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Decarbonization goals in the United States electricity sector are increasing the levels of renewable energy generation in the electricity supply system, and are driving increased attention to building electrification, which will increase the magnitude and shift the timing of the electricity system peak. These changes are motivating new approaches to coordinate building electricity demand with low-carbon renewable generation, elevating the importance of demand flexibility (DF) in buildings and the need to quantify the temporal impacts of DF. In this paper, we first characterize the hourly predictive accuracy of six commonly used baseline models in an application context of quantifying building-level load shift. Our analysis revealed insights such as hours of the day (afternoons), periods of the week (weekends), and seasons (summer) that were predicted with more accuracy than other time periods. In addition, the analysis showed tendencies toward overprediction or underprediction of load. Secondly, we provide the first published investigation of baseline erosion from repeated dispatch of building load shifting. We observed that as the baseline period is pushed back further from the prediction day, the distribution of errors across baseline model predictions increases, with notable inflection points near the three-week erosion point for two of the three models. [ABSTRACT FROM AUTHOR]

Abstract Convenience stores are known to have higher Energy Use Intensities (EUIs) than most other commercial building types. However, convenience store energy performance analyses have not been systematically investigated. Moreover, current national convenience store benchmarks are inconsistent from one data base to another due to lack of relevant energy data. This paper assesses the energy performance of more than five hundred convenience stores in the same fleet in Eastern United States. The investigation aims to establish benchmarks for convenience stores with and without gasoline pumping stations. The main factors influencing the actual convenience store building energy use were determined. Multiple regression models were developed to find relationships between annual energy consumption per unit area and gross floor area, customer transaction count, building operating year, etc. The statistically characterized results are meant to serve as a reference data set in comparing the whole-building energy performance index for buildings of similar functionality. The statistical correlation analyses can strengthen the robust prediction of energy performance in convenience stores, enabling proper assessment of energy conservation measurements (ECMs) for convenience store operations, as well as guiding additional such energy performance studies. [ABSTRACT FROM AUTHOR]

In the US, building sector consumes approximately 41% of all U.S. primary energy and 70% of all generated electricity. Office building uses the largest percentage of primary and derived energy in the commercial buildings sector. Therefore, energy saving is the primary target of building renovation and equipment retrofit. To estimate energy savings after a renovation or equipment retrofit, measurement and verification (M&V) must be conducted based on energy use models or benchmark tools to track and assess savings. Although some methods and modeling tools are applied more often, there is no well-accepted model formulation methodology and some methods have high uncertainty. This paper discusses a method to formulate the energy use model as an inverse regression model via an advanced and robust high-dimensional data analysis method. According to the inverse regression model, independent variables determined to be most influential to the energy consumption should be metered prior to building retrofit or audit. To select the most influential variables, this research considers a comprehensive set of potential key variables to avoid underspecified model issue. The models established by this method are observed to have great power in predicting the building energy consumption. More importantly, through the variable selection procedure, the method identifies key variables that should be monitored to continuously improve the building energy performance. A simulation study and a case study are presented to show the effectiveness of the new approach. [ABSTRACT FROM AUTHOR]

Utility incentive programs are an important channel to support the deployment of energy efficiency in buildings. To date, these programs have largely been limited to single-component strategies. However, many utilities are now motivated to identify and develop multi-component system retrofits to achieve deeper energy savings, which are essential to achieving broader energy and greenhouse gas reduction goals in the buildings sector. In this paper we present the energy savings, demand reductions, and cost-effectiveness of 16 systems retrofit packages in six utility regions in the United States. These results are being used by these utilities to inform and develop incentive programs for systems retrofits. Our analysis shows that packages with proven lighting and HVAC measures can provide 5–22% whole building annual energy savings, and 13–22% annual energy costs savings, using utility incentive program baselines (code and existing building). The packages are reasonably cost effective for replace-on-burnout but generally not for a retrofit scenario prior to end of equipment life. Demand response can increase both the energy savings and energy cost savings, further improving the cost effectiveness of these packages. We analyzed the impact of using existing building vs. code baselines for calculating savings, showing that the choice of baseline in developing utility incentive programs has a substantial impact on the attributable energy savings to a program, with significant implications for the overall viability of a program (generally savings against existing building condition are higher and improve project and program cost-effectiveness). [ABSTRACT FROM AUTHOR]

• A comprehensive analysis of data from commercial buildings in United States to identify operational problems and opportunities. • These opportunities were not strongly correlated with building vintage, size, or building type, but were reflective of how the buildings are operated. • This analysis showed that opportunities to improve building operations exist in almost every building. • There was wide variation in whole building energy savings, ranging from 0 to 50% and 0 to 18 $/m2 with median percent annual whole building savings of 12% and median normalized annual cost savings of $1.75/m2. In the United States, as much as 30% of the 19 EJ that commercial buildings consume is considered excess. Much of the excess energy is due to the inability to manage building operations efficiently. Because almost 20% of the total primary energy consumption is associated with commercial buildings, significant energy reductions in this sector are needed to mitigate climate change. Therefore, many cities and states are mandating periodic "tune-ups" of these buildings to eliminate excess energy consumption. Although the benefits of tune-ups and retro -commissioning are clear, focusing these mandates to look for specific opportunities has been a challenge because of the lack of studies that document the prevalence of opportunities. Therefore, we analyzed building automation system data from 151 buildings across the United States to document common operational problems and opportunities to improve building operations. This analysis showed that opportunities to improve building operations exist in almost every building. These opportunities were not strongly correlated with building vintage or size, but were reflective of how the buildings are operated. The prevalence of the top 20 opportunities ranged between 74% and 23%, with 40% of these associated with air-handling units. The rest of the opportunities are associated with schedules, chilled and hot-water distribution, and zone controls. Of the 151 buildings, 69 of them implemented corrective actions of some or all opportunities that were identified. Implementation varied across the Re-tuning categories, with 60% for schedule opportunities, 50% for zone opportunities, over 40% for the air-handling unit and hot-water opportunities, and 35% of the chilled-water opportunities. There was wide variation in whole building energy savings, ranging from 0 to 50% and 0 to 18 $/m2 with median percent annual whole building savings of 12% and median normalized annual cost savings of $1.75/m2. In addition to documenting these key findings, the paper provides a list of opportunities that can be automatically and continuously identified and corrected and offers a list of those opportunities that should be the focus of the mandates. [ABSTRACT FROM AUTHOR]