The increasing share of fluctuating renewable energy sources on the world-wide energy production leads to a rising public interest in dedicated forecasting methods. As different scientific communities are dedicated to that topic, many solutions are proposed but not all are suited for users from utility companies. We describe an empirical approach to analyze the scientific relevance of renewable energy forecasting methods in literature. Then, we conduct a survey amongst forecasting software providers and users from the energy domain and compare the outcomes of both studies.
The rapid growth of renewable resources induces the need for new regulating and operating schemes in the power grid. Conventional power plants in the fleet impose their ramp-rate limits on the operation of these renewables to the point that, with a high-level integration of wind and solar resources, these ramp rate limits must be managed by situational awareness and curtailment mechanisms. These mechanisms depend on forecasts, especially those that consider the ramp events. This paper defines and implements a qualifying metric for the solar power forecasts to assess the capability of the forecasting models to predict the ramp events, especially by the combined forecasts. A case study is presented and the criterion is also used to evaluate the accuracy of the forecasts in terms of ramp events as well as to demonstrate the suitability of the forecasts in the applications that consider the ramp rates of solar power.
Berzelius failed to make use of Faraday's electrochemical laws in his laborious determination of equivalent weights.