Measuring Application Availability,Usage and Performance : Implementation of EnView System

The main objective for this degree project is to implement an Application Availability Monitoring (AAM) system named Softek EnView for Fujitsu Services. The aim of implementing the AAM system is to proactively identify end user performance problems, such as application and site performance, before the actual end users experience them. No matter how well applications and sites are designed and nomatter how well they meet business requirements, they are useless to the end users if the performance is slow and/or unreliable. It is important for the customers to find out whether the end user problems are caused by the network or application malfunction. The Softek EnView was comprised of the following EnView components: Robot, Monitor, Reporter, Collector and Repository. The implemented system, however, is designed to use only some of these EnView elements: Robot, Reporter and depository. Robots can be placed at any key user location and are dedicated to customers, which means that when the number of customers increases, at the sametime the amount of Robots will increase. To make the AAM system ideal for the company to use, it was integrated with Fujitsu Services’ centralised monitoring system, BMC PATROL Enterprise Manager (PEM). That was actually the reason for deciding to drop the EnView Monitor element. After the system was fully implemented, the AAM system was ready for production. Transactions were (and are) written and deployed on Robots to simulate typical end user actions. These transactions are configured to run with certain intervals, which are defined collectively with customers. While they are driven against customers’ applicationsautomatically, transactions collect availability data and response time data all the time. In case of a failure in transactions, the robot immediately quits the transactionand writes detailed information to a log file about what went wrong and which element failed while going through an application. Then an alert is generated by a BMC PATROL Agent based on this data and is sent to the BMC PEM. Fujitsu Services’ monitoring room receives the alert, reacts to it according to the incident management process in ITIL and by alerting system specialists on critical incidents to resolve problems. As a result of the data gathered by the Robots, weekly reports, which contain detailed statistics and trend analyses of ongoing quality of IT services, is provided for the Customers.

Analyzing the Effect of Soiling on the Performance of a Photovoltaic System of Different Module Technologies in Kalkbult, South Africa

The fact that most of the large scale solar PV plants are built in arid and semi-arid areas where land availability and solar radiation is high, it is expected the performance of the PV plants in such locations will be affected significantly due to high cell temperature as well as due to soiling. Therefore, it is essential to study how the different PV module technologies will perform in such geographical locations to ensure a consistent and reliable power delivery over the lifetime of the PV power plants. As soiling is strongly dependent on the climatic conditions of a particular location a test station, consisted of about 24 PV modules and a well-equipped weather station, was built within the fences of Scatec’s 75 MW Kalkbult solar PV plant in South Africa. This study was performed to a better understand the effect of soiling by comparing the relative power generation by the cleaned modules to the un-cleaned modules. Such knowledge can enable more quantitative evaluations of the cleaning strategies that are going to be implemented in bigger solar PV power plants. The data collected and recorded from the test station has been analyzed at IFE, Norway using a MatLab script written for this thesis project. This thesis work has been done at IFE, Norway in collaboration with Stellenbosch University in South Africa and Scatec Solar a Norwegian independent power producer company. Generally for the polycrystalline modules it is found that the average temperature corrected efficiency during the period of the experiment has been 15.00±0.08 % and for the thin film-CdTe with ARC is 11.52% and for the thin film without ARC is about 11.13% with standard uncertainty of ±0.01 %. Besides, by comparing the initial relative average efficiency of the polycrystalline-Si modules when all the modules have been cleaned for the first time and the final relative efficiency; after the last cleaning schedule which is when all the reference modules E, F, G, and H have been cleaned for the last time it is found that poly3 performs 2 % and 3 % better than poly1 and poly16 respectively, poly13 performs 1 % better than poly15 as well as poly5 and poly12 performs 1 % and 2 % better than poly10 respectively. Besides, poly5 and poly12 performs a 9 % and 11 % better than poly7. Furthermore, there is no change in performance between poly6 and poly9 as well as poly4 and poly15. However, the increase in performance of poly3 to poly1, poly13 to poly15 as well as poly5 and poly12 to poly10 is insignificant. In addition, it is found that TF22 perform 7% better than the reference un-cleaned module TF24 and similarly; TF21 performs 7% higher than TF23. Furthermore, modules with ARC glass (TF17, TF18, TF19, and TF20) shows that cleaning the modules with only distilled water (TF19) or dry-cleaned after cleaned with distilled water(TF20) decreases the performance of the modules by 5 % and 4 % comparing to its respective reference uncleanedmodules TF17 and TF18 respectively.