waaree december

Singapore Optimises Its Power Grid Resilience Via Solar Forecasting Tools


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The Solar Forecasting Model trial to predict solar fluctuation and improve Singapore’s power grid adaptability has finally been accomplished. 


The model, which was supported by the Energy Market Authority (EMA) and the Meteorological Service Singapore (MSS) of the National Environment Agency (NEA), completed its one-year trial in September this year at the EMA’s Power System Control Centre. Being the first of its kind, this model can actually anticipate Singapore’s island-wide solar irradiance up to 60 minutes in advance, with an average error rate of less than 10%. This is one of the lowest in the tropics for solar forecasting.

The Solar Forecasting Model utilizes data from real-time irradiance sensors installed on rooftops of buildings and electrical substations across Singapore. It also incorporates numerous dynamic solar forecasting techniques such as satellite imagery and machine learning algorithms. Combining outputs from MSS’ numerical weather prediction system, known as SINGV, the Solar Forecasting Model is able to aggregate the various types of data to generate round-the-clock solar irradiance forecasts at regular intervals from 5 minutes to 24 hours ahead of schedules.

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Solar power generation cannot be moderated as per the energy demand. Its power generation is dependent on Singapore’s tropical weather conditions which fluctuate depending on environmental factors. This can lead to imbalances between electricity demand and supply output from solar photovoltaic systems.

The Model would enable the EMA, as Singapore’s power system operator, to forecast solar energy output in advance and take proactive measures to control solar intermittency and balance the electricity network. This is another step toward ensuring grid reliability as Singapore’s solar deployment gradually expands.

Mr. Ngiam Shih Chun, Chief Executive, of EMA said that Singapore aims to deploy at least 2 gigawatt-peak (GWp) of solar capacity by 2030, in tandem with the Singapore Green Plan 2030, and to advance Singapore’s energy transition. A dependable solar forecasting model that predicts solar irradiance will improve Singapore’s grid resilience and flexibility while also facilitating the deployment of additional solar capacity. 

He further added, “This contributes to our solar goals while also trying to improve the resilience of our power grid.”

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Dr. Thomas Reindl, Deputy Chief Executive Officer at SERIS, who led the project team stated, “Forecasting of solar irradiance is increasingly being required by Asian power grid operators from owners of large-scale solar power systems. Therefore, the developed model has strong potential to be scaled up and commercialized to support the operations of solar farms across the region.”

Soon after the completion of this trial, EMA will be upgrading its Energy Management System (EMS) in order to incorporate solar generation forecasts by the Solar Forecasting Model by 2023.


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