A Multi-Criteria Ranking Approach for Energy Efficiency Ranking of a Cluster of Commercial Buildings

Abstract

Buildings are responsible for 30-40% of global energy consumption, making them prime candidates for improvements in energy efficiency. To this end, states across the U.S. are actively implementing building performance standards to regulate the operations of the existing building stock. However, when multiple buildings are being considered for energy performance upgrades, it can be difficult for decision-makers to determine which facility to prioritize. This study presents the development of a multi-criteria ranking tool capable of facilitating rapid, reliable, and efficient virtual energy audits. The ranking generated by this tool can be used to conduct performance analyses and identify facilities with suboptimal performance. The proposed ranking of the cluster of buildings can be used to make decisions based on key metrics such as energy use intensity (EUI), net total CO2e emissions per square foot, and dollar-saving potential per square foot. By assigning different weights based on the performance of facilities relative to energy and greenhouse gas emission benchmarks from the Commercial Building Energy Consumption Survey (CBECS) and the local/regional mandates as applicable, a cumulative score is developed for a portfolio of buildings. For the case study analyzed here, the building portfolio's end-use energy data resulted in a minimum annual average energy savings potential of 1,522 terajoules (TJ) (1,442,951 MMBtu), representing a possible 45% reduction in energy consumption. This translates to approximately 567 megajoules per square meter (MJ/sq. m.) (50 kBtu/sq. ft.) over a six-year analysis period (2018-2023). As a result, this average annual energy reduction would lead to a yearly decrease in greenhouse gas (GHG) emissions of 115,249 metric tons of CO2e, also a 45% reduction, equivalent to roughly 43 kilograms per square meter (kg/sq. m.) (4 kg/sq. ft.) over the same six-year analysis period (2018-2023). Furthermore, the potential annual average dollar savings is estimated at USD 26 million [~USD 10/sq. m. (~USD 1/sq. ft.)], reflecting a 40% cost reduction. Multi-criteria ranking models, such as the one presented here, are essential for identifying and prioritizing subpar building performance, facilitating targeted energy improvements, and allocating resources toward sustainability goals.