Energy Management using storage to facilitate high shares of Variable Renewable Energy

Remote islands are a very lucrative market for Variable Renewable Energy (VRE) resources. They rely on expensive fossil fuels, primarily diesel, to suffice their electrical generation demands and to ensure reliability. This not only makes them vulnerable to the fluctuating oil prices in the international market but also depletes their environment. The paper looks into establishing a renewable energy based power generation system facilitated by storage and takes the Island of Bonaire as the case study. Bonaire has good Solar resource summing up to around 1,826 kWh/m2, while a healthy Wind resource until September when it faces low wind speeds until December. Using the actual load profile obtained from the utility at Bonaire; WEB Bonaire, two scenarios are generated using Homer Pro software. The first scenario; business-as-usual, is based on replicating the current power system and establishing a baseline for further comparison. The second scenario; Renewable Energy Scenario, aims to facilitate high shares of Wind and Solar using storage technologies – Hydrogen to be used when the wind resources are low as a seasonal storage, and Lithium Iron Phosphate batteries to absorb surplus energy by VRE technologies and to be used when they are not available on daily basis. The RE scenario lowers the share of Diesel based power generation from 65.78% to 0.53% and results in an LCOE of 12.76€ cents/kWh. The RE scenario demonstrates the efficient use of Hydrogen production and storage over longer periods of times and illustrates its feasibility

NOT ANOTHER CANCER JOURNAL!

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Particle tracking using the unscented Kalman filter in high energy physics experiments

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The extended Kalman lter (EKF) has a long history in the field of non-linear tracking. More recently, statistically-based estimators have emerged that avoid the need for a deterministic linearisation process. The Unscented Kalman filter (UKF) is one such technique that has been shown to perform favourably for some non-linear systems when compared to an EKF implementation, both in terms of accuracy and robustness. In this Thesis, the UKF is applied to a high energy physics particle tracking problem where currently the EKF is being implemented. The effects of measurement redundancy are investigated to determine improvements in accuracy of particle track reconstruction. The relationship between measurement redundancy and relative observability is also investigated through an experimental and theoretical analysis. Smoothing (backward filtering), in the high energy physics experiments, is implementedusing the Rauch Tung Striebel (RTS) smoother with the EKF , however, in Unscented Kalman filter algorithms, the Jacobian matrices required by the RTS method, are not available. The Unscented Rauch Tung Striebel (URTS) smoother addresses this problem by avoiding the use of Jacobian matrices but is not effi cient for large dimensional systems such as high energy physics experiments. A technique is implemented in the RTS smoother to make it suitable for the UKF. The method is given the name the Jacobian Equivalent Rauch Tung Striebel (JE-RTS) smoother. The implementation of this method is quite straight forward when the UKF is used as an estimator

Near to DC level multilevel inverter

The purpose of this study is to investigate the application of genetic algorithm (GA) in modelling linear and non-linear dynamic systems and develop an alternative model structure selection algorithm based on GA. Orthogonal least square (OLS), a gradient descent method was used as the benchmark for the proposed algorithm. A model structure selection based on modified genetic algorithm (MGA) has been proposed in this study to reduce problems of premature convergence in simple GA (SGA). The effect of different combinations of MGA operators on the performance of the developed model was studied and the effectiveness and shortcomings of MGA were highlighted. Results were compared between SGA, MGA and benchmark OLS method. It was discovered that with similar number of dynamic terms, in most cases, MGA performs better than SGA in terms of exploring potential solution and outperformed the OLS algorithm in terms of selected number of terms and predictive accuracy. In addition, the use of local search with MGA for fine-tuning the algorithm was also proposed and investigated, named as memetic algorithm (MA). Simulation results demonstrated that in most cases, MA is able to produce an adequate and parsimonious model that can satisfy the model validation tests with significant advantages over OLS, SGA and MGA methods. Furthermore, the case studies on identification of multivariable systems based on real experiment t al data from two systems namely a turbo alternator and a continuous stirred tank reactor showed that the proposed algorithm could be used as an alternative to adequately identify adequate and parsimonious models for those systems. Abstract must be bilingual. For a thesis written in Bahasa Melayu, the abstract must first be written in Bahasa Melayu and followed by the English translation. If the thesis is written in English, the abstract must be written in English and followed by the translation in Bahasa Melayu. The abstract should be brief, written in one paragraph and not exceed one (1) page. An abstract is different from synopsis or summary of a thesis. It should states the field of study, problem definition, methodology adopted, research process, results obtained and conclusion of the research. The abstract can be written using single or one and a half spacing. Example can be seen in Appendix 1 (Bahasa Melayu) and Appendix J (English)

ENHANCEMENT OF MARKOV RANDOM FIELD MECHANISM TO ACHIEVE FAULT-TOLERANCE IN NANOSCALE CIRCUIT DESIGN

As the MOSFET dimensions scale down towards nanoscale level, the reliability of circuits based on these devices decreases. Hence, designing reliable systems using these nano-devices is becoming challenging. Therefore, a mechanism has to be devised that can make the nanoscale systems perform reliably using unreliable circuit components. The solution is fault-tolerant circuit design. Markov Random Field (MRF) is an effective approach that achieves fault-tolerance in integrated circuit design. The previous research on this technique suffers from limitations at the design, simulation and implementation levels. As improvements, the MRF fault-tolerance rules have been validated for a practical circuit example. The simulation framework is extended from thermal to a combination of thermal and random telegraph signal (RTS) noise sources to provide a more rigorous noise environment for the simulation of circuits build on nanoscale technologies. Moreover, an architecture-level improvement has been proposed in the design of previous MRF gates. The redesigned MRF is termed as Improved-MRF. The CMOS, MRF and Improved-MRF designs were simulated under application of highly noisy inputs. On the basis of simulations conducted for several test circuits, it is found that Improved-MRF circuits are 400 whereas MRF circuits are only 10 times more noise-tolerant than the CMOS alternatives. The number of transistors, on the other hand increased from a factor of 9 to 15 from MRF to Improved-MRF respectively (as compared to the CMOS). Therefore, in order to provide a trade-off between reliability and the area overhead required for obtaining a fault-tolerant circuit, a novel parameter called as ‘Reliable Area Index’ (RAI) is introduced in this research work. The value of RAI exceeds around 1.3 and 40 times for MRF and Improved-MRF respectively as compared to CMOS design which makes Improved- MRF to be still 30 times more efficient circuit design than MRF in terms of maintaining a suitable trade-off between reliability and area-consumption of the circuit

Innovative optical non-contact measurement of respiratory function using photometric stereo

Pulmonary functional testing is very common and widely used in today's clinical environment for testing lung function. The contact based nature of a Spirometer can cause breathing awareness that alters the breathing pattern, affects the amount of air inhaled and exhaled and has hygiene implications. Spirometry also requires a high degree of compliance from the patient, as they have to breathe through a hand held mouth piece. To solve these issues a non-contact computer vision based system was developed for Pulmonary Functional Testing. This employs an improved photometric stereo method that was developed to recover local 3D surface orientation to enable calculation of breathing volumes. Although Photometric Stereo offers an attractive technique for acquiring 3D data using low-cost equipment, inherent limitations in the methodology have served to limit its practical application, particularly in measurement or metrology tasks. Traditional Photometric Stereo assumes that lighting directions at every pixel are the same, which is not usually the case in real applications and especially where the size of object being observed is comparable to the working distance. Such imperfections of the illumination may make the subsequent reconstruction procedures used to obtain the 3D shape of the scene, prone to low frequency geometric distortion and systematic error (bias). Also, the 3D reconstruction of the object results in a geometric shape with an unknown scale. To overcome these problems a novel method of estimating the distance of the object from the camera was developed, which employs Photometric Stereo images without using other additional imaging modality. The method firstly identifies the Lambertian Diffused Maxima regions to calculate the object's distance from the camera, from which the corrected per-pixel light vector is derived and the absolute dimensions of the object can be subsequently estimated. We also propose a new calibration process to allow a dynamic (as an object moves in the field of view) calculation of light vectors for each pixel with little additional computational cost. Experiments performed on synthetic as well as real data demonstrate that the proposed approach offers improved performance, achieving a reduction in the estimated surface normal error by up to 45% as well as the mean height error of reconstructed surface of up to 6 mm. In addition, compared with traditional photometric stereo, the proposed method reduces the mean angular and height error so that it is low, constant and independent of the position of the object placement within a normal working range. A high (0.98) correlation between breathing volume calculated from Photometric Stereo and Spirometer data was observed. This breathing volume is then converted to absolute amount of air by using distance information obtained by Lambertian Diffused Maxima Region. The unique and novel feature of this system is that it views the patients from both front and back and creates a 3D structure of the whole torso. By observing the 3D structure of the torso over time, the amount of air inhaled and exhaled can be estimated

Libra: An Economy driven Job Scheduling System for Clusters

Clusters of computers have emerged as mainstream parallel and distributed platforms for high-performance, high-throughput and high-availability computing. To enable effective resource management on clusters, numerous cluster managements systems and schedulers have been designed. However, their focus has essentially been on maximizing CPU performance, but not on improving the value of utility delivered to the user and quality of services. This paper presents a new computational economy driven scheduling system called Libra, which has been designed to support allocation of resources based on the users? quality of service (QoS) requirements. It is intended to work as an add-on to the existing queuing and resource management system. The first version has been implemented as a plugin scheduler to the PBS (Portable Batch System) system. The scheduler offers market-based economy driven service for managing batch jobs on clusters by scheduling CPU time according to user utility as determined by their budget and deadline rather than system performance considerations. The Libra scheduler ensures that both these constraints are met within an O(n) run-time. The Libra scheduler has been simulated using the GridSim toolkit to carry out a detailed performance analysis. Results show that the deadline and budget based proportional resource allocation strategy improves the utility of the system and user satisfaction as compared to system-centric scheduling strategies.Comment: 13 page

OPTIMIZATION OF GAS LIFT SYSTEM

The intent behind this study was to optimize the Gas Lift System in order to achieve the target of maximizing the oil production from the four oil wells. To accomplish the optimization process, hurdles or constraints associated were addressed efficiently which resulted in effective outcome. Initial gas injection rates and oil production rates were analyzed by using Well Flo3.8.7 and maximum economic waters cuts were calculated for each well. Increasing water cuts is one of the major constraint that limits the injection gas volume which needs to be optimized and this constraint was addressed by calculating the optimum gas injection rates for all wells using Well Flo3.8.7. The overall comparison between the initial conditions and optimized conditions for all wells were presented in order to provide a clear picture of optimization in terms of oil production and maximum economic water cut. The results for total increase in all production were found to be 25954stb/day and initially it was 19099stb/day. The maximum economic water cut has been improved from 52% to 78%. The second major constraint is the ability of compressor to handle the optimized gas lift volumes and to deliver these gas volumes at sufficient discharge pressure for effective gas lift process, which were addressed by making use of HYSIS simulator. A model of three stage compression system is run in HYSIS simulator by using the designed capacity of compressor in terms of volume and discharge pressure to validate the design ratings and the load of compressor was also calculated at these conditions which includes power consumption by each compression stage and respective inter stage coolers. Another model is run in HYSIS simulator for compression train and the results for the optimum injection gas lift rates (23.8 MMSCFD) were used as an input in this model and hence an optimized model of compression train was obtained which could handle the optimized gas lift volumes at sufficient discharge pressure (3100 psig). In the end the total power consumption for both models was compared together and small increase of 253 KWH were observed which is acceptable in terms of increase in oil production