Abstract:
This thesis presents a research work which is carried out to find out correct network resources requirement for an automatic meter reading system. There are various technologies available to automate the meter reading such as PLC, messaging over GSM, telephone line and RF technologies. As far as utilities providers are concerned, their focus is on a reliable AMR system to read the meter at minimum cost. Development of a reliable AMR system is highly dependant on telecommunication infrastructure which is costly. Therefore, network resource planning needs to be researched in depth to develop a reliable utility wide AMR system. This particular research is on data concentrator based AMR system focusing on the analysing of cross relationship between channel requirements of the last mile data communication channel, data concentrator memory requirement and backbone channel bandwidth requirements. This research has established mathematical simulation models for the last mile channel communication, data concentration memory and backbone channel communication infrastructure and integrated into a single model using software tool MATLAB Simulink. This model has established a scientific conclusion of a methodology to estimate the infrastructure requirements to design of such data concentrator based AMR system. Developed MATLAB Simulink program is used as a computational algorithm that can repeat the program with multi variable inputs to obtain the numerical results. Monte Carlo method is quite useful for solving this kind of simulating phenomena with having many degrees of freedom, significant uncertainty in inputs and wide variety of scenarios. Various sampling parameters were input to the system and, related results for various scenarios were obtained. These results were then used to find out cross relationships between three main components of a data concentrator based AMR systems and their requirements. The results of this research are also adopted to develop a utility wide AMR system as pilot projects with LECO staff at various distribution networks.
