1、Adam Hirsch and Shanti Pless are engineers in the commercial building group at the National Renewable Energy Laboratory, Golden, CO. David Okada and Porus Antia are engineers at Stantec Engineering, San Francisco, CA. The Role of Modeling When Designing for Absolute Energy Use Intensity Requirements
2、 in a Design-Build Framework Adam Hirsch, PhD David Okada, PE Shanti Pless Porus Antia ASHRAE Member ASHRAE Member ASHRAE Member ASHRAE Member ABSTRACT The Research Support Facilities (RSF) building at the National Renewable Energy Laboratory is a 220,000 square foot office building designed to hold
3、 822 occupants, to use 35.1 kBTU/sf/yr, to use half the energy of an equivalent minimally code-compliant building, and to produce as much renewable energy as it consumes on an annual basis. These energy goals and their substantiation through simulation were explicitly included in the projects fixed
4、firm price design-build contract. The energy model was required to be repeatedly updated during the delivery process to match design documents as well as the final building as it was built to the greatest degree practical. Computer modeling played a key role in diagnosing the energy impact of buildi
5、ng program and design decisions throughout the design process and in verifying that the contractual energy goals would be met within the specified budget. The main tool was a whole building energy simulation program. Other models were used as needed to provide more detail or to complement the whole
6、building simulation tool as required by the delivery schedule, including tools to calculate: thermal bridging, daylighting, natural ventilation, data center energy consumption, transpired solar collectors, thermal storage in the buildings crawlspace, and electricity generation by photovoltaic panels
7、. Results from these specialized models were either fed back into the main whole building simulation tool or used to post-process model output to provide the most accurate possible annual simulations. This paper details the models used in the design process and how they informed important program an
8、d design decisions on the path from preliminary design to the completed building. INTRODUCTION The National Renewable Energy Laboratorys (NREL) mission is to advance the U.S. Department of Energys and the nations goals in the areas of energy security, environmental quality, and economic vitality. Fr
9、om the beginning, it was recognized that the new Research Support Facilities (RSF) building on the NREL campus represented a unique opportunity to demonstrate the state of the art in terms of energy efficient, cost-effective, commercial office design and operation. Today, buildings use roughly 39% o
10、f total U.S. energy consumption (22% residential, 18% non-residential), with energy consumption in this sector projected to grow by almost 30% in the next two decades. The RSF is intended to demonstrate that significant gains in energy efficiency can be realized in non-residential buildings today wi
11、th existing technologies in a cost-effective manner if careful attention is paid to project energy goals, the building delivery process, and integrative building design. The purpose of this paper is to delve into the details of how computer simulation tools were used to help design the RSF from the
12、outset of the project and what capabilities the project required of those tools. It is also intended to present a portrait of how setting an absolute whole building energy consumption target changes the role of energy modeling in the design process. LV-11-C048398 ASHRAE Transactions2011. American So
13、ciety of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in ASHRAE Transactions, Volume 117, Part 1. For personal use only. Additional reproduction, distribution, or transmission in either print or digital form is not permitted without ASHRAES prior written pe
14、rmission.PROJECT OVERVIEW The RSF project contains several novel features related to the delivery model, team structure, and request for proposals (RFP) that require description to provide context for how energy modeling was used in the design process. Delivery Model It was decided early on that in
15、order to deliver the RSF, with its challenging performance requirements, on time and on budget, a traditional design-bid-build procurement process would not suffice. Rather, a performance-based “Best Value Design-Build/Fixed Price with Award Fee” delivery approach Post, 2010 was pursued in order to
16、encourage innovation; reduce the building owners risk; speed construction and delivery; control costs; make optimal use of team members expertise; and establish measurable success criteria. The RSF procurement strategy provides an important context for understanding the RSF design process and the us
17、e of energy modeling tools in that process. By hiring a design-build team, NREL encouraged the formation of an integrated design process comprising architects, engineers, and builders. This arrangement resulted in an iterative pattern between architects and engineers with detailed computer simulatio
18、ns used to assess whether the building design as it evolved would meet the performance requirements of the owner. In addition, the arrangement put the onus on the owner to clearly define the scope and goals of the project in the project RFP and then allow the creativity of the design-build team to f
19、ind solutions to meet those goals. Having specific end-use and whole building energy balance goals necessitated that energy modeling be included in the design process from the very beginning. The firm fixed budget for all work (conceptual design, preliminary design, final design, and construction) o
20、f $64 million, formulated by the U.S. Department of Energy, required that cost modeling be given as much emphasis as the energy modeling. Project Objectives In the conceptual documents in the original request for proposals (dated February 6, 2008), the project objectives were prioritized into three
21、groups: Mission Critical, Highly Desirable, and If Possible. Competing design-build teams were judged based on their ability to meet as many of the goals as possible while meeting the overall budget constraint and a total floor area of 220,000 ft2. Here we only include a subset of goals related dire
22、ctly to energy modeling and the low energy design process: 1. Mission Critical a. LEED Platinum Designation b. Energy Star Appliances, unless other system outperforms 2. Highly Desirable a. 800 Staff Capacity (later adjusted to 822) b. 35.1 kBTU/sf/year1c. Measurable 50% plus energy savings versus A
23、SHRAE 90.1-2004 3. If Possible a. Net Zero/Design approach b. LEEDPlatinum Plus c. Exceed 50% savings over ASHRAE baseline The absolute site energy consumption, net zero energy balance, and LEED Platinum goals in particular influenced the modeling tools and design process used in the project, as des
24、cribed below. The RFP also specified parameters such as temperature and humidity setpoints, night setback, maximum U-value of windows, and compliance with ASHRAE 55 that 1Absolute energy goals of 25, 32, and 35.1 kBTU/sf/yr all appear at certain points in the project documents; 25 kBTU/sf/yr assumes
25、 650 occupants and data center energy use prorated to reflect that only a portion of the data center services are consumed in the RSF; 32 assumes 822 occupants and prorated data center energy; 35.1 includes the entire data center energy consumption. 2011 ASHRAE 399have energy impacts. Energy Goal Se
26、tting The absolute energy consumption target for the RSF project was chosen based on analysis done as part of a sector-wide energy efficiency modeling study Griffith et al., 2006. As part of that study, energy models of all the buildings in the 2003 Commercial Building Energy Consumption Survey (CBE
27、CS) were created in EnergyPlus. These models were then modified to make them minimally comply with ANSI/ASHRAE/IESNA Standard 90.1-2004 requirements. Tables containing these simulation results are available online2for use by the industry at large to assist energy goal-setting. An absolute energy goa
28、l for the RSF project was chosen corresponding to half the average energy use of the simulated office/professional buildings in ASHRAE climate zone 5B which contains Golden, Colorado. This absolute energy use goal was in line with the measured performance of several high performance office buildings
29、 analyzed in detail by the Commercial Buildings group at NREL Torcellini et al., 2006. Further feasibility studies carried out in 2007 in the NREL Commercial Buildings Group indicated that this target should be achievable in the Denver area for an office building with the RSF program if special atte
30、ntion were paid to: optimizing glazing area to maximize daylighting yet minimize thermal losses; stretching the building along the E-W axis to increase the daylit fraction; and minimizing plug/process loads. The modeling study used NREL design optimization software called Opt-E-plus to explore desig
31、n options that could lower end-use energy consumption. Opt-E-Plus modeling begins with an initial baseline EnergyPlus energy model then systematically alters the design features of the building, at each stage selecting the most cost-effective energy saving design options. MODELING IN CONCEPTUAL AND
32、SCHEMATIC DESIGN PHASES The design-build team selected to work on the RSF performed a great deal of energy modeling leading up to the submission of their design competition proposal. The MEP engineers on the project conducted early feasibility studies of their own to assess whether the absolute ener
33、gy goal set in the RFP was realistic. Even before the internal design-build charrettes began, initial model calculations stressed the importance of daylighting and natural ventilation. The building form quickly came to reflect these strategies, with two 60-ft wide office wings, attached by central c
34、ore of conference-spaces in the shape of a “lazy H”, spaced to avoid self-shading. At this early stage of conceptual design, self-shading was studied using Google Sketchup, while energy modeling was performed using eQuest version 3.60. In these early eQuest model runs, hydronic radiant heating and c
35、ooling in the ceiling slab and daylighting with continuous dimming were both included; however, numerous design features were not included in the proposal concept energy model but incorporated in subsequent design phases, such as: winter ventilation pre-heating (using a double skin faade design), su
36、mmer, occupancy sensors, natural ventilation, daylight redirection, and demand-controlled ventilation. The radiant heating/cooling system is modeled in eQuest as a fan coil unit with nearly zero fan energy. Early concept design drawings show a double skin faade. This approach was later eliminated up
37、on further analysis based on multi-disciplinary design coordination, thermal analysis (in IES Virtual Environment), and cost modeling in favor of an approach using a single faade with transpired solar collector. Producing timely energy modeling projections was a continual challenge for the design-bu
38、ild team throughout the design and construction process due to the rapid pace of the design and construction schedule. Rather than relying solely on eQuest, a constellation of models was employed to provide detailed analysis of different building components. The results of these models were then eit
39、her fed back into the eQuest model or used to post-process eQuest output to provide an integrated picture of whole-building energy use. For example: x Daylighting calculations were performed in Radiance, including window shading and light redirection using LightLouver technology and fed into eQuest;
40、 2http:/apps1.eere.energy.gov/buildings/publications/pdfs/commercial_initiative/energy_use_intensity_targets.pdf 400 ASHRAE Transactionsx Thermal effects of natural ventilation strategies were analyzed using IES Virtual Environment (IES VE) and used to post-process the eQuest results; x Data center
41、energy use, including electricity consumed by IT equipment, cooling energy, fan energy, and heat recovery was modeled outside of eQuest and added to the eQuest energy projections; x Air heating by transpired solar collectors on the south face of the building was used to post-process eQuest results;
42、x Ventilation pre-heating benefits of the crawlspace in the heating season, with inputs from the data center and transpired solar collector models, were modeled using a finite-difference thermal model and combined with the eQuest output. More details of each module in the energy modeling suite follo
43、w below. Daylighting/Lighting Modeling The Sensor Placement and Optimization Tool (SPOT) program is designed to quantify annual daylighting characteristics of a space and to establish optimal sensor placement for energy savings. It is driven by Radiance, a ray-tracing daylighting design tool designe
44、d to provide accurate, quantitative daylighting illuminance predictions, even when considering complex fenestration systems such as daylight redirection devices. Radiance was initially employed in the design competition phase in the context of the LEED daylight credit iEQ8.1, mandated in the RFP. An
45、alysis of the workplane illuminance under clear skies on equinox a metric for assessing compliance with this criteria showed that even with best practices of separating view glass and daylight glass and using the LightLouver Daylight System to redirect incoming sunlight deeper into the building, a m
46、aximum floor depth of 60 could be daylit sufficiently to claim the credit. This consideration effectively set the buildings footprint. For the purpose of the energy modeling, SPOT was able to provide an 8,760 hour schedule of the lighting power fraction for an electric lighting system with dimming c
47、ontrols needed to match the specified office illuminance setpoint. This schedule can be passed seamlessly to the DOE 2.2 engine of the eQuest energy model. For this analysis, the typical office space was broken into three zones a south perimeter zone, a core zone, and a north perimeter zone. Other d
48、aylit spaces were simulated using the built-in continuous dimming sensor and daylighting calculations available in eQuest. Installed lighting power density in open office areas is very low only 0.64 W/ft2, facilitated by the open office structure (no obstructions), reflective surfaces, ability to ut
49、ilize a regular grid, and by very efficient T8 fluorescent bulbs and fixtures. Natural Ventilation Modeling Window configurations and control strategies for natural ventilation were analyzed by modeling the building in IES VE. IES VE was used because it allows for explicit modeling of both the thermal effects of natural ventilation and thermal mass effects currently not possible in eQuest. The natural ventilation modeling was performed without including mechanical systems in the IES VE model, so that results represent purely passive conditioning. T
