Abstract
Thermal modeling and optimal design of a combined cooling, heating, and power (CCHP) generation system are presented in this paper. A new procedure for simultaneous selection of the type (gas engine, diesel, gas turbine) and number of available prime movers (PMs) in a market, selecting PMs partial load, selecting the heating capacity of backup boiler as well as selecting the cooling capacity of electrical and absorption chillers available in the market are presented. A genetic algorithm (GA) with discrete and continuous decision variables is applied to select the equipment for the CCHP system by maximizing the actual annual benefit (AAB) as the objective function. The optimization problem is carried out for 1000 alternative states for electricity, cooling, and heating (E‐Q‐H) loads in the range of 500 kW to 5000 kW to investigate the effect of E‐Q‐H loads. Moreover, the optimization is performed at two SELL and NO‐SELL modes. In the former case is the sale of the excess electricity to the network is allowed and in the latter one, it was not allowed to sell the excess electricity to the grid. A correlation in terms of E‐Q‐H loads is obtained to specify the effect of E‐Q‐H loads on optimum AAB values in SELL and NO‐SELL modes. Using these correlations, designers can predict the maximum accessible AAB for any electricity, cooling, and heating loads in the above specified range.
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