Lighting/HVAC interactions and their effects on annual and peak HVAC requirements in commercial buildings

Lighting measures is one effective strategy for reducing energy use in commercial buildings. Reductions in lighting energy have secondary effects on cooling/heating energy consumption and peak HVAC requirements; in general, they increase the heating and decrease cooling requirements of a building. Net change in a building`s annual and peak energy requirements, however, is difficult to quantify and depends on building characteristics, operating conditions, climate. This paper characterizes impacts of lighting/HVAC interactions on annual and peak heating/cooling requirements of prototypical US commercial buildings through computer simulations using DOE-2.1E building energy analysis program. Ten building types of two vintages and nine climates are chosen to represent the US commercial building stock. For each combination, a prototypical building is simulated with two lighting power densities, and resultant changes in heating and cooling loads are recorded. Simple concepts of Lighting Coincidence Factors are used to describe the observed interactions between lighting and HVAC requirements. (Coincidence Factor (CF) is ratio of changes in HVAC loads to those in lighting loads, where load is either annual or peak load). The paper presents tables of lighting CF for major building types and climates. These parameters can be used for regional or national cost/benefit analyses of lighting- related policies and utility DSM programs. Using Annual CFs and typical efficiencies for heating and cooling systems, net changes in space conditioning energy use from a lighting measure can be calculated. Similarly, Demand CFs can be used to estimate the changes in HVAC sizing, which can then be converted to changes in capital outlay using standard-design curves; or they can be used to estimate coincident peak reductions for the analysis of the utility`s avoided costs. Results from use of these tables are meaningful only when they involve a significantly large number of buildings