SBIR Phase I: Predictive Modeling and Automatic Control of Landfill Gas Collection

This Small Business Innovation Research Phase I project proposes to improve the collection of landfill gas by applying a real-time control system and developing advanced models of gas generation and extraction. It has the potential to improve the economics of the Landfill Gas to Energy (LFG-E) market and reduce the environmental impact of landfills. With industry-wide implementation, annual revenues from existing LFG-E projects could be increased by over $450 million. The additional energy produced would power over 350,000 homes. Methane is a powerful greenhouse gas, and the Environmental Protection Agency (EPA) estimates that in 2011, emissions from landfills accounted for nearly 17.5% of all human-generated methane in the US. The associated reduction in Green House Gas emissions from improved landfill gas collection would be equivalent to cutting the consumption of over 3.6 billion gallons of gasoline or 76 million barrels of oil. Furthermore, because of the improved economics, this Phase I project could encourage the development of new LFG-E projects, further expanding the size and value of the landfill gas to energy market. According to EPA estimates, currently undeveloped sites could account for an additional 850 MW of power generation, enough to power over 508,000 homes. Landfill gas collection systems are currently operated manually and lack the embedded feedback capabilities to properly match the rate of gas extraction to the rate of generation in response to changing environmental conditions. The proposed control hardware is a wireless, fully automatic sensor and actuator device able to measure key characteristics of landfill gas and adjust gas extraction rates on individual wells in real time. The research objective is to utilize these capabilities to collect data and develop a deeper understanding of landfill gas generation and the complex interactions within the extraction system. A series of experiments will quantify the strength of interactions between different wells in a landfill. The data will be used to develop a model describing how gas characteristics change in response to modulations in gas extraction pressure. A successful outcome of this research would be the development of a basic control model that can be used to analyze recent trends in extraction data and incorporate real time information about environmental conditions (temperature, barometric pressure, precipitation, etc.), in order to maximize energy extraction.