Energy Innovation: A Focus on Power Generation Data Capture and Analytics in a Competitive Market

Abstract

Efficiency, operational flexibility, durability, environmental friendliness, and reliability — these words are often used to define expectations and requirements for product performance, required in the energy market today. Yet, depending on where one looks at the curve of product evolution, these words have very different meanings. One thing remains constant, irrespective of where one looks at performance growth over time, product improvement requires actual field experience data on a number of operating plants and units, to supplement the testing and verification processes of the Original Equipment Manufacturer (OEM). The combination of the field experience with the latest testing, verification, and quality control techniques, followed by the OEM, is essential to achieve the inherent reliability and ultimately, the life-time expectations set by the market. There is always a question as to the amount of actual field experience data that is necessary to validate product improvement or advancement. Today, the market seems to accept a lower standard of operating time (∼ 8,000 Actual Operating Hours (AOH)), compared with the past (∼ 100,000 AOH) for product validation. If Equivalent Operating Hours (EOH) were the basis for assessing the maturity of a new technology, the times would be lower. Whether the number is 8,000 or 100,000 AOH, the fact is that field experience data represents the intersection of the OEM’s design, validated through component and system level testing, coupled with the actual operating and maintenance practice and experience of the owner/operator. It is here that the OEM and owner/operator begin to directly share a common objective; the ability to demonstrate the efficiency, operational flexibility, durability, environmental friendliness and reliability of the product improvement. Consequently, the OEM and the owner/operator have a strong and shared interest in the accuracy, fidelity, and the completeness of field data; to ensure that an effective Failure Reporting and Corrective Action (FRACA) process is in place — driving continuous product improvement; to meet market expectations for equipment performance, and to support new product introduction. The focus of this paper is field experience data, past and present, with a specific emphasis on the increasing influence and value that data has in the ever changing and competitive energy market. The paper will suggest that the present and future need for high fidelity equipment data (at a component level of detail) is not just essential for supporting engineering efforts for product evolution, but also to support effective Operations & Maintenance (O&M) strategies. The paper will advance the notion that the fusion of total plant data, from three primary sources, with the ability to transform, analyze, and act based on integrating subject matter expertise is essential for effectively managing assets for optimum performance and profitability; executing and delivering on the promise of “Big Data” and advanced analytics.