Net ZEB Design Processes and Tools - Modeling, Design, and Optimization of Net-Zero Energy Buildings - page 187

4.3 Net ZEB Design Tools, Model Resolution, and
Design Methods
4.3.1 Introduction
Building performance simulation (BPS), a method for predicting a
building's performance prior to construction, has been available since the
1960s (Clarke, 2001). With the additional objective of aiming to achieve
absolute performance targets (e.g., net-zero energy), demands placed on the
usability and accuracy of BPS tools increase substantially. The prevalent
contemporary use of BPS in practice is to substantiate that the proposed
building performs well relative to a reference case (e.g., ASHRAE Standard
90.1 (ASHRAE, 2010a)) and for equipment sizing. One of the major
objectives of this chapter, in contrast, is to demonstrate the value of BPS in
design, from conception to detailed design, and to provide more absolute
performance data. Extensive use of BPS in this way is also presented in the
four detailed case studies in Chapter 7 .
By the most common Net ZEB definitions (Marszal et al. , 2011), a detailed
model must predict both annual energy demand and on-site generation.
Corollary requirements include (a) a high temporal resolution of electrical
power demand and supply from and to the grid in order to assess
grid-interaction considerations and (b) data about occupant comfort to
ensure that meeting energy objectives does not jeopardize comfort. Thus,
the three following requirements are imposed on Net ZEB modeling tools:
1. Ideally, at least one of the BPS tools used during the design process
must be capable of modeling all systems in an integrated manner.
Depending on the proposed building systems, an unintegrated model
(e.g., assessing a house and its solar thermal system separately) could
lead to poor modeling accuracy. Nearly all building systems have some
degree of interaction and should be treated as such.
2. Absolute performance of the building and all subsystems should be
estimated by using accurate inputs and circumscribing the uncertainty
of weather, occupant behavior, and construction quality. This is a
significant development from most modeling methodologies and
building energy codes, which emphasize typical building conditions
(e.g., occupancy patterns) and accept relative predicted performance.