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首页> 外文期刊>Indian journal of power and river valley development >Artificial intelligence to achieve reliabile operations at thermal power plants
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Artificial intelligence to achieve reliabile operations at thermal power plants

机译：人工智能实现热电厂的可靠运营

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Thermal power plants are complex entities with multiple systems interacting with a high stress environment. To ensure profitable operations, it is necessary that a plant stay functional round the clock irrespective of changing loads, fuel characteristics and environmental conditions. Traditionally reliability has been posed as an engineering and maintenance problem. This paper proposes a data centric approach that promises to vastly improve the efficacy of maintenance. Also, this paper provides details about setting up of an integrated system that can help detect degrading behaviour and identify root causes well before systems reach criticality. The primary components of this system are (ⅰ) data integration (ⅱ) scalable data processing and most importantly (ⅲ) artificial intelligence. Here artificial intelligence refers to mathematical processes that are capable of learning from examples and mimic human like intelligent behaviour. By building an integrated system, we also demonstrate how the infrastructure can then be extended to handle additional use-cases towards plant improvement like heat rate improvement, auxiliary power consumption optimization, etc. Finally, this paper will discuss a specific case where artificial intelligence is able to identify the cause for increased vibrations in a turbine in a captive power plant and how this leads to resolving the issue with zero downtime and no intrusive interventions resulting in significant savings. This case demonstrates clearly how data can be an invaluable resource when it comes to helping Indian power plants stay competitive in challenging market conditions and operate efficiently and reliably. Also, it is an example of inter-disciplinary collaboration: power generation experts and data mining experts working towards a common goal and achieving an outcome that would have been improbable otherwise.
机译：热电厂是具有多种系统的复杂实体，与高应力环境相互作用。为了确保有利可图的运营，无论载荷，燃料特性和环境条件如何，都必须围绕时钟的植物保持功能。传统上可靠性被构成为工程和维护问题。本文提出了一种以数据为中心的方法，有助于大大提高维护的效果。此外，本文提供了有关设置集成系统的详细信息，可以帮助检测劣化行为，并在系统达到临界之前识别根本原因。该系统的主要组件是（Ⅰ）数据集成（Ⅱ）可扩展数据处理，最重要的是（Ⅲ）人工智能。这里的人工智能是指能够从示例和模仿人类等智能行为的数学过程。通过构建集成系统，我们还展示了如何扩展基础设施以处理额外用例，以便促进厂家改善，如热速率提升，辅助功耗优化等。最后，本文将讨论人工智能的特定情况能够识别俘获电厂中涡轮机中振动的原因以及这导致如何解决零停机时间，并且没有侵入性的干预措施，导致显着的节省。此案清楚地展示了如何在帮助印度发电厂保持竞争力的挑战性市场条件下，数据可以是无价值的资源，并有效可靠地运营。此外，它是跨学科合作的一个例子：发电专家和数据挖掘专家，努力实现共同的目标，并达到否则将不可能实现的结果。

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