-
36 Languages:
2.9 Summary
The RETScreen CHP Project Model uses a combination of algorithms to predict the energy delivered, on a yearly basis, by a combined heating, cooling and power system. Peak heating and cooling loads are calculated from building descriptions entered by the user. Load duration curves are derived from monthly degree-days data; domestic hot water is included in the load by defining equivalent degree-days for hot water heating. The load duration curve is then used to calculate the energy use on a monthly basis and during a fictitious ‘peak period’. Algorithms for steam turbines (without or with extraction), gas turbines, combined cycle gas turbines, and other systems, are used to calculate power capacity, recoverable heat and fuel consumption. The monthly energy use are used to predict what fraction of the needs is met by base, intermediate and peak systems given their respective capacities.
Various parts of the algorithm have been validated against other programs or against values published in the literature. Despite the simplicity of the model, the accuracy of the model proves acceptable at the pre-feasibility stage, when compared with other software tools or with published data.
The RETScreen CHP Project Model uses a combination of algorithms to predict the energy delivered, on a yearly basis, by a combined heating, cooling and power system. Peak heating and cooling loads are calculated from building descriptions entered by the user. Load duration curves are derived from monthly degree-days data; domestic hot water is included in the load by defining equivalent degree-days for hot water heating. The load duration curve is then used to calculate the energy use on a monthly basis and during a fictitious ‘peak period’. Algorithms for steam turbines (without or with extraction), gas turbines, combined cycle gas turbines, and other systems, are used to calculate power capacity, recoverable heat and fuel consumption. The monthly energy use are used to predict what fraction of the needs is met by base, intermediate and peak systems given their respective capacities.
Various parts of the algorithm have been validated against other programs or against values published in the literature. Despite the simplicity of the model, the accuracy of the model proves acceptable at the pre-feasibility stage, when compared with other software tools or with published data.
