Evaluating the energy impact potential of energy efficiency measures for retrofit applications:A case study with U.S.medium office buildings

Quantifying the energy savings of various energy efficiency measures(EEMs)for an energy retrofit project often necessitates an energy audit and detailed whole building energy modeling to evaluate the EEMs;however,this is often cost-prohibitive for small and medium buildings.In order to provide a defined guideline for projects with assumed common baseline characteristics,this paper applies a sensitivity analysis method to evaluate the impact of individual EEMs and groups these into packages to produce deep energy savings for a sample prototype medium office building across 15 climate zones in the United States.We start with one baseline model for each climate zone and nine candidate EEMs with a range of efficiency levels for each EEM.Three energy performance indicators(EPIs)are defined,which are annual electricity use intensity,annual natural gas use intensity,and annual energy cost.Then,a Standard Regression Coefficient(SRC)sensitivity analysis method is applied to determine the sensitivity of each EEM with respect to the three EPIs,and the relative sensitivity of all EEMs are calculated to evaluate their energy impacts.For the selected range of efficiency levels,the results indicate that the EEMs with higher energy impacts(i.e.,higher sensitivity)in most climate zones are high-performance windows,reduced interior lighting power,and reduced interior plug and process loads.However,the sensitivity of the EEMs also vary by climate zone and EPI;for example,improved opaque envelope insulation and efficiency of cooling and heating systems are found to have a high energy impact in cold and hot climates.

An Analysis of Energy and Environment Efficiency of China＇s Iron and Steel Industry

Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.