In the current market environment, gas engine-based plants have proven to be a very competitive option for meeting the needs for power, heat and/or cold in municipal as well as industrial applications.
In the strive for improving overall CHP fuel efficiency, many new concepts for integrating the various heat sources available from the engine are being considered, but with an increasing level of integration there is also an increasing level of complexity. For assessing overall plant performance under various ambient and load conditions, it is therefore necessary to capture the characteristics of the engine not only in terms of rejected heat, but also with the related characteristics and/or constraints of flows, temperatures, and pressures.
In close coordination with leading OEM such as MAN Diesel & Turbo, Caterpillar/MWM, Kawasaki and GE Jenbacher, VTU Energy, the Austrian expert company in the field of heat balance analysis, developed a generic engine model that allows for representing engine performance and the control schemes of the various sources of engine heat that can be recovered to maximize overall fuel efficiency. The individual engine models can be selected from a library of pre-configured data sets that accurately represent the performance information including part load characteristics as documented by the OEM.
Users of the EBSILON Professional heat balance software can now integrate reciprocating engines from various OEM in detailed design and off-design models of complex plant systems that contain boilers, water heaters and/or entire steam cycles, but also ORC, absorption chillers, heat pumps, and other cogeneration options.
“With our Reciprocating Engine Library we are responding the market need for detailed technical information on the system level of the CHP plant”, says Dr. Peter Pechtl, managing director of VTU Energy. “With the growing fluctuations in the electricity market due to the increasing share of renewables, CHP plants are facing moving targets on both ends, power and heat demand, and every investment decision should be based on in-depth analysis using operating scenarios that are as realistic as possible as well as on sensitivity analysis of the expected demand”.