As China gradually phases out its subsidy policy for offshore wind power (OWP), the industry has entered a decisive cost reduction and efficiency enhancement stage. Unlike onshore wind projects, OWP projects still face substantially higher construction and operating costs, which makes competitiveness under grid-parity conditions highly challenging. However, the theoretical framework for managing the smart lifecycle of OWP projects remains underdeveloped, with incomplete asset management and evaluation methods. The smart lifecycle management of OWP projects is in its nascent stage, with fragmented data systems and poor integration across planning, construction, and operations. Consequently, there is an urgent need for an innovative, lifecycle-oriented management approach to support the OWP industry's high-quality and sustainable development.

This study proposes a closed-loop smart management mechanism for OWP projects, focusing on four key dimensions: perception, analysis, real-time control, and optimization. This study summarizes the digital transformation and smart management pathways of OWP assets throughout their lifecycle, from feasibility to construction, operation, and final decommissioning. This study classifies management elements into cost, efficiency, and risk, creating a closed-loop evaluation model for OWP assets. This model enables a dynamic representation of each asset's status in terms of cost, efficiency, and risk levels at any moment. Furthermore, this study identifies and analyzes key smart management technologies relevant to various phases of the lifecycle. Accordingly, a smart lifecycle management platform has been designed with a five-layer architecture: data acquisition, data management, modular functional applications, decision support, and interactive visualization. A prototype system was developed to address project development and design, smart construction, and smart operation and maintenance. The system was applied in a large offshore wind farm in Jiangsu Province, China, and the asset conditions were compared before and after its implementation.

A comparative analysis based on actual operational data showed significant improvements: (1) Effective cost control was achieved during the construction period, along with rational planning for operation and maintenance, reduced downtime, and improved generation efficiency. Thus, the lifecycle levelized cost of energy decreased from 0.92 yuan/(kW·h) to 0.76 yuan/(kW·h), which was approximately 17.4%. (2) When evaluated against three key efficiency indicators—compliance rate of power generation, effective operation time assurance rate, and average failure rate—the poorly performing turbines (#3, #10, and #16) showed significant improvements after rectification, with lower osculating values. (3) Comprehensive risk assessment identified anomalies in the transmission and blade systems as primary concerns, which allowed for targeted maintenance interventions, improved equipment availability, and reduced unplanned maintenance requirements.

The proposed closed-loop smart lifecycle management system offers a new technical solution for reducing costs and improving efficiency in OWP projects. Practical application shows that the system can enhance project planning and design, reduce development and operational costs, improve asset equipment reliability, extend the power generation lifecycle, and ensure ongoing value creation throughout the lifecycle. The study findings offer valuable guidance for smart management in similar offshore renewable energy projects, thereby contributing to the sustainable development of the wind power industry through digital transformation.