PLANNING WIRELESS MESH NETWORKS FOR IOT SMART GRID APPLICATIONS HUGO CAFÉ ANDRÉ MARTINS PEDRO VIEIRA ANTÓNIO RODRIGUES HUGO.CAFE@TECNICO.ULISBOA.PT ANDRE.MARTINS@CELFINET.COM PVIEIRA@DEETC.ISEL.PT ANTONIO.RODRIGUES@LX.IT.PT 1
INTRODUCTION AIM OF THE STUDY RF MESH SYSTEM FOR SMART METERING - OVERVIEW SIMULATOR ANALYSIS RESULTS & ANALYSIS CASE STUDY BRAZIL CONCLUSIONS AND FUTURE WORK 03 04 05 06 09 12 2
INTRODUCTION THE ENERGY SYSTEMS ARE NOT EFFICIENT THE SOLUTION: SMART GRIDS MONITOR THE ENERGY CONSUMPTIONS 3
AIM OF THE STUDY DEVELOPMENT AND OPTIMIZE A NEIGHBORHOOD AREA NETWORK TO MONITOR ENERGY CONSUMPTION. MULTIPLE-HOPS MESH NETWORK WHICH ENSURES THE CONNECTION BETWEEN THE SMART METERS AND THE CONCENTRATORS. Source: Optimal Positioning of GPRS Concentrators in Smart Grids Considering Routing in Mesh Networks 4
RF MESH SYSTEM FOR SMART METERING - OVERVIEW IEEE 802.15.4 (ZIGBEE) SMART METER DATA RATE: 9.6 KBPS CONCENTRATOR DATA RATE: 9.6 KBPS OR 19.2 KBPS THE UNLICENSED INDUSTRIAL, SCIENTIFIC AND MEDICAL (ISM) BAND OF 902-928 MHZ 240 DISCRETE CHANNELS (100 KHZ BANDWIDTH) FREQUENCY HOPPING SPREAD SPECTRUM SYNCHRONOUS ALOHA WITH 0.7 S TIME SLOTS Source: Landys + Gyr FSK MODULATION IN THE ALLOTTED TIME SLOT NETWORK TIME PROTOCOL 5
SIMULATOR ANALYSIS (1/3) PROPAGATION MODEL L tot = L out + L tw + L in [db] L out = 42.6 + 20 log f GHz L tw = W e + WG e 1 sin θ L in = αd [db] + 26 log(s[km] [db] 2 [db] f=928 MHz α=0.2 db/m d = 2 m W e = 12 db WG e = 25 db θ = 30 o Source: Performance Analysis of Radio Propagation Models for Smart Grid Applications 6
SIMULATOR ANALYSIS (2/3) CONSTRAINTS 3rd 5th TRANSMITTER POWER P t SM = 26 db P t C = 30 db SENSITIVITY P r SM = 108 db P r C = 105 db MAXIMUM DISTANCE BETWEEN SMART METERS 340 M MAXIMUM DISTANCE BETWEEN SMART METER AND CONCENTRATOR 1,830 M P = 512 BYTE PACKET T = 15 MINUTES λ=4.55 M (bit/sec) TRAFFIC CHARACTERIZATION M λ m down = 19200 M = 2nd 4219.78 L = 4219 4th 3rd ε i λ m down + λ m up + λ m up = 9600 ε i = 2nd 1054.44 F =1054 240 DISCRETE CHANNELS 7
SIMULATOR ANALYSIS (3/3) INPUTS ALGORITHM OUTPUTS Build C mesh networks considering R constraint SMART METERS POSITIONS CONCENTRATORS POSSIBLE POSITIONS MAXIMUM DELAY d ij = τ QP = R 1 k=0 N k 7 = 0.7 R R = 10 connected smart meters total smart meters = 0,99 Determine all the assumptions with NA concentrators Reach QP? Y Mesh network considering NA concentrators Verify the constraints? Y N N Metrics 1. Minimum number of hops 2. Minimum distance between smart meters NA= NA+1 NUMBER OF CONCENTRATORS POSITIONS OF CONCENTRATORS CLUSTERS 8
RESULTS & ANALYSIS CASE STUDY BRAZIL (1/3) LOCATION: SÃO PAULO, BRAZIL NUMBER OF SMART METERS 1774 NUMBER OF CONCENTRATOR POSSIBLE POSITIONS - 70 9
RESULTS & ANALYSIS CASE STUDY BRAZIL (2/3) CONCENTRATORS ARE TYPICALLY MOUNTED STRATEGICALLY ON POLE TOPS OR ON LAMP POSTS GOOGLE EARTH STREET VIEW MODE 10
RESULTS & ANALYSIS CASE STUDY BRAZIL (3/3) 11
CONCLUSIONS AND FUTURE WORK EMERGING NEED TO MODERNIZE THE MONITORING OF ENERGY CONSUMPTION AVOID ENERGY WASTAGE IMPROVE COSTUMER EXPERIENCE LOWER GREENHOUSE GAS EMISSION DEVELOPMENT OF A REALISTIC SIMULADOR FOR ENERGY MONITORING USING WIRELESS MESH NETWORKS THE SIMULADOR CONSIDERS THE DEVICES CONSTRAINTS AND THE PROPAGATION MODEL PARAMETERS NEW MASTER THESIS ABOUT IOT (SIGFOX, LTE-MTC, WIRELESS SENSOR NETWORKS, ) 12
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