Systems Approach to Energy Efficient Building Operation: Case Studies and Lessons Learned in a University Campus
|Title||Systems Approach to Energy Efficient Building Operation: Case Studies and Lessons Learned in a University Campus|
|Publication Type||Conference Proceedings|
|Year of Publication||2010|
|Authors||Narayanan, Satish, Michael G. Apte, Philip Haves, Mary Ann Piette, and John Elliott|
|Conference Name||2010 ACEEE Summer Study on Energy Efficiency in Buildings|
|Conference Location||Asilomar, California, USA|
This paper reviews findings from research conducted at a university campus to develop a robust systems approach to monitor and continually optimize building energy performance. The field analysis, comprising three projects, included detailed monitoring, model-based analysis of system energy performance, and implementation of optimized control strategies for both district and building-scale systems. One project used models of the central cooling plant and campus building loads, and weather forecasts to analyze and optimize the energy performance of a district cooling system, comprising chillers, pumps and a thermal energy storage system. Fullscale implementation of policies devised with a model predictive control approach produced energy savings of about 5%, while demonstrating that the heuristic policies implemented by the operators were close to optimal during peak cooling season and loads. Research was also conducted to evaluate whole building monitoring and control methods. A second project performed in a campus building combined sub-metered end-use data, performance benchmarks, energy simulations and thermal load estimators to create a web-based energy performance visualization tool prototype. This tool provides actionable energy usage information to aid in facility operation and to enable performance improvement. In a third project, an alternative to demand controlled ventilation enabled by direct measurements of building occupancy levels was assessed. Simulations were used to show 5-15% reduction in building HVAC system energy usage when using estimates of actual occupancy levels.