TECHNO ECONOMIC ANALYSIS, DESIGN AND IMPLEMENT A SUITABLE COMMUNICATION METHOD FOR UTILITY SYSTEMS Mahesh Sachintha Dunuweera (118665 N) Thesis submitted in partial fulfilment of the requirement for the Degree of Master of Science Department of Electrical Engineering University of Moratuwa Sri Lanka August 2016 i Declaration “I declare that this is my own work and this thesis does not incorporate without acknowledgement any material previously submitted for a Degree or Diploma in any other University or institute of higher learning and to the best of my knowledge and belief it does not contain any material previously published or written by another person except where the acknowledgement is made in the text. Also, I hereby grant to University of Moratuwa the non-exclusive right to reproduce and distribute my thesis, in whole or in part in print, electronic or other medium. I retain the right to use this content in whole or part in future works (such as articles or books)”. ……………………….. ……………………….. M.S. Dunuweera Date The above candidate has carried out research for the Masters Thesis under my supervision. ……………………….. ……………………….. Signature of the supervisor Date (Dr. P.S.N. De Silva) ……………………….. ……………………….. Signature of the supervisor Date (Dr. K.T.M.U Hemapala) ……………………….. ……………………….. Signature of the supervisor Date (Dr.Chandika Wavegedara) ii Abstract This thesis presents a research work which is carried out to optimize the Zigbee based remote meter reading network. There are various technologies available to automate the meter reading such as PLC, GSM, Optical fibre and RF technologies. As far as utilities providers are concerned, their focus is on a reliable RMR system to read the meter at minimum possible cost. The development of a reliable RMR system is highly dependent on telecommunication infrastructure which is costly if GPRS is used as a way of communication. Therefore, research were done in depth to analyse the cost and function of RMR system as large number of sensors are used in the electrical utility. This particular research is on data concentrator based RMR system focusing on the analysing of communication delay and resource optimization. In this research Matlab Simulink software was used for simulations and Visual Studio C# is used for creating the software. Several simulations were carried out in this research, for simulating communication speed, communication path and study the behaviour with the presence of noises. As the final outcome of the research, software was developed for selecting Zigbee power rating based on GPS locations and generated algorithms for calculating communication delay and path which can be incorporated to the coordinator. iii Acknowledgement This dissertation is prepared as a result of the support and guidance provided by various personnel and parties. First of all, I would like to express my heartiest gratitude to my supervisors, Dr. P.S.N De Silva from Lanka Electricity Company private Limited (LECO), Dr. K.T.M.U Hemapala from the Department of Electrical Engineering, University of Moratuwa (UOM) and Dr. Chandika Wavegedara from the Department of Electronic and Telecommunication Engineering (UOM) for their support, guidance and valuable advices throughout these academic years. Their continuous supervision and advices on the research, pave me the way for a successful completion of the scope of work. I would like to thank University of Moratuwa for giving me the opportunity for my Master studies. I would like to give my special thanks to Dr. P.S.N De Silva as the Head of Engineering of LECO, Mr. S.D.C. Gunawardana as the System Development Manager of LECO, the Branch Manager and all the staff at LECO Negombo Branch and all staff at LECO Head office, for giving me the support to accomplish my study by providing necessary details on power distribution network. Finally, thanks to all the lecturers & my friends that I have been working with throughout the period of study in University of Moratuwa. iv Table of Contents Chapter 1 1 INTRODUCTION 1 1. 1.1. Introduction to Remote Meter Reading Technology 1 1.2. Analysis of Remote Meter Reading Technology 2 1.3. Problem Identification 3 1.4. Objective 5 1.5. Methodology 5 1.6. Contribution 5 Chapter 2 9 LITERATURE REVIEW 9 2. Chapter 3 15 ENERGY METER AND RMR 15 3. 3.1. Introduction to Electricity Energy Meter 15 3.1.1. Meter Data Communication Protocols 16 3.1.1.1. Introduction to Object Identification System 17 3.1.2. Read Meter Through GPRS (Mobile Network) 19 3.1.3. GPRS 19 3.1.4. PLC 19 3.1.5. Radio Frequency 20 3.1.6. Optical fibre Communication 21 Chapter 4 22 DEVELOPMENT OF TEST BENCH FOR ZIGBEE NETWORK 22 4. 4.1. AnteLECO DDSF949 meter 24 4.1.1. Communication module 24 4.1.2. Coordinator 25 4.2. LQI 27 4.3. RSSI Measurement (dBm) 29 4.4. Data usage of modem 32 4.5. MATLAB Simulink 33 4.6. White Gaussian Noise 34 4.7. Free Space Propagation Model 34 4.8. Economic Analysis 45 4.9. Visual Studio C# 45 v Chapter 5 50 CONCLUSION AND DISCUSSION 50 5. Chapter 6 52 FUTURE DEVELOPMENTS 52 6. REFERENCES 53 7. vi List of Figures Figure 1-1 Observe Mesh network using XCTU software 7 Figure 2-1 Cost and power consumption comparison of wireless technologies 10 Figure 2-2 Zigbee Network topologies 12 Figure 2-3 Zigbee tree routing and shortcut tree routing 13 Figure 3-1 Meter Reading Software 17 Figure 4-1 Location 22 Figure 4-2 Selected locations 23 Figure 4-3 DDSF949 Meter 24 Figure 4-4 Zigbee Routers 24 Figure 4-5 Coordinator 25 Figure 4-6 Observation of mesh network on XCTU software 26 Figure 4-7 LQI variation 26 Figure 4-8 RSSI Logger Software 28 Figure 4-9 Communication delay variation Vs Meter ID on 80 min and 1320 min time stamps 29 Figure 4-10 Communication delay variation Vs Time Stamp for 6th and 56th Meters 29 Figure 4-11 RSSI variation Vs Time Stamp for 1st and 23rd Meters 31 Figure 4-12 RSSI Variation Vs Meter No for day time and night time 31 Figure 4-13 Data usage for 100 meters Vs Reading No 32 Figure 4-14 Data Usage for meter reading 32 Figure 4-15 Number of Attempts to read meter 33 Figure 4-16 Simulation Model 35 Figure 4-17 Simulation Model 36 Figure 4-18 Configuration Window Of Gaussian Noise Generator 37 Figure 4-19 Communication Speed Variation Of Links Vs Time 38 Figure 4-20 Communication Speed of 7th Link Vs Time 38 Figure 4-21 Number of Routings Vs Gaussian Noise Mean Value 39 Figure 4-22 Received No of Nodes Vs Test No 40 Figure 4-23 Simple zigbee arrangement of 10 nodes 41 Figure 4-24 Simulation of communication delay 42 Figure 4-25 Data propagation path 42 Figure 4-26 Developed software for generating levels 43 Figure 4-27 Generated Levels 43 Figure 4-28 Application and Network layers in Zigbee network 44 Figure 4-29 Distance Matrix 45 Figure 4-30 Report 46 Figure 4-31 Flow chart 47 Figure 4-32 Cost reduction vs Number of nodes (between 1 mW and 63 mW) 49 file:///J:/Users/Mahesh/Acadamic/MSc/2nd%20Year/Project/6th%20Step%20Thesis%20M.S.%20Dunuweera/Thesis%20M.S.%20Dunuweera_R32%20With%20grammer%20correction.docx%23_Toc457102693 file:///J:/Users/Mahesh/Acadamic/MSc/2nd%20Year/Project/6th%20Step%20Thesis%20M.S.%20Dunuweera/Thesis%20M.S.%20Dunuweera_R32%20With%20grammer%20correction.docx%23_Toc457102694 file:///J:/Users/Mahesh/Acadamic/MSc/2nd%20Year/Project/6th%20Step%20Thesis%20M.S.%20Dunuweera/Thesis%20M.S.%20Dunuweera_R32%20With%20grammer%20correction.docx%23_Toc457102707 file:///J:/Users/Mahesh/Acadamic/MSc/2nd%20Year/Project/6th%20Step%20Thesis%20M.S.%20Dunuweera/Thesis%20M.S.%20Dunuweera_R32%20With%20grammer%20correction.docx%23_Toc457102716 file:///J:/Users/Mahesh/Acadamic/MSc/2nd%20Year/Project/6th%20Step%20Thesis%20M.S.%20Dunuweera/Thesis%20M.S.%20Dunuweera_R32%20With%20grammer%20correction.docx%23_Toc457102718 file:///J:/Users/Mahesh/Acadamic/MSc/2nd%20Year/Project/6th%20Step%20Thesis%20M.S.%20Dunuweera/Thesis%20M.S.%20Dunuweera_R32%20With%20grammer%20correction.docx%23_Toc457102721 vii List of Tables Table 2-1 Comparison among different wireless technologies 10 Table 2-2 Comparison between wireless technologies 11 Table 3-1 Some registers 18 Table 4-1 Selected Transformers 23 Table 4-2 Result of communication distance measurement 23 Table 4-3 Communication delay Vs time stamp and meter ID 28 Table 4-4 RSSI variation VS Meter ID and Time Stamp 30 Table 4-5 Transmit power 35 Table 4-6 Coordinates of Positions 37 Table 4-7 Test-Communicate with multiple Zigbee units in same time 40 Table 4-8 Practical tests with considering levels 44 Table 4-9 Cost comparison 48 viii List of Abbreviations Abbreviation Description RMR Remote Meter Reading RF Radio Frequency GPRS General Packet Radio Service GSM Global System for Mobile Communications PLC Power Line Carrier AMR Automatic Meter Reading SIM Subscriber Identity Module IOT Internet of Things RSSI Received Signal Strength Indicator ZTR ZigBee Tree Routing STR Shortcut Tree Routing AODV Ad Hoc On Demand Distance Vector DSDV Destination Sequenced Distance Vector TOD Time Of Day OBIS Object Identification System EDIS Energy Data Identification System LQI Line Quality Index LED Light Emitting Diode LD Laser Diode https://www.techopedia.com/definition/2922/ad-hoc-on-demand-distance-vector-aodv ix LIST OF APPENDICES Appendix Description Page Appendix – A Meter Readout data 55 Appendix – B Some Photos 58 Appendix – C Coordinator Program code 59 Appendix – D LQI Variation 68 Appendix – E Simulation Program-Communication Speed 69 Appendix – F Simulation Program-Communication Path 73 Appendix – G Program-VS-Finding Levels and Zigbee pro selection 76 Appendix – H BZ 501 Transformer area map 81