The weather factor: how temperature and wind drive power prices

Frustratingly, the weather impacts both energy demand and generation: as the weather gets colder, demand spikes increase, and as the temperature hits freezing, it affects generation.

Any industry that relies on natural forces will feel the effects of the weather’s volatility. As a warming planet results in more unpredictable and violent weather patterns, climate change increases that volatility.

Luckily, there are technological and financial tools that can help to predict how the weather might impact pricing. We will look at some of these tools, such as forecasting and hedging approaches, and how they might impact on power pricing.

Why weather is the single biggest short-term price driver for energy

While the longer-term impacts of weather on power pricing have the potential to shape how the energy industry evolves, the short-term effects can be felt just as keenly.

Daily, weekly, and seasonal effects

Energy prices can vary on a shorter-term basis, particularly with regard to consumer-led effects. This is because the effects of the weather and impact on how consumers use energy, for example, daily, colder days can increase energy demand, but if there is no wind, it can reduce the output of wind energy, putting a strain on renewable resources and driving prices up as less energy is available but more energy is required. On a weekly basis, a lack of wind or a ‘wind drought’ can reduce the amount of energy generated without a dip in demand, causing a spike in energy pricing. From a seasonal perspective, wind energy output can be at its lowest during the summer months due to extreme heat and lack of wind, which can cause supply and demand problems and further exacerbate pricing. 

Weather sensitivity vs. fuel price sensitivity

When the renewable share of the market increases and becomes more competitive with fossil fuels, it can alleviate fuel price sensitivity. Wind energy can help smooth out volatility in the energy market because it doesn’t have the direct fuel costs associated with fossil fuels. When fuel prices in fossil sources increase, wind can be a more competitive, zero-fuel-cost alternative. This is reinforced when an extreme weather event, such as a storm or high winds, increases the amount of wind power generated, making wind energy even more competitive.

How temperature affects demand and load curves

Load curves are calculated by subtracting renewable energy generation from electricity in relation to net load, showing how it changes daily and how it’s impacted by storage and demand response. 

Cooling/heating degree days and elasticity

When temperatures are cooler or hotter than usual, they can cause an increase in demand for energy, which can affect the load curve. This can be due to a cold period, which increases the demand for energy during certain times of day, for example, the evening when consumers return from work and school. 

Heatwave and cold snap case studies

The load curve can be flattened when we move temperature-sensitive loads away from peak times. For example, suppose a manufacturing facility can adjust its air conditioning use to kick in during off-peak periods. In that case, it can lessen the demand on the grid, particularly when residential consumers are also requiring air conditioning, flattening the curve.

The role of wind, solar, and hydro variability

The effect of high renewable energy output is connected to pricing. There is a correlation between output and price dips as more renewable energy floods the market and unbalances more expensive fossil fuel alternatives. This is because of merit-order: lower running costs and increased amounts of renewable energy outstrip the pricing for energy-intensive and higher-cost fossil fuels.

This can become an issue if the market is flooded with renewable energy, for example, wind energy during a high-wind storm, as it can lead to negative pricing. However, hydro storage can step in as a stabilising force by storing excess wind energy until it can be used when wind energy output is low. It does this by using the excess and energy to pump lower-level water to a higher level in a hydro reservoir. 

Low-wind and solar events, also known as ‘dunkelflaute’ events, occur during periods of low renewable output and can cause price spikes. This is the ideal scenario to use hydro storage solutions.

Forecasting weather impacts on prices

Watching and learning from how power plants operate during extreme weather events can help companies prepare for and mitigate the risks associated with investing in renewable energy in the future. The use of both real-time and historical data can integrate meteorological data into market models and predict how pricing might change based on current and past extreme temperature events. Artificial intelligence can take modelling one step further, automating data analysis, manipulation and algorithm production. Leveraging AI-based forecasting can help address unknown factors, such as monitoring confidence intervals, particularly in predicting pricing behaviour during heatwaves.

Coping with climate change and more extreme events

As the effects of climate change are felt more keenly around the world, the energy industry is one of the key industries to be impacted. While extreme weather can lead to higher output of renewable energy, it can also cause infrastructure damage and reduce opportunities for maintenance, resulting in increased maintenance costs and insurance implications. It’s therefore crucial to invest in flexibility and resilience, including initiatives such as machine health monitoring, to forecast and plan for predictive maintenance before issues occur. Weather will always move markets, but understanding its rhythms is key to energy risk management.