Wireless Sensor and Actuator Networks for Lighting Energy ...

More documents

Recommendations

Info

The second scenario assumed a more densely occupied office with seven occupants present, and the lighting preferences of some occupants sitting adjacent to each other varied drastically. This simulation demonstrated the capability of the system to balance diverse and conflicting lighting preferences while delivering reasonable lighting to all occupants. The resulting workplane level illuminance is shown in Figure 6-7, and the corresponding optimal settings for each luminaire are [76%, 27%, 100%, 100%, 100%, 60%, 96%, 0%, 21%, 0%, 44%, 0%]. Only 52.0% of the light was used compared to the original all-on/off lighting configuration. The optimized light setting, the numbers in the middle of each group of three stacked numbers in Figure 6-7, diverged from the specified values (the numbers at the bottom) due to the necessary compromise of diversely specified preferences between adjacent occupants. Nonetheless, the optimized lighting stayed within 15% of the specified illuminances, as did the actual measurements. Figure 6-7 Optimal lighting for scenario 2. 93
It is obvious from Figure 6-6 and Figure 6-7 that the measured illuminances differed from the calculated optimal illuminances more significantly towards the north side of the office (right side) where an artificial wall was placed in the room to simulate an interior room. The additional absorption and reflection introduced by the virtual wall might have rendered the illuminance models near the north side of the office less accurate. Since the illuminance models were generated with respect to an empty room, the furniture in the real office could have also contributed to the inaccuracies in the models. Moreover, the lighting hardware, namely the dimming ballasts and fluorescent lamps, might not guarantee a consistent mapping from the dimming signals to the actual output luminous due to manufacturing tolerances. These uncertainties signified the need of sensory feedback for better performances. 6.4.2 Lighting Optimization Algorithm with Sensory Feedback The sensor information was incorporated for testing the optimal lighting actuation algorithm with sensory feedback to eliminate possible modeling uncertainties as well as to respond to daylight. Four occupants were present in the office, and the photosensors were placed on their desktops to measure the task illuminances and send the lighting information back for the next iteration of optimization. The algorithm was set to terminate when the difference between the specified lighting preferences and the actual illuminances were within five lux for all occupants. As shown in Figure 6-8, it took four iterations for the light to converge to each occupant’s preference. The top number of each stack of five numbers represents the preferred lighting specified by each occupant, and the following four numbers are the sensor readings after the first, second, 94
Page 1 and 2:
Wireless Sensor and Actuator Networ
Page 3 and 4:
Abstract Wireless Sensor and Actuat
Page 5 and 6:
To my wife for having faith in me a
Page 7 and 8:
Table of Contents Chapter 1 Introdu
Page 9 and 10:
6.4.2 Lighting Optimization Algorit
Page 11 and 12:
10.2.1 Theoretical Contributions...
Page 13 and 14:
List of Figures Figure 1-1 Research
Page 15 and 16:
Figure 7-8 Voltage divider. .......
Page 17 and 18:
Figure 9-31 Energy savings vs. payb
Page 19 and 20:
The integration of wireless sensor
Page 21 and 22:
esulting lighting is optimal in the
Page 23 and 24:
acquisition and wireless transmissi
Page 25 and 26:
a central base computer for sensor
Page 27 and 28:
optimal light settings were in turn
Page 29 and 30:
possibility of wireless actuator ne
Page 31 and 32:
Chapter 2 Motivation The motivation
Page 33 and 34:
[21]. Lighting accounts for 30% of
Page 35 and 36:
Table 2-1 summarizes each of the co
Page 37 and 38:
from light level tuning impossible
Page 39 and 40:
used in the progress of this resear
Page 41 and 42:
are expected to autonomously config
Page 43 and 44:
office, and industrial applications
Page 45 and 46:
Chapter 3 Related Research and Lite
Page 47 and 48:
Although radio frequency is a suppo
Page 49 and 50:
channels with different capabilitie
Page 51 and 52:
In practice, fusion of sensor data
Page 53 and 54:
The emergence of wireless sensor ne
Page 55 and 56:
A is empty f A (x) = 0, x X (3.1)
Page 57 and 58:
Convex combination: the relation Th
Page 59 and 60: where no crisp boundary can be defi
Page 61 and 62: developed by Dantzig [87]. The ineq
Page 63 and 64: sensor network is far more valuable
Page 65 and 66: Figure 4-1 Mote-FVF algorithm archi
Page 67 and 68: Figure 4-2 Gaussian correlation cur
Page 69 and 70: predicted reading. Note that the of
Page 71 and 72: fuzzification and m for the defuzz
Page 73 and 74: mote sensors were arranged in a 3-b
Page 75 and 76: Figure 4-6 Mote-FVF with median val
Page 77 and 78: Figure 4-8 Comparison of variations
Page 79 and 80: The daylighting system application
Page 81 and 82: The key components are the predicti
Page 83 and 84: Figure 5-3 Prediction performance o
Page 85 and 86: Figure 5-5 Prediction performance o
Page 87 and 88: Among them, adaptive Wiener filteri
Page 89 and 90: even though the sensed environment
Page 91 and 92: 5.3 Simulation and Experiment Resul
Page 93 and 94: Figure 5-11 Adaptive sensing with d
Page 95 and 96: Figure 5-13 Damped adaptive sensing
Page 97 and 98: Chapter 6 Optimal Lighting Actuatio
Page 99 and 100: of the workplane level illuminance
Page 101 and 102: office with K luminaires, for examp
Page 103 and 104: E sub = e pq e rs e xy 1
Page 105 and 106: optimizer for a consistency check.
Page 107 and 108: Figure 6-4 Pseudo code of the light
Page 109: simulation was to show that the opt
Page 113 and 114: Chapter 7 Wireless-Enabled Lighting
Page 115 and 116: determined to be 0-2000 lux. Conseq
Page 117 and 118: discrete outputs from the motes spa
Page 119 and 120: actuation technologies, and additio
Page 122 and 123: Figure 7-8 Voltage divider. Since t
Page 124 and 125: Given the 256-level dimming capabil
Page 126 and 127: Figure 7-11 Prototyping Luminaire S
Page 128 and 129: to its simplicity. Although coded w
Page 130 and 131: The second experiment was executed
Page 132 and 133: Chapter 8 System Verification on Hu
Page 134 and 135: commercial system was randomized fo
Page 136 and 137: 8.2.1 Hardware Implementation in Sm
Page 138 and 139: eference point on the desktop was s
Page 140 and 141: commands were received. In addition
Page 142 and 143: were provided with three wireless p
Page 144 and 145: (a) Figure 8-6 Sensor placement of
Page 146 and 147: lower meter readings was that the m
Page 148 and 149: (2) Subtle and invisible shadows ma
Page 150 and 151: function keys are. The function key
Page 152 and 153: deliberately perturbed the lights d
Page 154 and 155: Table 8-2 Summary of the test on pr
Page 156 and 157: Current Level on the investigator
Page 158 and 159: Chapter 9 System Implementation and
Page 160 and 161:
Figure 9-1 Floor plan of the small
Page 162 and 163:
Figure 9-3 System operation diagram
Page 164 and 165:
campus-wide lighting maintenance, w
Page 166 and 167:
message is addressed. The destinati
Page 168 and 169:
Both the actuation and the grouping
Page 170 and 171:
The construction or updating of the
Page 172 and 173:
determines if this message is for u
Page 174 and 175:
Figure 9-12 Lighting preset setting
Page 176 and 177:
Figure 9-13 Average hourly percent
Page 178 and 179:
9.4 Daylight Response The second ph
Page 180 and 181:
Furthermore, the structure allows t
Page 182 and 183:
Figure 9-16 Daylight harvesting tes
Page 184 and 185:
Figure 9-18 Sensor readings in the
Page 186 and 187:
then gradually dimmed. After reachi
Page 188 and 189:
Page 190 and 191:
Seven-occupant case with simulated
Page 192 and 193:
Page 194 and 195:
under significant daylight. Again,
Page 196 and 197:
newly calculated light settings may
Page 198 and 199:
Annual energy consumption = ( Numbe
Page 200 and 201:
Figure 9-30 Energy savings vs. payb
Page 202 and 203:
have partially contributed to the h
Page 204 and 205:
$40 per unit and the system achieve
Page 206 and 207:
performance of the current research
Page 208 and 209:
sensors. The research in [14] prese
Page 210 and 211:
Other than optimizing the energy co
Page 212 and 213:
lighting configuration in the offic
Page 214 and 215:
communications. The adaptive sensin
Page 216 and 217:
integration of the research system
Page 218 and 219:
will broaden the application to dif
Page 220 and 221:
system could be reallocated to oper
Page 222 and 223:
entities could be tremendously crit
Page 224 and 225:
[7] J. A. Veitch and G. R. Newsham,
Page 226 and 227:
[20] K. A. Karmel, High Performance
Page 228 and 229:
[34] P. Levis, S. Madden, J. Polast
Page 230 and 231:
International Workshop on Wireless
Page 232 and 233:
[57] LonMark International, "Fact S
Page 234 and 235:
[71] S. Sahni and X. Xu, "Algorithm
Page 236 and 237:
Proceedings of the 1st Internationa
Page 238 and 239:
[99] SPOT: Sensor Placement + Optim
Page 240 and 241:
[113] Advance Transformer Technical
Page 242 and 243:
A.2 Circuit Schematics of Photosens
Page 244 and 245:
A.4 Circuit Schematics of the Secon
Page 246 and 247:
Appendix B Human Subject Test B.1 C
Page 248 and 249:
(a) Sensor placement of subject No.
Page 250 and 251:
B.2 Comparison of System Performanc
Page 252 and 253:
B.3 Summary of the Responses from t
Page 254 and 255:
B.4 Human Subject Test Approval Let
Page 256 and 257:
B.5 Human Subject Test Protocol Nar
Page 258 and 259:
241
Page 260 and 261:
243
Page 262 and 263:
245
Page 264 and 265:
247
Page 266 and 267:
249
Page 268 and 269:
B.7 Human Subject Test Questionnair
Page 270 and 271:
253
Page 272 and 273:
B.8 Human Subject Test Interview Sc
Page 274 and 275:
Luminaire surface depreciation: 1.0
Page 276 and 277:
Table C-1 Daylight reception durati
Page 278:
At the rate of 9.62 cents per kWh a
show all

Wireless Sensor and Actuator Networks for Lighting Energy ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?