Tri-generation investment analysis using Bayesian network: A case study

ABSTRACT

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

Acknowledgments

We thank the experts from Istanbul Technical University Energy Institute for their valuable contributions to this work. The authors thank the Editor, Xianguo Li, and anonymous reviewers for their valuable comments and suggestions that have helped us to improve this paper.