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

机译：使用贝叶斯网络的三代投资分析：一个案例研究

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摘要

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.
机译：自2015年巴黎COP21协议以来，不断增长的能源需求，日益增长的能源依赖性，能源供应安全和环境问题已成为商业政策的一部分。制冷，供暖和发电（CCHP或三代）联合系统起着重要作用对这些政策给予必要的重视。三代发电投资是一项混合使用能源的复杂决定。本文旨在通过在三代投资项目周期的投资前阶段使用贝叶斯信念网络来降低此决策的复杂性。提出的模型可以深入分析决策，并帮助决策者从中生成或购买决策，以便满足不同情况下的能源需求。针对大学案例研究了该模型。将讨论CCHP（三代）系统的投资决策，作为从国家电网购买电力和天然气的替代方案。

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