Optimizing the selection of sustainability measures for existing buildings
Buildings in the United States have significant impacts on the natural environment, national economy, and society. According to the U.S. Green Building Council, buildings in the United States account for 41% of energy consumption, 73% of electricity consumption, 38% of carbon dioxide emissions, and 14% of potable water consumption. Furthermore, aging buildings represent a significant percentage of existing buildings and are often in urgent need for upgrading to improve their operational, economic, social, and environmental performance. The owners of these buildings often seek to identify and implement building upgrade measures that are capable of improving building sustainability as well as achieving certification under various green building programs such as the Leadership in Energy and Environmental Design (LEED). Several green upgrade measures can be used to improve the sustainability of existing buildings such as energy-efficient lighting and HVAC systems, photovoltaic systems, and water-saving plumbing fixtures. Decision makers often need to select an optimal set of these building upgrade measures in order to maximize the sustainability of their buildings while complying with available upgrade budgets. The main goal of this research study is to develop single and multi-objective models for optimizing the selection of sustainability measures for existing buildings. To accomplish this goal, the research objectives of this study are to (1) evaluate the actual operational performance of sustainability measures in existing buildings, (2) develop a novel LEED optimization model that is capable of achieving user-specified certification levels with minimum upgrade cost, (3) develop an innovative environmental model for minimizing the negative environmental impacts of existing buildings, (4) develop an economic model for minimizing building life-cycle cost, and (5) develop a multi-objective optimization model that is capable of generating optimal tradeoffs among the building sustainability objectives of minimizing negative environmental impacts, minimizing upgrade cost, and maximizing LEED points. The performance of the developed optimization models was analyzed and verified using case studies of public buildings. The results of analyzing these case studies illustrated the novel and unique capabilities of the developed models in searching for and identifying optimal sets of building upgrade measures for existing buildings. These new and unique capabilities are expected to support building owners and managers in their ongoing efforts to (i) achieve LEED certification, (ii) reduce building energy and water consumption, (iii) reduce building negative environmental impacts, and (iv) reduce building operational and life-cycle costs.
Optimization, Sustainability, public buildings, operational performance, green-building measures, sustainability measures, user satisfaction, ease of maintenance, operational problems, energy savings, water savings, payback period, energy consumption, water consumption, Leadership in Energy and Environmental Design (LEED) rating system, Leadership in Energy and Environmental Design (LEED) certification, existing buildings, negative environmental impacts, greenhouse gas emissions, refrigerant impacts, light pollution, mercury-vapor emissions, life-cycle cost, upgrade cost.
University of Illinois - Urbana-Champaign
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University of Illinois at Urbana-Champaign