Engineering Reference

Introduction

The insights and recommendations provided by the Ecologic platform are underpinned by a set of advanced physical and financial simulations. This document provides a high-level description of the model basis and assumptions to facilitate peer review, transparency and confidence.

HVAC simulation

The HVAC Module calculates the energy and water consumption of a wide range of heating, ventilation and air conditioning equipment using the EnergyPlus simulation engine developed by the US Department of Energy.

The program performs a simulation of the thermal physics of the building at least every 20 minutes throughout the year.

The primary driver of this simulation is the external meteorological conditions including consideration for external air temperature, humidity, solar radiation, wind speeds and direction. This is drawn from Typical Meteorological Year files which provide synthetic but statistically representative meteorological data for approximately 2,200 locations around the world.

A thermal model is developed to determine the coupled interaction between the indoor conditions and the external environment. This firstly involves generating a 3D model of the building from the 2D floorplan, either inferred using machine vision from aerial photography or directly input by the user. This process takes into consideration any specified building features including orientation, shading, window areas, eave depths, roof geometry and zoning. The building constructions are then applied to model the thermal performance of each building component including their thickness, thermal conductivity, density, specific heat and absorptance. Infiltration of outside air is modelled using the Sherman-Grimrud model, with leakage areas based on regression analysis of 147,000 buildings (Chan, Joh and Sherman 2013). Natural ventilation is simulated using an airflow network model where specified. The foundation heat transfer is modelled using a 2-dimensional finite difference model (Kruis 2015).

The performance of the HVAC equipment is simulated to determine its ability to maintain the indoor environment within a range of control points, such as the desired temperature set points, humidity levels and ventilation rates. The HVAC simulation takes consideration of a range of variables including the system type (zone vs central, evaporative vs refrigerative cooling, heating fuel etc), the heating and cooling set points, the HVAC system capacity, the coefficient of performance (or energy efficiency ratio) and how the system performs under part loading and/or subject to different external air temperatures.

The output of the simulation is the simulated internal comfort conditions and energy and/or water loads attributable to the HVAC equipment.

Key assumptions

Lighting simulation

The Lighting Module calculates the lighting condition and energy loads associated with a range of lighting equipment. The simulation combines details on the building geometry, including the presence of windows and other glazed surfaces, with occupancy data (e.g. occupancy type and schedules) to determine the required lighting throughout the day. The energy loads are a function of the lighting levels and the efficiency of the lighting fixtures that have been applied, which is determined for each lighting type (e.g. incandescent, fluorescent, LED etc).

Key assumptions

Appliance simulation

The Appliance Module calculates the electricity, gas and water consumption of each appliance installed on the property. The consumption is defined by the following function:

consumption = intensity * activity

• the intensity defines the amount of electricity, gas and/or water consumed by the appliance, either per unit of time (e.g. in watts) or per usage event (e.g. in joules or kilowatt-hours)
• the activity defines when the appliance is used, whether in terms of event frequency per day (or per week), event duration, usage duration per day (or week)

The resource consumption rate (or 'intensity') of each appliance is estimated based on a range of predictors including the type of appliance (e.g. whether a fridge is a top fridge-freezer or side-by-side fridge freezer), the age of the appliance, the size of the appliance etc. Where such information has been provided, these estimates are overriden by the actual rated consumption of the appliance model (either directly or accessed via one of our appliance rating databases using an appliance model code).

Appliance usage behaviour (or 'activity') is assigned across the day (or week) using an activity distribution schedule for each property type and for each appliance. For instance, if the property is a residential home and they have indicated they use a television for 2 hours each day, the distribution schedule assumes those two hours occur during the most common times of day, in this case in the evening at around 6-8pm. If they use a television for 8 hours, this usage will be assigned across the night time peak, and then the remainder across the daylight hours. A different activity distribution schedule is assigned for other property types (e.g. commercial offices, retail spaces etc).

Key assumptions

Water heating simulation

The Water Heating Module calculates the energy consumed by a range of water heating systems including electric, gas, and solar. This is achieved by firstly estimating the property hot water demand attributable to all appliances using the Appliance Module. A water heater is then simulated to provide all water heating loads on the site based on a range of input variables including the water heater type, the tank size, the water heater fuel, and the conversion efficiency of the water heater. For solar water heaters, a hybrid system is developed to determine the relative role of the thermal solar panels as distinct from the electric or gas booster heater. For air source heat pump water heaters, the simulation incorporates interaction effects with the external air conditions including the deterioration in performance under cold conditions.

Key assumptions

Solar and battery simulation

The Solar and Battery Module calculates the energy generated and stored on the property throughout the year using the PVWatts simulation engine developed by the US Department of Energy. The solar simulation applies hourly direct and indirect solar insolation data for the nearest typical weather file to firstly determine the radiant energy available. A set of geometrical calculations are performed to calculate the incident radiation received by the surface of the solar PV panels. If no panel azimuth is provided, the azimuth is assumed to be the most sunward roof surface (if specified) else due north / south are assumed. If no panel tilt is provided, the site latitude is applied. The incident radiation is then converted to electrical energy using the assumed panel efficiency and system losses (see table). A sub-hourly energy balance is then performed to estimate the amount of energy consumed on-site, stored in battery storage and/or exported to the grid for each time step. The performance of the battery system includes consideration of the storage capacity, charge capacity, discharge capacity, charge efficiency, discharge efficiency, and operating regime (i.e. whether the battery is operated to maximise self consumption, for time of use triage and/or for peak load levelling).

Key assumptions

Tariff simulation

The Tariff Model translates the electrical, gas, and water consumption and/or generation into bill estimates. The model supports a wide range of tariff structures including:

• flat tariffs, which apply a consistent volumetric charge rate throughout the year
• block tariffs, which apply a volumetric charge rate that varies with the level of consumption over a defined period, whether it be 'inclining block', where higher levels of consumption cost more per unit, or declining block, where higher levels of consumption cost less per unit.
• time-of-use tariffs, which apply different volumetric charge rates at different times of day, typically including at least a 'off peak rate', a 'peak rate', and optionally a 'shoulder rate' and/or 'mid peak rate'.
• controlled load tariffs and other appliance-specific tariffs, where a specific rate is applied to off peak hot water systems, heating systems, pools etc.
• peak demand charges, which apply a charge for the peak rate of electical load over a defined period.
• net feed-in tariffs, gross feed-in tariffs, and/or supply rates which reward the property for exporting electricity to the network
• fixed connection charges

Location-specific defaults are applied where no specific rates have been specified.

If no load profile has been provided, the tariff module applies the simulation engine to estimate a synthetic profile of the electricity, gas and water consumption throughout the year.

Where on-site generation and/or storage is considered, the tariff simulation incorporates the sub-hourly import, self consumption and export of electricity to provide an estimate of the bill impacts of different generation and/or storage systems.

Greenhouse gas simulation

The Greenhouse gas model simulates the greenhouse gas emissions attributable to activities on the property including direct, indirect and embodied emissions. Emissions are calculated by assigning a set of equivalent greenhouse gas intensity factors to each of the activities.

Peer review

If you have any questions or suggestions regarding the model structure and assumptions please contact us at info@ecologicapps.com.