At this week’s seminar Paulina Rowińska explored some of the methods used in energy finance, their applications and limitations. One specific topic she covered was a model that takes into account the impact of wind energy production on electricity prices, the topic of today’s blog post.
I bet you are not looking forward to your monthly electricity bill: can you predict how much they will charge you this time?
The field of quantitative energy finance emerged as a result of the gradual liberalisation of electricity markets. Mathematicians struggle to find a universal model for energy prices, because not only do market rules in various countries differ significantly, but also relevant laws frequently change.
Many perceive financial mathematics as difficult, not without a reason. Stock values change in unpredictable ways, they also strongly depend on political events and human behaviour. These challenges attract increasing numbers of mathematicians with different backgrounds. Actually, not only mathematicians: the so-called Brownian motion, which serves as a building block for many financial models, was first used by physicists to describe chaotic movement of particles. Only our imagination limits the tools we can apply!
Energy markets behave differently than traditional stock exchanges. As opposed to other financial instruments, the demand and supply for electricity must always match because of the high cost and inefficiency of energy storage. On the other hand, industry and citizens require a~specific amount of power for their regular activities, making the demand inflexible. Significant imbalances in the energy market cause losses or blackouts. What does it mean for you? No Netflix, no microwaved dinner, or a high energy bill, both of which I would rather avoid.
Thankfully mathematicians work hard to make sure that you do not have to dig out these candles too often. Mathematical models help producers decide how much energy to generate and traders to buy and sell its appropriate amounts.
In electricity markets one can trade two main types of contracts:
- Spot contracts (usually traded at noon) oblige producers to deliver a specified amount of energy for 24 hours, from midnight of the following day.
- Futures contracts determine the price of electricity delivered during a specified period: a week, a month or a year. For example, if a producer signs a “one month ahead” contract in November 2018, they would have to deliver the electricity between 01-12-2018 and 31-12-2018.
However, predicting the prices so far in the future can get difficult, because we do not know the general state of economy or politics at this time. And, what interests me most, the state of the weather.
Weather conditions significantly influence electricity prices, both the demand and supply. In countries like the UK or Germany, the demand increases in cold months, when we need to heat our houses and offices, as well as switch on the lights more often. In warmer places, hot summers require a lot of energy for air-conditioning. On the supply side, renewable energy production strongly relies on the weather: we cannot generate wind energy without wind!
Because of that my model of electricity prices includes weather-related variables, in particular forecasts of wind energy production. As you might have learned the hard (probably wet or cold) way, weather forecasts have high uncertainty, which I also need to take into account. In my research I use stochastic processes which describe probabilities of events, for example of particular electricity prices.
You might wonder if in practice wind energy really influences electricity prices. It does!
Now many markets even allow negative prices, which means that sometimes we can get paid for the electricity usage. It happens rather rarely, so you will not even notice. However, we observe almost all negative prices in early morning hours after a windy night. This suggests that a high level of wind energy generation, combined with a low demand (most factories do not operate at night, we also tend to sleep), can significantly decrease electricity prices.
In other words, the chance for a lower electricity bill is literally blowing in the wind.
Paulina Rowinska is a final year PhD student of the Mathematics of Planet Earth CDT at Imperial College London. Her research interests include statistics and stochastic modelling applied to Earth sciences and finance.
Currently she is studying how renewable energy sources influence electricity prices. She also actively engage sin science communication, for example by blogging about science at www.paularowinska.wordpress.com. In 2017 she gave a TEDx talk about looking for exciting maths in everyday life.