Optimal Power Generation Unit Sizing for Base-Loaded Combined Heat and Power Systems Using Monthly vs. Hourly Time-Steps

In many applications combined heat and power (CHP) systems provide both cost and environmental benefits when used in place of traditional grid utility systems. The benefits of CHP systems, however, are very sensitive to the proper selection of the system’s components for given loading conditions, especially the power generation unit (PGU). The PGU size should be selected based on the facility’s electrical and thermal loading conditions to generate the maximum cost savings. Many researchers have presented methods for selecting the optimal PGU size using hourly load data. However, hourly load data is seldom available for a facility. For this reason, this paper provides a series of calculations that determine the optimal PGU size based on annual cost savings for a base-loaded CHP system using monthly load data, which is representative of a facility’s utility bills that are always available. Furthermore, because resale of excess electricity to the grid is widely available in the United States and other countries, this capability is included in the equations presented in this paper. Unfortunately, in some cases monthly-based calculations do not provide enough information to properly determine the optimal size of the PGU. A case study is performed to compare the results of monthly-based and hourly-based calculations for sixteen benchmark buildings in Albuquerque, NM and Baltimore, MD to investigate when monthly-based calculations can be used. It is noted that resale of excess electricity is considered in Baltimore, but not considered in Albuquerque for this study. A statistical analysis of the results uncovers that the magnitude of the coefficient of variation of the building’s heating demand indicates whether monthly-based calculations can be used, and furthermore, whether annual cost savings are possible. Results indicate that the proposed monthly-based calculations can determine the optimal PGU size, and calculate annual cost savings for approximately half of the facilities in Albuquerque and Baltimore. Further studies must be performed to determine a broader range of locations where this monthly-based calculation strategy is valid.