Conference Year
2016
Keywords
Cogeneration, optimization, power plant, steam and chilled water production
Abstract
The Wade power plant at Purdue University produces chilled water, steam and electricity using CCHP (Combined Cooling, Heating and Power) systems to meet the campus cooling, heating and electricity demands. Steam generated from utility boilers is not only distributed through a steam tunnel system for campus heating but also used for power generation, chilled water production and in-plant auxiliary usage. Chilled water is generated using both steam driven chillers and electric chillers and is delivered through a closed water circulation loop to campus to meet the time-varying cooling demand. The electricity generated using two steam turbine driven generators provide 30-50% of the electricity required to meet campus needs. The remainder of the electricity is purchased from the local electric utility and includes a real-time pricing component that varies with time. Plant primary energy use and costs depend upon decisions regarding generation and purchasing of electricity in response to time varying factors so as to keep the operating cost minimum and meet campus electricity, heating, and cooling demands subject to time-varying prices, loads, and environmental conditions. This paper presents an approach for optimizing the operation of the CCHP system using a multimodal genetic algorithm based on hourly load forecasts and fuel pricing with a joint characteristic for the energy components to minimize the total operating cost of the plant. The tool is used to evaluate the benefits of optimal control for the Purdue CCHP plant as a function of different (possibly future) utility rate incentives.