It has been well established in the literature that surface contamination can adversely affect the aerodynamic performance of aerofoils and hence the efficiency with which turbines can convert wind to electrical power. Hence it is critical to ensure that turbine blades are kept as free as possible of contaminants. In this manuscript, we discuss LIBS and machine learning techniques on contaminated wind turbine blades with a view to the possibility of integrating these methods into a standoff laser ablation setup in the future. A LIBS signal will be a key step in the decision process, i.e., to determine if a wind turbine blade has been fouled in the first place. Relatedly one must also determine the point at which the laser has adequately removed contaminants from the current Area of Irradiation (AoI) before moving to the adjacent AoI, i.e., interim end-point-detection. For both steps (presence / absence of fouling) we are investigating laser-induced breakdown spectroscopy (LIBS) to discriminate clean from fouled wind turbine blade samples. In particular we have performed LIBS in both the Vacuum Ultraviolet (VUV) and Ultraviolet Visible (UV–Vis) spectral ranges. Analysis of the spectra showed only slight variations in the constituent materials between clean and contaminated blade samples. In order to address this challenge, the efficacy of a number of machine learning and statistical methods for clean versus contaminated blade classification was investigated. Four methods (Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machines (SVM), Competitive Learning (CL), and Convolutional Neural Networks (CNN)) were evaluated. The spectral regions where machine learning algorithms were applied was determined via a volumetric ellipsoid overlap test based on Principal Component Analysis (PCA). It was found that SVMs provided the most accurate methodology for binary classification of clean vs contaminated blades whilst also yielding the shortest run time.

Abstract International wild Atlantic salmon management priorities have moved from exploitation to conservation since the 1990s, recognizing the need to protect diversity and abundance at individual river levels amid widespread declines. Here we review international salmon-stock assessments and describe a simple, transferable catch-advice framework, established for management of fisheries that conforms to international obligations. The risk assessment approach, applied at the river scale, jointly incorporates uncertainty in estimated and forecasted returning salmon numbers with the level of uncertainty around spawning requirements (Conservation Limits). Outputs include quantification of risk of stocks not attaining conservation limits (CL) and surpluses above CL on stocks able to support sustainable exploitation via total allowable catches (TAC), with monitoring by rod catch or fish counter. Since management implementation and cessation of at-sea mixed-stock fisheries, there has been a deterioration in the performance of many individual stocks, without any sustained increase in fisheries open to harvest. Given declines in mid-latitude Atlantic salmon populations over 30 years, the novel framework presented provides an approach to protect stocks failing to meet spawning thresholds while supporting sustainable exploitation of those achieving them. On-going management policy of adopting scientific advice and allowing exploitation only on stocks exceeding CLs is central to the objective of protecting salmon stocks.

Substation Automation Systems are commonly used to control, protect and monitor substations in a power system. Many existing substation automation systems use proprietary protocols, which are no longer supported. Therefore, expensive and complex solutions are often required when automation equipment fails or reaches the end of life (15/20 years), or a substation extension is required. Older proprietary-based protocols in substation automation systems are being updated and replaced by introducing the IEC 61850 standard series.IEC 61850 brings significant changes to how Intelligent Electronic Devices used for protection are to be tested. The introduction of non-traditional relay signals resulted in the need for new tools and processes regarding commissioning, testing and maintenance.This paper provides an overview of existing proprietary protocols and outlines the IEC 61850 standard. The challenges in testing IEC 61850 protection equipment are investigated. Finally, a power utility approach for extending existing legacy substation automation systems is demonstrated in a lab-based trial. The comparison illustrated the many benefits of installing and extending substations using IEC 61850 rather than reengineering the proprietary systems.

High-Temperature Low-Sag (HTLS) conductor technologies are often implemented, among many approaches, for optimizing the overhead lines utilization. The advancements of HTLS conductors are based on the differences in core and aluminum properties and installation procedures. This non-linear conductor behavior, although considered in the sag-tension calculations, by implementing the knee-point temperature, is often omitted from the aeolian vibration calculations. To understand the implications of the complex HTLS conductor structure on vibrations, a new calculation approach is proposed in this paper to quantify the effect of installation and operating conditions on the performance of any HTLS conductor. The proposed method conceives a prediction lay area that estimates where the actual field data are expected to lay, and is validated with good accuracy against the field data from ACSR, ACCC, and GZTACSR. The developed model enables the prediction of non-homogeneous (composite) conductors and should be implemented at above knee-point operating temperatures with zero aluminum tensions