Alternate power generation system to conventional system

What is it about?

For the generation of electricity, the conventional power generation system is Rankine cycle. However due to scarcity of coal, there is a necessity for finding an alternate power generation system. Power generation systems are identified based on the heat recovery applications as high temperature, medium temperature and low temperature. Sizable number of investigations on high temperature and low temperature applications are summarized in literature. Hence in the present work a power generation system suitable for recovering waste heat from medium temperature heat source is examined. Kalina cycle is a power generation adopted for low temperature and high temperature applications. The power generation system uses two component working fluid ammonia-water mixture. Water and ammonia are the components having identical molecular weights. The components involved in the proposed power generation system are identical to Rankine power generation system. For separating liquid and vapor mixture from the proposed component is performed with the inclusion of separator. Thermophysical properties of the ammonia water mixture are evaluated using Python software. The coding was developed in Python with the existing correlations for the binary mixture. The property values are identical as resulted through Matlab. For the proposed system energy and conventional exergy analysis have been carried out. To evaluate the performance of the system parametric investigation have been carried out. With the identified parameters the energy assessment identifies the output with the given input. By carrying out the conventional exergy analysis the losses in the components of the system is investigated. The losses are higher in the components using high energy source.

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Photo by American Public Power Association on Unsplash

Photo by American Public Power Association on Unsplash

Why is it important?

The investigation provides the equations for carrying out the energy and exergy measures. The algorithm to identify the thermodynamic property measurement is summarized. Generally the properties can be evaluated using MATLAB, EES etc. In this work the properties are evaluated using Python software.

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