Case Studies in Lighting Efficiency Honeycomb Intelligent Lighting Controls Kenneth Seeton
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1 Case Studies in Lighting Efficiency Honeycomb Intelligent Lighting Controls Kenneth Seeton Wed, July 22, 2015
2 Project Scope and Savings Project location: NSM (Natural Science & Mathematics), ERC (Library) & LCH (LaCorte Hall) Completion date: December 15, 2014 Brief narrative: To bring wasted light out of the Honeycomb ceiling and down to the ground in a more efficient manner without creating places for birds to nest. To have better control of lights and be able to dim them down to a more cost effective lighting level while still keeping the area safe at 2 am. Project cost: $77,953 Estimated annual energy savings: 101,188 kwh Estimated annual cost savings: $12,648 electricity savings ROI: 4.24 years 2
3 A fixture did not currently exist that would meet all my criteria and so I finally found a vendor (MaxLite)that would think outside the box with me. We worked together to design a mounting plate that would hold a standard troffer fixture that could be mounted flush to the bottom of the ceiling. I again enlisted the aid of Professor Judy King and her students to count the existing lights and taught them how to do the energy savings calculations. While the students were doing their homework we installed 4 prototype 45w LED fixtures. Through the use of Enlighted smart controls I saw that we could operate the lights at 10% minimum and 50% maximum and have better light output then the old fixtures. In fact the light output by lowering the fixture out of the Honeycomb ceiling was so good that we skipped every other fixture and so put in half as many as we removed around the NSM building. We found that we had many extra fixtures so we were able to do all three buildings on campus with this same type of Honeycomb architecture style. In the end we replaced w u-tube fluorescent fixtures with w LED fixtures with Enlighted Smart programmable occupancy controls. The new lights are programed for 10% minimum (9watts) to 50% maximum (25watts) with a 1 min off delay when no occupancy. I used the students as my eyes and ears to check on the light levels and comfort of the areas and would talk to their class on a few occasions to get their feedback. In this way the students learned all aspects of a project and not just the design phase. Once again we have created a project that students can feel proud of and have pride in knowing they improved their University. 3
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11 Lighting is the Largest Controllable Load 11
12 Enlighted at a Glance + The Most Advanced Wireless Sensor Network for Commercial Real Estate + Lighting Energy Savings is the First Application + Lighting Justifies the Sensor Network and Brings Buildings into the Internet of Things + Lowest installed cost solution for meeting new buildings codes + IOT Applications built on top of the sensor network: HVAC Optimization, Real Estate Planning, Space Utilization, ADR, and many others Fortune 500 (200+ Total Clients, 600,000+ Connected Sensors,36 States, 8 Countries + Largest Networked Lighting Controls Company 12
13 Enlighted Building-Level Architecture (wireless) ROOM CONTROLLER Push control profiles on command Pull sensor data every 5 minutes No mesh point to point IEEE standard 2.4 GHz ISM spectrum AES-128 bit encryption 13
14 Zonal vs Granular Feature Area Zonal Granular Difference Daylight Limited Area All Areas No sacrifice of savings for first cost Occupancy Large Area Fine Grain Control Doesn t activate entire area for one user Facility Utilization Limited/No Data Complete Provides needed information for planning and operations User Control Not Possible Fixture by fixture PC, user friendly, password level Security Limited Data, Low Resolution Every 10 Feet (3m) In Development Traffic Flow Limited Data, Low Resolution Every 10 Feet (3m) Adjustable time base allows pattern Recognition HVAC Integration Additional Equipment Fine Grain High Density Usable data for facility manager and BMS via BACnet Intelligence Network Dependent Localized control and response Walk-thru logic for hallways, Soft edges in offices (Envelope) 14
15 Sensor Occupancy Dual Tech DPIR Motion Light/Logic Light Levels Daylight Source/Fixture Degradation Offset Thermal Thermal Distribution Airflow Patterns Inform BMS & HVAC via BACnet Local Microprocessor Eliminates Network Dependency Hardwired to Fixture Dependability Transceiver Capability Range Extension Dry, Damp and IP65 Multiple Optics High Bay, Pole, Office, Garage Push control profiles on command Pull sensor data every 5 minutes No mesh point to point IEEE standard 2.4 GHz ISM spectrum AES-128 bit encryption 15
16 Network Components Control Unit Normally Closed Relay Lights on with any problem Power Metering 0-10V Control Line LED, Fluorescent, HID, Plasma, OLED Gateway 250+ Sensors 300ft(100m)Range POE Powered Wireless Switch Dim Brighten Scenes Automatic Energy Manager Sensors Continuous Local Backup Backup to network share Future Cloud Connections 16
17 Features & Benefits Data and analytics for HVAC control and space planning / utilization. ADR. Daylight Harvesting. Temperature. Occupancy. BACnet. Plug Load Monitoring. No Software to install. 17
18 Realtime Status of Each Fixture NSM 2 nd floor 18
19 Realtime Status of Each Fixture LCH 1 st Floor 19
20 ERC 1 st Floor 20
21 Realtime Status of Each Fixture 21
22 Realtime Status of Each Fixture 22
23 Profile Management 23
24 Honeycomb 10_50 Sun Profile 24
25 Demand Response 25
26 Reporting 26
27 Energy Usage and Savings by Measure Reduction Through Task Tuning Net Consumption Daylight Harvesting Occupancy Reduction 27
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29 Energy Consumption Report 29
30 Consumption by Space Type 30
31 Fixture Outage Reporting 31
32 Time of Use Pricing Model for ADR 32
33 Commissioning X 33
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36 Fixtures Discovered and Tested Pending Strobing and Placement 36
37 Occupancy and Utilization 37
38 Motion & Occupancy Data Analysis 38
39 Space Utilization: Occupancy Maps 0-20% 20-40% 40-60% 60-80% % Areas Stations/Rms SF Stations/Rms SF Stations/Rms SF Stations/Rms SF Stations/Rms SF Private Offices , Open Areas , ,920 Sm. Conference Rooms Lg. Conference Rooms Social Utility Total Stations/Rms SF 33 3, , , , , ,939 24% 29% 9% 9% 13% 12% 32% 30% 22% 19% Occupancy heat map by area highlights specific areas that are underutilized and areas that are heavily utilized. 39
40 Time Series Analysis Makes It Easy to See Broad Patterns & Predict Future Occupancy
41 Optimizing HVAC with Occupancy Data HVAC Advisor uses occupancy data collected from Enlighted sensors to: Create temperature set-backs and airflow recommendations Provide recommendations to the BMS via Bacnet» BMS always remains in control of system! Set-back recommendations vary by time of day and weekday/weekend status Airflow depends on bands of space utilization (Min, Low, Medium, and High) Set-up is done easily through HVAC Advisor Application 41
42 Optimizing HVAC with Occupancy Data Pervasive temperature sensors describe hot and cold zones in the building Pervasive occupancy sensors indicate setback zones for active duty cycling 42
43 3 = unoccupied 4 = occupied
44 Possible savings from HVAC only During February 2015, EcoVox building analytics showed that the 15 VAV units with Enlighted occupancy controls averaged 152 hours each with flow reduced by 161 cfm from normal. This accounts for a 2.1% reduction of the total airflow through air handlers 2 and 3, saving 720 kwh. There was also a savings of approximately 80 therms of natural gas, due to cooling saved at the chiller level. Welch Hall has a total of 185 VAV units. 185 / 15 = kWh * = 8,878 kwh * 12 months = 106,531 kwh per year 80 therms * = 986 therms * 12 months = 11,837 therms per year
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48 Contact info Kenny Seeton Manager Central Plant / Energy Manager California State University Dominguez Hills kseeton@csudh.edu Erica Plastino enlighted Director of Sales, Southwest Region m o Mike Xenakis enlighted Vice President, Education Sales e: mike.xenakis@enlightedinc.com c: Benecia Ave Sunnyvale, CA David Wyatt MaxLite VP Sales, West Cell
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