Project Frog understands there isn’t a "one size fits all" approach to achieve significant energy savings. Energy demand can only be reduced through a whole systems analysis – one which evaluates how all the components of a building (including insulation, light fixtures, orientation, climate, and occupancy) work synergistically to reduce the building’s overall energy demand. 

Our proprietary predictive modeling tool establishes our baseline design for different climates and building types. This model is then adjusted based on specific client needs to achieve an optimized design that creates the right balance between energy performance, user comfort and project cost.

In the future, all buildings will be built this way. We're just building brighter now.

Our energy and comfort simulations are run using a program built up from EnergyPlus, a peer-reviewed and field-tested energy simulation software that models heating, cooling, lighting, ventilating, and other energy flows within the structure based on first principles of facility science. While originally based on the features and capabilities of BLAST and DOE-2, EnergyPlus includes many innovative simulation capabilities such as thermal mass, natural ventilation, complex window effects, multi-zone air flow, and photovoltaic systems.   

Working closely with Loisos + Ubbelohde, one of the world’s most respected energy consultancies, Project Frog has developed a specific set of parametric modeling and optimization routines that allow us to run multi-dimensional matrices for optimizing buildings for our clients. As opposed to traditional energy analysis which might compare only 10 – 20 scenarios and where it is not possible to account for interactions among multi-variable parametrics, our more robust code has enabled us to compare thousands of scenarios for any given project.

As part of the overall qualitative/quantitative analysis approach, a deterministic, quantitative multi-criteria decision model (MCDM) algorithm weighs the relative importance of three metrics used to define the optimal configurations of the structure: annual energy use, cost-effectiveness and occupant comfort.

Annual Energy Use. Achieving a low-energy configuration, in terms of cooling, heating, lighting and equipment loads, is a primary metric for determining the optimal configuration. However, it cannot be the only one. There are practical limits to the constructability of energy efficiency solutions, and it is important to determine the point of diminishing returns. For example, how much benefit is derived from adding an additional inch of insulation? Therefore, energy use is considered along with the other metrics below.

Practical Cost-Effectiveness. This metric uses estimated construction costs relative to a standard baseline facility for the particular components of a modeled configuration, as well as the cost of the PV array required to provide 100% of its energy use. The sum of these costs or cost savings is considered the cost-effectiveness for choosing a particular configuration that will result in a real impact on overall construction cost, energy use and therefore PV array size/cost.

Occupant Comfort. Many energy efficiency measures do not show up as beneficial in a simple energy use calculation, but they could have a large impact on thermal comfort. One example is thermal mass. Though thermal mass does not significantly reduce cooling loads, it does affect interior mean radiant temperatures, and therefore occupant comfort and potentially HVAC system sizing or setpoints. This metric uses the number of degree-hours spent outside a specified comfort zone over the course of a year to measure occupant comfort.

Each of these components is critical to a building’s efficiency, and is inherent to Frog’s smart systems.