How new climate modeling can shape the renewable energy landscape
Interchange Recharged
Wood Mackenzie
4.8 • 535 Ratings
🗓️ 27 October 2023
⏱️ 33 minutes
🧾️ Download transcript
Summary
New forecasts for weather patterns could help the solar and wind industries make better investment decisions in the long term.
Climate trends are accelerating rapidly. Global temperatures hovered consistently at around 1.5 degrees above pre-industrial levels from January to August. Then in September, they shot up to 1.8 degrees. Dr Zeke Hausfather, research scientist at Berkeley Earth, opined in a recent NYT piece that global warming has actually accelerated in the last 15 years, rather than continuing at a gradual pace.
The effects of climate change are no longer something for the next generation to worry about; they’re being felt here, and now. As a result, it’s crucial to deploy renewables as quickly and efficiently as possible. This involves continuing to invest in the two largest sectors – wind and solar.
There’s a strong correlation between the effectiveness of these energy sources and the weather predictions we make to inform our long-term planning and investment decisions.
Anticipating and planning for variability in supply and demand comes from analyzing historical weather and climate data.
On the Interchange Recharged today, we are joined by Rob Cirincione, founder and CEO of Sunairio. They have a model which they say can make better predictions for solar and wind demand and supply, helping the industry to make better investment decisions and deploy more quickly.
Traditionally, historical data has been the primary tool for making predictions about future weather events and their possible impact on supply-demand imbalances. Historical data has its limits and does not always provide an accurate representation of future weather events. With climate change accelerating faster than we thought, and with a limited amount of historical data available, there’s a need for modeled projections to fill this gap.
For instance, in the solar industry, historical average models like the typical meteorological year (TMY) are used to predict future performance and returns. However, the assumption that the climate is the same as it was when the model was developed is flawed. Therefore, it's essential to continually measure and observe the impact of climate trends on irradiance and thus, the performance and returns of solar projects.
Rob explores the tools used to predict weather-driven variability in energy, what the solar industry currently uses to predict long-term performance, how to apply the predictive model Sunairio is developing to make better investment decisions, and how progress with decarbonisation efforts could impact future forecasts.
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00:00:00: Introduction to the show
00:00:01: Rob's career and the start of Sunairio
00:00:06: The weather's impact on energy supply and demand
00:00:37: Tools used to predict weather-driven variability in energy
00:01:01: The limitations of using historical weather data
00:01:47: The reason for creating Sunairio
00:02:02: Sunairio's role in the industry
00:03:18: Investment analysis and planning in regards to weather events
00:03:32: Current practices in solar industry
00:04:38: Flaws in using historical data for future predictions
00:07:18: The impact of changing climate trends on the solar performance
00:09:02: The importance of this analysis for investors and project managers
00:09:30: The risk of production underperformance in renewable projects
00:10:49: Sunairio's use of statistical climate model for predictions
00:11:16: Discussion on weather forecasting and its impact on energy production
00:12:20: Using statistical approach in climate modeling for energy production
00:12:42: Applying the predictive model in decision-making
00:14:27: The forecasted production gap and how it affects renewable energy goals
00:16:13: Coverage and capabilities of the modeling system
00:17:49: Expansion and future expectations for the renewable energy markets.
00:20:01: Geographical challenges and solutions in energy production
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Transcript
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| 0:00.0 | This is The Interchange Recharged, a Wood McKenzie production. |
| 0:04.4 | I'm David Banmiller. |
| 0:10.8 | Staggering, unnerving, mind-boggling, absolutely gobsmackingly bananas. |
| 0:18.9 | Those are the words Dr. Zeke, Housefather, used to describe the climate data he analyzed in a recent piece for the New York Times. |
| 0:30.6 | It was another year of record temperatures. |
| 0:34.6 | Data from Berkeley Earth showed September almost a full degree Fahrenheit |
| 0:39.0 | hotter than the previous record. 2023 is likely to be the hottest year since records began |
| 0:45.4 | over 150 years ago. Where have we heard that one before? It's against this backdrop of a rapidly |
| 0:51.8 | changing climate that we focus today on the importance of climate modeling for renewables. |
| 0:57.0 | Solar and wind still lead the way when it comes to renewable energy investment. |
| 1:02.0 | Efficient use of these renewables is linked to the ability to anticipate and plan for the variability in supply and demand. |
| 1:09.0 | Traditionally, historical data has been the primary tool for predicting future weather events |
| 1:14.6 | and their impact on supply, demand, and balances. |
| 1:17.6 | Historical data, though, has its limits. |
| 1:20.6 | Climate change and the limited quantity of available historical data |
| 1:24.6 | is reducing the accuracy of weather predictions, and in turn, |
| 1:29.3 | demand and supply implications for wind and solar. |
| 1:33.0 | Scenario is a startup that says they have a solution. |
| 1:36.3 | Rob Serencion is founder and CEO of Scenario. |
| 1:39.3 | If you're a vertical utility and you're responsible for serving your customer's demand |
| 1:44.0 | hour by hour for the whole year |
| 1:45.9 | for a planning period, you need to ensure that you have enough generation to meet that |
... |
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