Summary
It has been almost 15 years since concerns about the limited capacity of remnant native vegetation to supply the volumes of seed required to meet increasing restoration demands were first raised. Since that time little progress has been made towards addressing this constraint with the ongoing decline of native vegetation communities, especially since 2000, further challenging seed supply. We provide examples of the size of this demand for seed, as well as major issues associated with seed sourcing. We also discuss how invoking the concept of market forces to drive seed supply and demand is inappropriate and highlight the need for an industry body to oversee seed collection and utilisation standards. We further propose key actions that are required to secure the seed supply chain within the next 20 years to meet existing and future restoration targets. We argue that concerted, coordinated action at Commonwealth, State and regional levels are required to underpin effective future restoration outcomes.
Intensive condition monitoring of wind generation plant through analysis of routinely collected SCADA data is seen as a viable means of forestalling costly plant failure and optimising maintenance through identification of failure at the earliest possible stage. The challenge to operators is in identifying the signatures of failure within data streams and disambiguating these from other operational factors. The well understood power curve representation of turbine performance offers an intuitive and quantitative means of identifying abnormal operation, but only if noise and artefacts of operating regime change can be excluded. In this paper, a methodology for wind turbine performance monitoring based on the use of high-frequency SCADA data is employed featuring state-of-the-art multivariate non-parametric methods for power curve modelling. The model selection considerations for these are examined together with their sensitivity to several factors, including site specific conditions, seasonality effects, input relevance and data sampling rate. The results, based on operational data from four wind farms, are discussed in a practical context with the use of high frequency data demonstrated to be beneficial for performance monitoring purposes whereas further attention is required in the area of expressing model uncertainty.
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