Tag: Energy Modeling

Technological advancements in the building design and construction industry are allowing the performance envelope to be pushed from all directions. Reducing energy usage, improving occupant comfort, optimizing lighting levels, and integrating systems to simplify operation and maintenance practices are all examples of issues that require close scrutiny and expertise when designing high performance buildings. To achieve success with such projects, high performance buildings require a more collaborative approach to design and construction. In order to produce and sustain the performance levels of these types of facilities, owners are actively involved during the design process and have upgraded their approach to operations and maintenance. more

The current approach in building design focuses almost solely on increasing energy efficiency by improving system-oriented controls and behavior. However, occupant behavior also affects energy efficiency. To provide a more realistic modeling result, occupant behavior needs to be included in energy modeling.  more

Micro-electro-mechanical systems (MEMS) were invented in the second half of the past century and since then their use has been growing rapidly. The automobile industry was an early adopter, using MEMS sensors for automobile navigation, tire pressure control, and airbag deployment. As we start transitioning from today’s buildings and systems to future smart buildings, design engineers will have a wide variety of MEMS applications to choose from. more

In my earlier columns, I tried to explain the concept of uncertainty analysis and also draw the attention of the industry to the advantages of performing probabilistic energy modeling. One of the most valuable complementary tools to uncertainty analysis is sensitivity analysis. Terje Aven in his book, Foundation of Risk Analysis,1 gives the following definition for sensitivity analysis: “A sensitivity analysis is a study of how sensitive the risk is with respect to changes in input parameter of risk model.” more

Building an energy-efficient building often begins with an energy (cost) comparison between a design building and an imaginary baseline building as defined in ASHRAE/IES Standard 90.1, Appendix G. Even though this method has contributed to higher performance of buildings and systems, I believe we can do better than that. more

In my November column, I discussed the necessity of performing a probabilistic energy modeling process instead of a deterministic one for an ASHRAE/IES Standard 90.1, Appendix G, design building. To be able to run a probabilistic energy model, the first step is to develop a tolerance margin library for all the construction material that would be used in constructing a building and for its associated equipment. more

Uncertainty analysis is the process of changing simulation model input parameters in a small margin of possible occurrences and observing how simulation output can be affected (output probability distribution). That is the basic difference between a deterministic simulation and a probabilistic (uncertain) simulation. Uncertainty analysis is a strong tool for modelers and those who use modeling results to make well-informed decisions. more