Dynamic failure analysis of renewable energy systems in the remote offshore environments

Abstract

For effective integrity management of marine renewable energy systems in the dynamic and uncertain ocean environments, understanding the failure dynamics is crucial. The cost of investment in marine/offshore renewable energy infrastructures and the associated cost due to failure and loss of energy production necessitate a predictive monitoring methodology that is dynamic and adaptive. This paper presents an integrated multi‐state pure‐birth‐pure‐death Markovian‐net profit value model for the offshore turbine subsystem failure analysis and its cost‐based consequences. The integrated model captures the offshore turbine subsystem's dynamic failure states and its economic implications due to the cost of energy loss and downtime for the period under consideration. The model applies a phase‐type exponential distribution to describe the monotonic state of failure. The methodology is demonstrated with an offshore wind turbine gearbox, and it captures the dynamic state of the system and its failure mechanisms. The cumulative effect of the subelements deterioration decreases the gearbox performance by over 35% within the first 2 years of operation.

A fatigue reliability assessment approach for wind turbine blades based on continuous time Bayesian network and FEA

“…Though the blade root withstands a greater stress, some reinforcement measures are often applied in the stages of design and manufacturing, thus the safety and reliability are improved 39,40 . Leading edge and trailing edge are the bonding areas of the upper and lower shells, and their failures are mainly caused by environmental factors, such as rain erosion, salt spray, etc., but not only the alternating cycle stresses 41,42 . Thus the local fatigue failure in leading edge or trailing edge, combined with the environmental factors impact analysis, requires more in‐depth study.…”

“…39,40 Leading edge and trailing edge are the bonding areas of the upper and lower shells, and their failures are mainly caused by environmental factors, such as rain erosion, salt spray, etc., but not only the alternating cycle stresses. 41,42 Thus the local fatigue failure in leading edge or trailing edge, combined with the environmental factors impact analysis, requires more in-depth study.…”

A Prescriptive Model for Failure Analysis in Ship Machinery Monitoring Using Generative Adversarial Networks

“…White box models are widely used, as they are characterized by their explicit mathematical equations and parameters, which have real-world interpretations. They are commonly used in reliability analyses [15] and failure analyses [16].…”

Deep reinforcement learning for resilient microgrid expansion planning with multiple energy resource

“…Renewable energy has become the preferred technology for power and various energy terminal applications. 12 At present, China is committed to realizing a new power system with renewable energy as the main body, and hopes to realize that the proportion of renewable energy in the power system will reach more than 50% in the future. 13 Although in most regions, solar photovoltaic or wind energy has become the cheapest renewable energy resource, 1 the fact that real power generation of renewable energy reaches 50% of total power generation is not as simple as raising their installed capacity up to 50% of total energy installed capacity.…”

“…Renewable energy has become the preferred technology for power and various energy terminal applications 12 . At present, China is committed to realizing a new power system with renewable energy as the main body, and hopes to realize that the proportion of renewable energy in the power system will reach more than 50% in the future 13 .…”