Photovoltaic System Design for a Contaminated Area in Falun – Comparison of South and East- West Layout

In this thesis the solar part of a large grid-connected photovoltaic system design has been done. The main purpose was to size and optimize the system and to present figures helping to evaluate the prospective project rationality, which can potentially be constructed on a contaminated area in Falun. The methodology consisted in PV market study and component selection, site analysis and defining suitable area for solar installation; and system configuration optimization based on PVsyst simulations and Levelized Cost of Energy calculations. The procedure was mainly divided on two parts, preliminary and detailed sizing. In the first part the objective was complex, which included the investigation of the most profitable component combination and system optimization due to tilt and row distance. It was done by simulating systems with different components and orientations, which were sized for the same 100kW inverter in order to make a fair comparison. For each simulated result a simplified LCOE calculation procedure was applied. The main results of this part show that with the price of 0.43 €/Wp thin-film modules were the most cost effective solution for the case with a great advantage over crystalline type in terms of financial attractiveness. From the results of the preliminary study it was possible to select the optimal system configuration, which was used in the detailed sizing as a starting point. In this part the PVsyst simulations were run, which included full scale system design considering near shadings created by factory buildings. Additionally, more complex procedure of LCOE calculation has been used here considered insurances, maintenance, time value of money and possible cost reduction due to the system size. Two system options were proposed in final results; both cover the same area of 66000 m2. The first one represents an ordinary South faced design with 1.1 MW nominal power, which was optimized for the highest performance. According to PVsyst simulations, this system should produce 1108 MWh/year with the initial investment of 835,000 € and 0.056 €/kWh LCOE. The second option has an alternative East-West orientation, which allows to cover 80% of occupied ground and consequently have 6.6 MW PV nominal power. The system produces 5388 MWh/year costs about 4500,000 € and delivers electricity with the same price of 0.056 €/kWh. Even though the EW solution has 20% lower specific energy production, it benefits mainly from lower relative costs for inverters, mounting and annual maintenance expenses. After analyzing the performance results, among the two alternatives none of the systems showed a clear superiority so there was no optimal system proposed. Both, South and East-West solutions have own advantages and disadvantages in terms of energy production profile, configuration, installation and maintenance. Furthermore, the uncertainty due to cost figures assumptions restricted the results veracity.

Using locally available components and local knowledge to build sustainable stand-alone power systems

The aim of this paper is to point out benefits as well as disadvantages associated with the use of locally available, not necessarily standardized, components in stand-alone electrical power systems at rural locations. Advantages and challenges arising when the direct involvement in design, construction and maintenance of the power system is reserved to people based in the area of implementation are discussed. The presented research is centered around one particular PV-diesel hybrid system in Tanzania; a case study in which technical and social aspects related to the particular power system are studied.

Residual-based test for Nonlinear Cointegration with application in PPPs

Nested by linear cointegration first provided in Granger (1981), the definition of nonlinear cointegration is presented in this paper. Sequentially, a nonlinear cointegrated economic system is introduced. What we mainly study is testing no nonlinear cointegration against nonlinear cointegration by residual-based test, which is ready for detecting stochastic trend in nonlinear autoregression models. We construct cointegrating regression along with smooth transition components from smooth transition autoregression model. Some properties are analyzed and discussed during the estimation procedure for cointegrating regression, including description of transition variable. Autoregression of order one is considered as the model of estimated residuals for residual-based test, from which the teststatistic is obtained. Critical values and asymptotic distribution of the test statistic that we request for different cointegrating regressions with different sample sizes are derived based on Monte Carlo simulation. The proposed theoretical methods and models are illustrated by an empirical example, comparing the results with linear cointegration application in Hamilton (1994). It is concluded that there exists nonlinear cointegration in our system in the final results.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.