A Comprehensive Risk Management System on Building Energy Retrofit

Due to the fluctuations in energy prices and the global warming effects as a result of pollution emission in the energy generation/conversion processes, energy conservation has gained much attention recently. The buildings in US consume significant amount of energy. Thus undertaking a building retrofitting project, in which new technology and features are added to the existing structure, can potentially both yield a good return on investment due to the future savings in energy consumption and reduce the negative environmental impact due to reduction in greenhouse gas emission. In this project, we study how to optimally perform energy retrofitting of existing building structures. Most existing methods either focus solely on minimizing energy consumption, while overlooking the financial incentives and occupant comfort, or aim at optimizing the energy related expenses under one particular deterministic setting and omitting the stochastic risks, such as volatility in energy pricing, weather uncertainties, in the operating environment. Hence, the building owners may not find the recommendation for building construction/recommendation relevant and profitable over its lifetime, and may not be willing to undertake such projects. This work proposes a novel risk management system on building energy retrofit, which uses a comprehensive optimization framework and considers both deterministic and stochastic factors. In one case study, we show that this system can improve the performance of the building under uncertainties while satisfying constraints imposed by occupant.