describes the development of a simple system for testing unsaturated soils under repeated loading. The equipment was comprised of a modified triaxial cell with hydraulic loading system, hall-effect transducers for on-sample strain measurements, and thermocouple psychrometer for suction measurements. A number of undrained monotonic and repeated loading triaxial tests were performed on compacted samples of kaolin clay in order to attest the newly developed system. The results yielded some useful information on the resilient modulus and permanent deformation of a soil when subjected to repeated loading. There is some difference between the failure deviator stress of samples subjected to repeated and monotonic loading, though repeated loading continued to result in a significant permanent deformation. This paper is aimed at demonstrating the key features of the equipment using preliminary data generated as part of the on-going research.

Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

The appraisal of an automated multi-immunoaffinity chromatography system to detect anabolic agents in bile and urine

Screening for residues of anabolic steroids frequently requires extraction from tissues and fluids before analysis. Chemical procedures for these extractions can be complicated, expensive to perform and not ideal for the simultaneous extraction of analytes with different solubilities. Extraction by multi-immunoaffinity chromatography (MIAC) may be used as an alternative. Samples are passed through a column containing a range of antibodies immobilized on an inert support. The desired analytes are bound to their respective antibodies, washed and then eluted by a suitable solvent. The purified extracts can then be incorporated into the analytical tests, The analytes that can be extracted presently are alpha-nortestosterone, zeranol, trenbolone, diethylstilboestrol, boldenone and dexamethasone. Manually, the MIAC procedure is limited to about six columns per operator but bq automating the process using a robotic sample processor (RSP), 48 columns can be run simultaneously during the day or night. The RSP has also been adapted to transfer extracts and reagents on to ELISA plates. The automated system has proved to be a robust and reliable means of screening large numbers of samples for anabolic agents with minimal manual input