Year: 2023
Type: preprint
Abstract: Renewable energy forecasting is the workhorse for efficient energy dispatch. However, forecasts with small mean squared errors (MSE) may not necessarily lead to low operation costs. Here, we propose a forecasting approach specifically tailored for operational purposes, by incorporating operational problems into the estimation of forecast models via designing a loss function. We formulate a bilevel program, where the operation problem is at the lower level, and the forecast model estimation is at the upper level. We establish the relationship between the lower-level optimal solutions and forecasts through multiparametric programming. By integrating it into the upper-level objective for minimizing expected operation cost, we convert the bilevel problem to a single-level one and derive the loss function for training the model. It is proved to be piecewise linear, for linear operation problem. Compared to the commonly used loss functions, e.g. MSE, our approach achieves lower operation costs.
Source: arXiv (Cornell University)
Authors: Zhang, Yufan, Wen, Honglin, Bian, Yuexin, Shi, Yuanyuan
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4387323672