(527d) Simultaneous Optimization of Design and Operation Strategies for CHP Systems
In our previous work , we demonstrated that a CHP plant with PV integration can in principle meet the demands of a residential neighborhood during the summer months. However, a CHP plant operating in island (i.e., grid-disconnected) mode must be optimally sized to maximize efficiency and to lower the capital and marginal costs, while producing enough electricity, heating, and cooling to meet the neighborhood demands at all times. A majority of the approaches described in literature for the optimal CHP plant sizing tend to select equipment by analyzing the various utility demands (i.e. electricity, steam, and chilled water) individually. Also, they only minimize the capital and O&M costs, overlooking the transitional costs of equipment turning on, by either not allowing the equipment to turn off or ignoring the monetary value of the wear and tear on the equipment. Lastly, many micro-grid papers assume that the main grid will be there to support the system at all times, if the CHP plant is not able to produce the needed energy.
In the paper, we describe a novel simultaneous optimization of design and operation strategies for a CHP plant as a utility producer for a residential neighborhood operating in island (i.e., grid-disconnected) mode, incorporating residential photovoltaics, implemented in a centralized fashion. In order to more accurately predict the operational costs of the CHP plant over a long period of time, the integrated design optimization is combined with an operational-oriented scheduling, forming a two-level problem. The first level consists of the presented integrated design and scheduling optimization, which selects equipment for a plant that must meet hourly residential neighborhood utility demands while minimizing the overall cost of the plant. The second level uses the optimal equipment sizes determined from the first level, and schedules the plant for a year, giving a better result of the operation economics of the CHP plant over a longer period of time. Utilizing data collected by Pecan Street Research Inc., a non-profit smart grid demonstration project headquartered at The University of Texas at Austin, a year of hourly residential heating, cooling, and electricity demand are analyzed and evaluated. These data are then used to create a time-resolved energy demand profile describing residential energy use, which is subsequently serves as a basis for optimizing the size and operation of the CHP plant so that all utility demands are met, while minimizing the capital and marginal costs, including transition penalties.
 Ondeck, A.D., Baldea, M., Edgar, T.F. (2015). Data-Driven Modeling and Optimal Operation of District-level Combined Heat and Power and Photovoltaic Power Generation System. Applied Energy, 156, pp. 593-606.