# Energy Analysis + System Modeling

### Estimating Annual Consumption

For the house to be both effective and affordable, electrical loads and thermal loads must be analyzed and minimized to properly size the PV system so that all electrical needs are met with minimal excess production. To perform this task, the team has estimated the annual expected energy consumption from indoor electrical loads (such as appliances, lighting, and various plug loads), the electric car, and the HVAC system, and used this along with modeled solar PV production data to size the array for Austin, TX. The following section summarizes the modeling effort for evaluating the performance of NexusHaus.

### Estimating Annual House Electricity Consumption

Estimating the electricity demands for the house was performed using a program called BEopt (Building Energy Optimization), a Department of Energy developed software that uses Energy Plus for the underlying energy modeling engine. BEopt was developed for quickly estimating energy consumption and savings from energy efficiency upgrades, and was designed specifically for modeling residential buildings. BEopt uses a simplified geometry builder to approximate the size and glazing of a home for energy purposes, which has been shown to be reasonably accurate at estimating actual home energy consumption from real-world benchmarking (1). This program provides a good starting point for residential energy analysis and system sizing. Modeling a simplified version of NexusHaus (see Figure 1), the team was able to estimate internal electric loads and whole-home heating and cooling loads.

Variables in the model included house insulation and glazing properties. These inputs, shown in Table 1 and other parameters, such as house location and orientation, number of bedrooms and bathrooms, type of lighting, type of appliances, and miscellaneous loads are all factored into the model to calculate annual energy consumption based on occupancy and usage.

NexusHaus was modeled in the BEopt system using LED lighting, energy efficient appliances, and typical miscellaneous loads. We were primarily interested in the indoor appliance and lighting loads, for which BEopt has a variety of preprogrammed values and schedules based on Building America survey data and previously validated models.

The modeled annual energy consumption from BEopt is shown in Figure 2. The category ‘Lg. Appl.’ includes the refrigerator/freezer, dishwasher, clothes washer, and dryer. ‘Misc.’ includes all plug loads present in a typical house (including small electronics, computers, televisions, etc.).

For order of magnitude comparison purposes, this model run shows the energy consumption from a mini-split heat pump with SEER 18 rating (similar system efficiency to the chiller model used in the NexusHaus design). This example analysis used the DOE-specified comfort range year-round for estimating the heating and cooling load. A more complete calculation is of the heating and cooling load is described on the Estimating Water + Mechanical Systems Electrical Consumption page.

### Estimating Water + Mechanical Systems Electricity Consumption

NexusHaus uses a hydronic heating and cooling system with indirect chilled water thermal storage utilizing rainwater—a design not typical of a normal residential home. While the BEopt model provides an order of magnitude estimate of heating and cooling energy consumption based on a heat pump system with similar efficiency, it does not have built-in hydronic fan coil options, nor the ability to model energy consumption from the rainwater system components. To calculate estimated performance of the hydronic system, and the potential energy consumption from the rainwater system, a separate post-processing step was used to calculate electricity consumption for the hydronic and rainwater systems.

The cooling load for a calendar year is taken from BEopt and used to calculate the run-time and energy consumption of the system, taking into account the outdoor air temperature.

Using this model, the total annual energy was calculated for cooling and heating the house, shown in Table 2. For this analysis, the thermal storage system was only used during the summer afternoon hours, and not during the winter.

While the thermal storage can reduce on-peak load (electricity demand and energy consumption) by approximately 75-80%, it has an associated energy penalty of 7-9% beyond the regular hydronic system. Since time of use and load shifting are not accounted for in the measured energy contest, the thermal storage system will not be operated during the competition to conserve energy for the energy balance competition. Similarly, the on-site treatment system is designed to run continuously 24 hours per day as a safety precaution, so this system will be turned off during the competition to avoid unnecessary energy consumption.

### Estimating Electric Car Annual Electricity Consumption

Electric car energy consumption is not something that is modeled in BEopt. Estimation of this load was performed by multiplying the average electric efficiency of the car (in kWh/100 miles) by estimated annual miles driven. These calculations were performed for three scenarios: a low car use (10mi/day) scenario, a medium car use (20mi/day) scenario, and the average American driver (approximately 41 miles/day). Table 3 below shows the estimated annual electricity consumption based on these car usage scenarios, assuming the average car efficiency, and that all car charging is performed at home, and that the charging efficiency is included in the car efficiency.

As shown in the table, electric car recharging loads can be quite significant, equaling over 13% of the non-car house electricity load on the low use scenario, and equal to over 54% if driven the average annual mileage for a typical American. Since NexusHaus is meant to be urban infill in the central neighborhoods of Austin, we will assume the occupant will not need to drive as for or as often, and therefore we will only evaluate PV array sizing based on the first two scenarios.

### Total Load for Sizing the Solar PV Array

Adding all non-HVAC house loads from BEopt, the estimated car load, and the calculated HVAC loads for the house, the total annual energy consumption estimate is shown below in Table 4. These numbers provide the basis for sizing the PV array to meet net zero energy operation. Looking at the differences between the annual total energy consumption, the range is from approximately 8,000 kWh on the lowest end to 10,550 kWh on the highest end. Since the goal of this house is to provide the ability to operate on a rainwater supply for domestic water, the system will be sized to accommodate the energy needs of the ITHERST system.

Using the PV modeling capabilities of BEOpt, it is estimated that an 8.1KW (DC) array could provide approximately 10,870kWh during a typical year in Austin. Based on the DC rating of the SolarWorld panels provided (290W), an array with a 10 degree slope comprised of 28 panels yields a system capacity of 8.12kW DC.

Beyond meeting the needs for the ITHERST System, up-sizing the PV array is also necessary to ensure the house produces enough energy for the Solar Decathlon competition. Modeling for the competition week (October 8-18) in BEOpt Estimates total energy consumption of approximately 252kWh, and solar production of approximately 277kWh. The energy consumption estimate from BEOpt is somewhat higher than our own conservative estimate (approximately 230kWh) calculated independently in Excel based on contest criteria, measured appliance performance, and name-plate ratings of light fixtures and other electric loads.

For more information about the engineering of NexusHaus, select one of the icons below:

Source:

- J. D. Rhodes, W. H. Gorman, C. R. Upshaw, M. E. Webber. Using BEopt (EnergyPlus) with energy audits and surveys to predict actual residential energy usage. Energy and Buildings 86: 808-816, November, 2014.

Thanks for the great share! I also like the idea of Energy Efficiency. The best part I like is this: The reliability and availability of modern energy sources cause people to tend to assume that it will always be accessible. And as for the case of non-renewable energy sources, most people do not know or maybe even refuse to accept that it will eventually run out.