From condition monitoring to maintenance management in electric power system generation with focus on wind turbines

Abstract

With increase in the number of sensors installed on various industrial components and hierarchical levels, the amount of data collected is rapidly increasing. Therefore, extracting the knowledge from the data can bring about significant improvements in asset management (component level) and organization operation (system level). This paper provides a path for achieving such an objective. In the first stage, it analyzes the data collected at the sub-assembly level in an industrial component and creates four frameworks for operation and maintenance (O&M) analysis. These frameworks address past, present and future horizons. The outcomes of the frameworks are improvement in operation, maintenance planning, efficiency and performance of the components and cost reduction. In the second stage, a link to integrate the developed component level frameworks with system level operation is created. This integration delivers additional improvement in operation and risk reduction since it connects the changes in the condition of the component, extracted from the collected data, to the operation of the system. In the third stage, to advance preventive maintenance scheduling in power system generation, the previously developed component level frameworks and the link between component and system levels are combined with criteria such as electricity markets and uncertainty in demand and wind. In particular, studies on strategic operation and maintenance planning in regulated and deregulated power systems, offshore wind farms and microgrids are carried out. The paper delivers an insight on how direct integration of the collected operation data from the component level can bring about benefit for market agents, asset owners and system operators. These benefits include increase in profit and savings and reduction in costs.