Efficient photovoltaic system maximum power point tracking using a new technique

Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV systems under partial shading conditions followed by the introduction of the new RMO-based technique for GMPP tracking. Finally, results are presented to demonstration the performance of the proposed technique under different partial shading conditions. The results are compared with those of the PSO method, one of the most widely used methods in the literature. Four factors, namely convergence speed, efficiency (power loss reduction), stability (oscillation reduction) and computational cost, are considered in the comparison with the PSO technique.

Computer Aided Design Algorithmic Technique for Very Large Scale Integrated Circuit Design and Smart Home Embedded System Design

To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.

Cost analysis error? Exploring issues relating to whole-life cost estimation in sustainable housing

Purpose: The main purpose of the study is to promote consideration of the issues and approaches available for costing sustainable buildings with a view to minimising cost overruns, occasioned by conservative whole-life cost estimates. The paper primarily looks at the impact of adopting continuity in whole-life cost models for zero carbon houses. Design/methodology/approach: The study embraces a mathematically based risk procedure based on the binomial theorem for analysing the cost implication of the Lighthouse zero-carbon house project. A practical application of the continuous whole-life cost model is developed and results are compared with existing whole-life cost techniques using finite element methods and Monte Carlo analysis. Findings: With standard whole-life costing, discounted present-value analysis tends to underestimate the cost of a project. Adopting continuity in whole-life cost models presents a clearer picture and profile of the economic realities and decision-choices confronting clients and policy-makers. It also expands the informative scope on the costs of zero-carbon housing projects. Research limitations/implications: A primary limitation in this work is its focus on just one property type as the unit of analysis. This research is also limited in its consideration of initial and running cost categories only. The capital cost figures for the Lighthouse are indicative rather than definitive. Practical implications: The continuous whole-life cost technique is a novel and innovative approach in financial appraisal [...] Benefits of an improved costing framework will be far-reaching in establishing effective policies aimed at client acceptance and optimally performing supply chain networks. Originality/value: The continuous whole-life costing pioneers an experimental departure from the stereo-typical discounting mechanism in standard whole-life costing procedures.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).