Research mini-projects, 1. Probabilistic forecasting of maximum wave height ; 2. Optimal sizing and operation of battery storage at ray wind farm

  • Ahmed el-Bozie

Student thesis: Master's Thesis

Abstract

1. Accurate forecasting provides a great deal of financial benefits and mitigation of risks in the shipping industry, as well as the operation and maintenance of marine energy systems. Forecasting maximum wave height over significant wave height gives a more thorough depiction of the sea state with respect to safety. Moreover, the probabilistic model's distribution illustrates the uncertainty in the forecast which allows for safer decision making. Linear models are produced and verified using continuous ranked probability score, mean absolute error and the pinball loss function. The data used to train the models consists of measured data, which is obtained from the FINO1 platform, and numerically forecast data from the Met Office database which is produced using the WAVEWATCH III R numerical model of the National Centres for Environmental Prediction. The models are trained to predict a mean value of the maximum wave height. The residuals are then used to calculate the variance and fit a distribution around the mean values that are predicted. The prediction performance of both linear models produced is compared and is found to be very similar. Further work is suggested in comparing the models to numerical weather predictions and considering other models for prediction.;2. This study provides an outline for the inclusion of a battery at a wind farm to offer flexible generation and allow for a higher fraction of distributed renewable energy on the grid. Many applications for batteries are considered, this study focuses specifically on the correction of forecast errors. Battery technologies are briefly discussed, particularly comparing the widespread Li-ion battery to the Vanadium Redox Flow Battery, which was chosen for this study. The strategy compromises on continuous error correction and designates the optimal times to correct forecast error based on price data. The assumption made with regards to the ability for battery charge/discharge from the grid is proven to be detrimental to the effective use of the battery. It is suggested that this assumption is omitted in further work and that ancillary service provision is considered as a revenue stream when the battery is not being used to correct forecast errors.
Date of Award2 Dec 2019
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsEPSRC (Engineering and Physical Sciences Research Council)

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