Showing papers on "Street light published in 2005"

Development of a Web-based Emissions Reduction Calculator for Street Light and Traffic Light Retrofits

Abstract: Four areas, involving 16 counties, in Texas have been designated by the United States Environmental Protection Agency (EPA) as non-attainment areas because ozone levels exceed the National Ambient Air Quality Standard (NAAQS) maximum allowable limits. These areas face severe sanctions if attainment is not reached by 2007. Four additional areas in the state are also approaching national ozone limits (i.e., affected areas). In 2001, the Texas State Legislature formulated and passed the Texas Emissions Reduction Plan (TERP), to reduce ozone levels by encouraging the reduction of emissions of NOx by sources that are currently not regulated by the state. Ozone results from photochemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) in the presence of sunlight. An important part of this legislation is the State’s energy efficiency program, which includes reductions in energy use and demand that are associated with the adoption of the 2000 International Energy Conservation Code (IECC 2000), including the 2001 Supplement (IECC 2001) which represents one of the first times that the EPA is considering State Implementation Plan (SIP) credits from energy conservation and renewable energy– an important new development for building efficiency professionals, since this could pave the way for documented procedures for financial reimbursement for building energy conservation from the state’s emissions reductions funding. This paper presents the procedures that have been developed and used to calculate the electricity savings from street and traffic lighting retrofits, which includes the use of the ASHRAE Inverse Model Toolkit (IMT) for weather normalization, a peak-extractor for calculating peak-day electricity savings, and the use of the EPA’s Emissions and Generations Resource Integrated Database (eGRID) for calculating NOx emissions reductions for the electric utility provide associated with the user. INTRODUCTION In 2001, the Texas State Legislature formulated and passed Senate Bill 5 to further reduce ozone levels by encouraging the reduction of emissions of NOx by sources that are currently not regulated by the state, including area sources (e.g., residential emissions), on-road mobile sources (e.g., all types of motor vehicles), and non-road mobile sources (e.g., aircraft, locomotives, etc.). An important part of this legislation is the evaluation of the State’s new energy efficiency programs, which includes reductions in energy use and demand that are associated with specific utility-based energy conservation measures, and implementation of the International Energy Conservation Code (IECC), published in 2000 as amended by the 2001 Supplement (IECC 2000; 2001). In 2001 thirty-eight counties in Texas were designated by the EPA as either non-attainment or affected areas. In 2003, three additional counties were classified as affected counties, bringing the total to forty-one counties (sixteen non-attainment and twenty-five affected counties) out of the 254 counties in Texas. In many communities, street lights and traffic lights represent one of the largest categories of electricity used by a city. By retrofitting the street lights with energy efficient lamps such as high pressure sodium and metal halide and traffic lights with light-emitting diode (LED) traffic signals, a city 1 In the 2003 and 2005 Texas State legislative sessions, the emissions reductions legislation in Senate Bill 5 was modified by House bill 3235, and House bill 1365 (2003), and House bill 2129 and 965. In general, this new legislation strengthens the previous legislation, and did not reduce the stringency of the building code or the reporting of the emissions reductions. 2 The sixteen counties designated as non-attainment counties include: Brazoria, Chambers, Collin, Dallas, Denton, El Paso, Fort Bend, Hardin, Harris, Jefferson, Galveston, Liberty, Montgomery, Orange, Tarrant, and Waller counties. The twenty-two counties designated as affected counties include: Bastrop, Bexar, Caldwell, Comal, Ellis, Gregg, Guadalupe, Harrison, Hays, Johnson, Kaufman, Nueces, Parker, Rockwall, Rusk, San Patricio, Smith, Travis, Upshur, Victoria, Williamson, and Wilson County. 3 These counties are Henderson, Hood and Hunt counties in the Dallas – Fort Worth area. ESL-IC-05-10-29 Proceedings of the Fifth International Conference for Enhanced Building Operations, Pittsburgh, Pennsylvania, October 11-13, 2005 2 cannot only save energy and money, but can also reduce greenhouse gas emissions and reduce light pollution. However, many municipalities are not aware of the available choices in technology and energy and emissions savings for street light and traffic retrofits, nor are they aware of procedures for calculating the length of day, or for calculating the emissions from electricity savings, which is often required by environmental decision makers. Therefore, this paper presents the procedures and tools that have been developed and used to calculate the electricity savings from street and traffic lighting retrofits, which includes the use of the ASHRAE Inverse Model Toolkit (IMT) for weather normalization, a peak-extractor for calculating peak-day electricity savings from monthly utility bills, and the use of the EPA’s Emissions and Generations Resource Integrated Database (eGRID) for calculating NOx emissions reductions for the electric utility provide associated with the user. METHODOLOGY The methodology that was developed for street lights and traffic lights includes two distinct paths for calculating energy savings, one path for users that have pre-retrofit and post-retrofit utility bills (i.e., the utility billing mode), and a second path for users that want to calculate the lamp-by-lamp savings from a group of lamps they intend on replacing (i.e., the design mode). In the utility bill analysis mode, a linear regression is performed on the pre-retrofit and postretrofit monthly utility data for street lights and traffic lights using the ASHRAE Inverse Model Toolkit (Haberl et al. 2003; Kissock et al. 2003). ASHRAE’s IMT is a FORTRAN 90 application for calculating linear, change-point linear, variable-based degree-day, multi-linear, and combined regression models. The development of the IMT was sponsored by ASHRAE research project 1050-RP under the guidance of Technical Committee 4.7 Energy Calculations. The coefficients from this analysis are then used to normalize the data to the 1999 baseline year using the weather data obtained from National Oceanic & Atmospheric Administration (NOAA)’s National Weather Service (NWS) from a nearby weather station (NOAA 1993). The normalized annual energy savings are then calculated for the 1999 baseline year. Using these same coefficients, the peak daily consumption is extracted, which is then used to calculate the peak savings during the Ozone Episode Peak day for 1999. In the design mode the energy and emissions savings are calculated based on the specific information the user provides about the lamp type, lamp code, wattage, and number of lamps for both pre-retrofit and post-retrofit lamps. The annual energy savings are then calculated for the 1999 baseline year, and the peak daily consumption is extracted, which is then used to calculate the peak savings during the Ozone Episode Peak day for 1999. Street Lighting Analysis: Utility Bill Mode In the utility bill analysis mode for street lights, first, the monthly energy consumption bill is divided by the number of days in each month to obtain the average daily energy consumption for each billing period (i.e., kWh/day). Second, the average daily temperature data for each billing period is calculated from the nearest NWS station daily temperature data. The data set containing the average daily temperature and average daily energy consumption for each month is then analyzed with the IMT to determine a weather normalized energy consumption as shown in Figure 1, which also shows the coefficients for the regression model for this street light example. The daily energy consumption predicted by applying the 1999 daily average temperature data from NOAA into the developed two-parameter regression model. Energy Consumption of Street Lights 0 2 4 6 8 10 12 14 16 18

A Study on Efficient On-line/Off-line Street Light Facility Management Database System

Abstract: This paper concerns developing a real time on-line light facility management system using internet and building a database system for control box and street light. Also, we designed the system to minimize the disparity with the conventional management system by referring to an old management ledger format. Thus, the proposed method may enable the system manager to administer the light facility efficiently and to reduce manpower and maintenance cost.