|
|
The forecast module (ic-fc) is conceived to provide a clear characterization of the most common forecasting data. During the ontology requirement specification process with the InterConnect partners, we noticed that a distinction was needed between point forecasts versus stochastic forecasts, as well as the various ways to express stochastic forecasts. Therefore, the ic-fc module takes into account this distinction. It reuses the ic-data module (see Section 4.2), which defines time-series and data-points that are important elements of forecasting. It also reuses the ic-topology module (see Section 4.9), which defines the forecast location (geographical but also topological, for example, the grid segment). Figure 7 shows the concepts that we designed for defining forecasts. In order to keep the figure readable, we focused on the new concepts and we did not extensively visualize the concepts already presented in Figure 6.
|
|
|
The forecast module (ic-fc) is conceived to provide a clear characterization of the most common forecasting data. During the ontology requirement specification process with the InterConnect partners, we noticed that a distinction was needed between point forecasts versus stochastic forecasts, as well as the various ways to express stochastic forecasts. Therefore, the ic-fc module takes into account this distinction. It reuses the ic-data module, which defines time-series and data-points that are important elements of forecasting. It also reuses the ic-topology module, which defines the forecast location (geographical but also topological, for example, the grid segment). The following figure shows the concepts that we designed for defining forecasts.
|
|
|
|
|
|
![Forecast.drawio](uploads/0a573923454b8199b0f0589430819425/Forecast.drawio.png)
|
|
|
|
... | ... | |