Applying Prescriptive Analytics to Enhance Asset Value in a Complex Operating Environment

摘要

A number of industries have been transformed by the wave of digital innovations, big data, analytics and computing; more recently, the power industry has begun to selectively apply these digital technologies to drive better economic outcomes for existing and greenfield power plants. These disruptive technologies are arriving at a time when the power industry is encountering dramatic market dynamics resulting from changes in fuel prices, increases in renewables coming on line, and changes in the regulatory environment. The challenges of managing power generation plants have become more complex—complicated system interactions, more co-optimization demands, and more operating profile flexibility. This convergence offers power producers an opportunity to embrace technology to re-position the competitiveness of their plant operations. This paper demonstrates how today’s power operators can use a modern ecosystem to provide on-going operational productivity—protecting against downside risk while constantly pursuing upside opportunities and increasing economic value while reducing total cost. The paper will cover a brief history of big data and applied analytics usage in power plants today, as well as the dynamics in the industry that have created new operational complexities. We present a maturity model that provides a roadmap for end users to advance through different stages of applied analytics to drive incremental and sustained productivity. We then discuss the obstacles to implementing this maturity model while specifically recommending how to progress to prescriptive analytics within the Industrial Internet architecture, moving from business applications in the cloud down to the controls layer.