*4.2. Building Energy Use of Manhattan Simulated by UBEM*

#### 4.2.1. UBEM Input

To run the UBEM, to quantify the building energy use of Manhattan, NYC, several pieces of important information need to be put into the model. In this study, most parameters were collected from the technical report of the US Department of Energy Reference Building Models of the National Building Stock provided by the National Renewable Energy Laboratory, to represent a typical performance of the different building types [48]. In general, the model input could be listed as program, form, fabric, and equipment (see Table 1.). Occupancy is one of the most important parameters in the model; it can be collected from different sources, such as CBECS, RECS, and ASHRAE. In this study, the occupancy rates for all the reference building models were collected from Standard 62.2 from ASHRAE. Table 2 lists the occupancy rate by space types, and most buildings are composed of one or more of the space types listed below. Ventilation/Outside air (OA) requirements are included in Table 3 by space types, and they are also collected using Standard 62 from ASHRAE. As limited information is available for old buildings, this study assumes all reference buildings are having the same ventilation requirements, and a reevaluation is expected when more information is available in the future. The occupancy schedule was applied with Standard 90.1 from ASHRAE. Different building types have quite different schedules. For instance, a restaurant may have a kitchen electric (gas) equipment schedule and dining area schedule. A hospital has an administrative area schedule, ER schedule, lab schedule, inpatient area schedule, and outpatient schedule. Residential buildings have a kitchen schedule, dining room schedule, and bedroom schedule. In general, some schedules are included in most building models, such as a building occupancy schedule, building the electric equipment schedule, and the HAVC system schedule (including both cooling and heating systems). All the occupancy schedules can also be divided as a weekday schedule, weekend schedule, and holiday schedule. Figure 5 shows the general weekday building occupancy schedules of the different building types. Due to the different functions they have, quite different hourly patterns could be found. The model input is the first and one of the most important steps for establishing the building energy-use model; more input parameter information could also be found from the technical report of the US Department of Energy Reference Building Models of the National Building Stock provided by the National Renewable Energy Laboratory [48].

**Table 1.** The general model input information [48].





**Table 3.** Outside air requirements (ventilation) [48].

**Figure 5.** Building weekday hourly occupancy schedules.

#### 4.2.2. UBEM Calibration

With the established UBEM model, the hourly energy-use intensity of all the designed building prototypes could be calculated. To further apply the simulated results for the final building energy-use calculation, the model calibration needs to be implemented first. In this study, the energy-use reference data from RECS and CBECS, including electricity and gas consumption data, were collected from the EIA for model calibration. RECS and CBECS are the only two nationwide statistical information sets on building energy consumption. RECS and CBECS data are collected in two phases: Phase 1 is the building survey, which collects basic information about the buildings, such as structural characteristics, building size, building type, and energy-use equipment; Phase 2 is the energy consumption survey that collects, through a website or mail, the basic energy-use information, such as electricity consumption, gas consumption, and heating oil consumption. The RECS and CBECS data are widely used by building managers, energy modelers, government leaders, and the Energy Star program. There are more than 1000 itemized information about buildings and their associated energy-use information included in the RECS and CBECS data sets. Selected important building and energy-use information is listed in Table 4. For instance, primary and more specific building activity delivers information about building types; construction year could help to separate the reference data into two categories, pre-1980 built buildings and post-1980 built buildings; the number of floors and building footprint helps the calculation of the referenced energy-use intensity; and electricity and gas consumption deliver direct information about the building's energy-use amount. With the all-important building and corresponding energy-use information listed in Table 4, the referenced building energy-use intensity for all 34 building types was calculated and used for further model calibration.


**Table 4.** Building and energy-use information included in RECS and CBECS.

To minimize the discrepancy between the modeled energy-use intensity and actual energy-use intensity, several important building parameters, such as the set point, occupancy schedule, usage pattern, etc., have all been optimized. Specifically, the setpoint of the cooling and heating system is very essential in modeling building energy use. Different building types may have a significantly varied cooling and heating demand. In this study, the minimum acceptable room temperature and the optimum room temperature in the summer from the engineering toolbox [49] were collected and used as reference data for adjusting the cooling and heating set point of the HVAC system in the model calibration (see Table 5). Table 5 shows that the accepted room temperature in winter for the school (classroom or lecture room) is 20 ◦C; the hotel is 21 ◦C; the office is 20 ◦C; the restaurant is 18 ◦C; and warehouse is 16 ◦C. Moreover, the general optimum room temperature in the summer is between 20 ◦C and 22 ◦C for most rooms. Therefore, when the calibration is conducted, the cooling and heating set point of the HVAC system has to be set with the consideration of the recommended room temperatures. Moreover, the occupancy schedule is another very important parameter. Business buildings, school buildings, and residential buildings may have different schedules. People may have different timing for getting up, leaving home, starting work or study, going back home, or going to bed. Therefore, different schedules must be considered for different buildings. In this study, the most optimum building occupancy schedule (Figure 5) recommended by the technical report of the US Department of Energy Reference Building Models of the National Building Stock provided by the National Renewable Energy Laboratory was applied. Furthermore, schools may have spring, summer, fall, and winter breaks, which result in lower energy consumption. They all must be considered in the schedule section during model calibration. The primary school and secondary school operating schedules were collected from the Department of Education in New York City [50]. It shows the spring semester starts in late January and ends in late June, and the fall semester starts in early September and ends in late December. Therefore, the summer break (July and August) and spring break (January) were set as time points of limited operation with relatively low energy consumption [50].


**Table 5.** The minimum acceptable room temperature in the winter and the optimal room temperature in the summer of different room types [49].

In addition, both electricity and gas consumption are coming from different components, such as lighting, cooking, heating, cooling, refrigerator, machines in the lab, machines in the office, etc. In general, one or more listed lighting, electric, and gas equipment are included in each specific building type (see Table 6). For instance, schools may include lighting, electric equipment, and gas equipment for a dorm, classroom, lab, cafeteria, library, and auditorium. The office only has office lights and corridor lights in lighting, electric equipment for the office, meeting room, and employee lounge, and no gas equipment. Residential buildings include more specific equipment, such as a refrigerator, microwave, laundry machine, TV set, stove for cooking, and lighting in different rooms. In this study, the reference data collected from the Pacific Northwest National Lab were used for updating all models for model calibration purposes [51]. In summary, energy plus has hundreds of parameters. On the one hand, it is impossible for us to make the change for all parameters; on the other hand, not all reference data are available to be used for the calibration. Therefore, the goal of the model calibration is to minimize the discrepancy between the modeled results and the referenced number with the available reference information.

**Table 6.** Selected lighting, electric, and gas equipment inside buildings.


Figure 6 indicates that, after calibration, the difference between the simulated electricity- and gas-use intensity and the actual energy-use intensity were all reaching the evaluation criteria (within ± 10%). Therefore, all the proposed energy-use intensity models are qualified to estimate the actual energy-use intensity of all the building prototypes. The annual energy-use intensity included in Figure 6 shows that for commercial buildings, the quick-service restaurant has the highest energy-use intensity for electricity consumption and the full-service restaurant has the highest energy-use intensity for gas consumption. Moreover, the warehouse has the lowest electricity- and gas-use intensity. In terms of residential buildings, the multi-family residences have a much higher electricity- and gas-use intensity than single-family residences. After model calibration, the modeled total electricity

and gas consumption in Manhattan was also compared with the real energy-use information from the City of New York, to make sure the modeled energy consumption is reasonable.

**Figure 6.** Comparison of the modeled and referenced energy-use intensity for residential and commercial buildings.

4.2.3. The Spatial Distribution of Energy Consumption in Manhattan

Figure 7 shows the spatial distribution patterns of energy-use intensity in Manhattan, and quite different spatial patterns could be found between electricity-use intensity and gas-use intensity. Specifically, the highest electricity-use intensity is located in the center and southern corner of

Manhattan, which are mainly composed of large offices with an annual electricity-use intensity over 200 kWh/m2. From the central area to the outlier of Manhattan, the electricity-use intensity drops significantly to around 100 kWh/m2, or even much lower as most buildings clustered here are medium offices, small offices, primary schools, secondary schools, retail stores, single-family houses, and midrise apartments. Moreover, some buildings, such as quick-service restaurants, full-service restaurants, and supermarkets, are dispersed in Manhattan with a much higher electricity-use intensity, around 500 kWh/m2. In contrast, quite different gas-use intensity patterns could be found in Manhattan. A very similar gas-use intensity could be found throughout Manhattan. Manhattan is very cold in the winter, gas is majorly used for heating purposes in the winter, and most buildings have a very similar gas-use intensity. Only some buildings located in the center and southern corner of Manhattan show a relatively lower gas-use intensity, which is mainly composed of large offices built after 1980 with improved energy-use efficiency. There are also some red spots with a high gas-use intensity dispersed in Manhattan, which is mainly composed of restaurants. With the modeled energy-use intensity of all the designed building prototypes, the building energy consumption could be quantified for all buildings in Manhattan through combing the corresponding building floor areas and number of floors information. The modeled building energy use is very straightforward as the total energy use was calculated for each building, and it is highly associated with building height. The energy use of Manhattan is progressively decreasing from the urban core, which is mainly covered by commercial buildings such as offices, hotels, and retail stores, to suburban areas, which are mainly composed of residential buildings (mostly apartments, single-family, and multi-family houses).

**Figure 7.** Modeled annual building electricity- and gas-use intensity in Manhattan, NYC, in 2012.
