Discussion of Parameters Setting for A Distributed Probabilistic Modeling Algorithm
Mengshuo Jia, Chen Shen, Zhiwen Wang
TL;DR
This paper discusses how to set parameters for a distributed probabilistic model used to forecast wind power errors, providing insights for improving model accuracy.
Contribution
It offers an in-depth analysis of parameter settings specific to a distributed probabilistic algorithm for wind power error prediction.
Findings
Parameter choices significantly impact forecast accuracy
Guidelines for optimal parameter settings are proposed
Enhanced understanding of model behavior with different parameters
Abstract
This manuscript provides additional case analysis for the parameters setting of the distributed probabilistic modeling algorithm for the aggregated wind power forecast error.
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Taxonomy
TopicsEnergy Load and Power Forecasting · Electric Power System Optimization · Integrated Energy Systems Optimization