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Finished intermediate february report + next steps from meeting

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Victor Mylle
2024-02-19 15:48:45 +01:00
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Reports/February/verslag.tex
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@@ -133,7 +133,7 @@
\section{Intermediate Results}
\subsection{Net Regulation Volume Moddeling}
\subsection{Net Regulation Volume Modeling}
Using a generative model, we try to predict the NRV for the next day. The model is trained on historical data and uses multiple input features to model the NRV. The data for the input features can all be downloaded from \href{https://www.elia.be/en/grid-data/open-data}{Elia Open Data}.
\subsubsection{Input Features}
@@ -181,7 +181,7 @@ Using the predicted NRV, a policy can be implemented to charge and discharge a b
\hline
\textbf{Policy} & \textbf{Total Profit (€)} & \textbf{Charge Cycles} \\
\hline
Baseline (charge: 150, discharge: 175) & 251,202.59 & 725 \\
Baseline (charge: €150, discharge: €175) & 251,202.59 & 725 \\
Baseline (yesterday imbalance price) & 342,980.09 & 903 \\
GRU Predicted NRV (mean thresholds) & 339,846.91 & 842 \\
Diffusion Predicted NRV (mean thresholds) & 338,168.03 & 886 \\
@@ -191,10 +191,23 @@ Using the predicted NRV, a policy can be implemented to charge and discharge a b
\label{table:energy_storage_policies}
\end{table}
The recommended charge cycles for a battery are <400 cycles per year. The policy also needs to make the charge cycles are below 400. A penalty parameter can be introduced and determined so that the policy is penalized for every charge cycle above 400. The policy can then be optimized using this penalty parameter. I am currenlty experimenting with this.
The recommended charge cycles for a battery is <400 cycles per year. The policy also needs to take this into account. A penalty parameter can be introduced and determined so that the policy is penalized for every charge cycle above 400. The policy can then be optimized using this penalty parameter. I am currenlty experimenting with this.
\newpage
\section{Schedule next months}
\begin{itemize}
\item Baselines with penalties for charge cycles above 400
\item Better visualizations of the policy profit results.
\item Case studies of days with extreme thresholds
\item Finetuning of models and hyperparametres based on model errors and profits of the policy
\item Ablation study of input features
\item Experiment further with diffusion models
\item During the experimenting, I will write my thesis and update the results and conclusions chapters.
\end{itemize}
\end{document}