Grantee Research Project Results
Final Report: Residential Energy Optimization Algorithms
EPA Contract Number: EPD10032Title: Residential Energy Optimization Algorithms
Investigators: Wright, Christopher David
Small Business: Interdisciplinary Design Collaborative, LLC
EPA Contact: Richards, April
Phase: I
Project Period: March 1, 2010 through August 31, 2010
Project Amount: $66,890
RFA: Small Business Innovation Research (SBIR) - Phase I (2010) RFA Text | Recipients Lists
Research Category: Small Business Innovation Research (SBIR) , SBIR - Green Buildings
Description:
Many homeowners and businesses today strive to conserve energy to cut down on costs as well as their environmental impact. One way to conserve energy is to activate systems based on the status of the room. An example of this is to reduce lighting based on occupancy and ambient lighting available. Some systems on the market give users an idea of total energy consumption, but leave the action up to the user. Consumers are unable to selectively choose how to use energy wisely. Automation systems allow such actions to be carried out automatically and more precisely and thus save energy, but most automation systems are based on simple logic. These systems also result in actions that are not optimized for the building type, weather forecasts, or future actions.
The main research interest of Interdisciplinary Design Collaborative, LLC (IDC) lies in the smart control and optimization of systems or products within the building to reduce electricity consumption. IDC has begun initial developments on software that builds on automation systems and improves their efficiency. The research was to design a starting parameter set for the energy modeling, develop a baseline energy consumption model, and determine the effect of the proposed optimization on the baseline energy model. The project was also designed to analyze the effect of the precision of forecasting and modeled data.
The software determines set-points that dictate the control of the automation system to optimize the energy conservation. The product also will forecast the effects between building systems to assist in the design and expansion of the current automation system. Research was completed during the period of performance for Phase I to determine the feasibility and marketability of the system.
Summary/Accomplishments (Outputs/Outcomes):
The optimized best case scenario resulted in the largest drop in energy usage with 24.14 percent reduction in energy consumption with daily set-point analysis. The seasonal optimization best case resulted in 23.35 percent reduction in energy consumption and the annual optimization best case resulted in 23.34 percent reduction. This is a range of 0.8 percent difference between all precision levels of the optimized best case. The worst cases resulted in 121.27 percent, 123.76 percent, and 125.03 percent of energy consumption with annual, seasonal, and daily optimization, respectively. The worst case variation in percent difference of energy consumption was 3.76 percent.
There is a slight, but noticeable, difference in the effect of the precision of the set-point optimization. The difference between the best case scenarios of the seasonal optimization from the daily optimization is 1.041 percent. The difference of the annual optimization from the daily optimization is 1.044 percent and the difference between the control model and the daily optimization is 31.814 percent.
Conclusions:
The shown 24.14 percent reduction in energy consumption over a non-actuated control model utilizing 12 set-point parameters shows promising feasibility for the IDC's optimization software. The higher precision of daily optimization showed slight improvement of results as compared to the annual optimization, which also may point to greater savings with the implementation of a greater set of set-point parameters. These results of 24 percent reduction compared to tested and implemented products for visualizing energy consumption that have shown 15 percent makes a case for the market potential of IDC's product with further testing and refining.
The commercialization plan represents the basic foundations of a business model focused on licensing a technology to a small number of system integrators who then will include it in a product sold to the general public. IDC's optimization product will be a portion of software designed to reduce the energy consumption in a building by analyzing and comparing sensor data to a computer model, then looking for variables that can be changed to reduce total energy cost. IDC intends to protect the intellectual property developed with applicable international and domestic patents, registered trademarks will protect the brand name, and copyrights will protect portions of the software. Pricing for OEM manufacturers to integrate IDC's product will have very low initial capital requirements and allow for some manufacturers' widgets to be sold at under the $100 mark. IDC also will charge a consulting fee to those who wish for extra help when integrating the optimization product. Primary marketing efforts will be through one-on-one contact with potential integrators and extensive efforts to document, test, and publish scientific results regarding system performance. Continued development efforts will take place in Rolla, Missouri, which offers an ideal location: low-cost, technically influenced talent pool, and close proximity to Missouri S&T, a premier research institution. IDC has successfully commercialized other software- and hardware-based projects and will use the same methodologies employed previously with success to define and penetrate new markets. Overall, this model is fast and flexible and allows IDC to maintain low overhead cost, reduced risk to all stakeholders, and the highest potential for monetary return and job growth.
Supplemental Keywords:
small business, SBIR, EPA, green buildings, indoor air quality, alternative energy technologies, energy consumption, energy management, energy reduction, optimization algorithms, residential energy conservation, HVAC efficiency, power consumption, energy production, photovoltaic systemThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.