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Tri-generation investment analysis using Bayesian network: A case study
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DOI：10.1080/15435075.2018.1454321.png)
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Abstract
En 中文
The increasing energy demand, increasing energy dependency, energy supply security, and environmental concerns have become a part of business policies since COP21 agreements in Paris, 2015. Combined cooling, heating, and power (CCHP or tri-generation) systems play an important role in paying the necessary attention to these policies. Tri-generation investment is a complex decision with hybrid use of energy resources. This article aims to reduce the complexity of this decision by the use of Bayesian belief networks in pre-investment stage of tri-generation investment project cycle. The proposed model gives an insight into decision analysis and helps the decision-makers either generate or purchase from it in order to meet the energy demand with different scenarios. The model is studied for a university case. The investment decision for a CCHP (tri-generation) system will be discussed as an alternative for purchasing the electricity and natural gas from the national grids.
Keywords:
Bayesian belief network
decision-making
scenario analysis
tri-generation
tri-generation investment
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