Building the Sun4Cast System: Improvements in Solar Power Forecasting

Abstract

As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from the public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers. The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, which forms the basis of the system beyond about 6 h. For short-range (0–6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short- to midterm irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. This paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.

A Design for a Data and Information Service to Address the Knowledge Needs of the Water-Energy-Food (W-E-F) Nexus and Strategies to Facilitate Its Implementation

“…W-E-F Nexus-related information projects include the Vision on Technology for a Better World, a system that facilitates data processing and distribution and analyzes global trends affecting the W-E-F Nexus (https://vito.be/en), and the GIZ Water, Energy & Food Security Resource Platform (http://www.water-energyfood.org/). An example for the energy sector is a system being developed by Haupt et al (2018) to forecast solar energy outputs. The water sector is covered by the Aqueduct system, developed by the Water Resources Institute, which has more than a decade of experience in shaping outputs for those needing water risk assessment tools (http://aqueduct.wri.org).…”

Short-Range Forecasting for Energy

“…These improvements have stemmed from including observations in the immediate vicinity of the resource, both in the nowcasting and assimilated into the NWP models, as well as better methods of blending multiple models for the appropriate timescales. Solar power predictions have not been a focus for very long, but rapid improvement is also happening here (Lorenz et al 2009;2014;Tuohy et al 2015;Haupt et al 2017).…”

Assessment of Simulated Solar Irradiance on Days of High Intermittency Using WRF-Solar

“…All these changes have been incorporated in a specific augmentation of the advanced research version of the WRF Model [35] designed for solar energy predictions known as WRF-Solar [36]. WRF-Solar has been extensively tested in the USA [36][37][38][39][40][41] and other countries, such as Spain [42], Singapore [43], Kuwait [44], and Saudi Arabia [45]. Most studies have reported significant improvements in solar irradiance predictions under different sky conditions with WRF-Solar in comparison to standard WRF simulations.…”