
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Application of Monte Carlo method in economic optimization of cogeneration systems – Case study of the CGAM system

Abstract Similar to other energy systems, economic analysis of cogeneration systems is one of the most important steps in their design procedure. In this paper, a novel method is suggested for economic optimization of cogeneration systems. This method provides an opportunity to consider uncertainties in various economic parameters. Accordingly, by providing the probability distribution function of the net present value or payback time, this method offers further insights in economic evaluations of cogeneration systems. As a common practice for demonstrating novel methodologies in design and optimization of cogeneration systems, the proposed method of this study is applied to a well-known cogeneration case in the literature. In a coupled scheme, Monte Carlo approach is applied with net present value method to optimize the system. Accordingly, the obtained result is the probability distribution function of the net present value of the maximum profit. The results verify that compared to previously used methods which did not consider uncertainties in economic parameters, this probability distribution function provides a more general point of view on the profitability of the system. Therefore, by showing economic risks, these considerations make investments in this cogeneration system far more interesting.
- K.N.Toosi University of Technology Iran (Islamic Republic of)
- K.N.Toosi University of Technology Iran (Islamic Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).10 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
