Interviewing Isha Saxena
It was my pleasure to interview Isha, a PhD student in the Engineering Department here at Durham. Her research specialises in data-driven infrastructure for offshore wind farms in order to reduce uncertainty in failure rates. As part of this month’s theme, the Renewable Revolution, we explore opportunities for renewable energy in the UK.
Firstly, could you please start with an overview of your work?
So, we know that wind turbines are really complex structures, and they face failures and repairs on a daily basis. Offshore wind turbines actually have even more challenges as compared to onshore, because there can be instances where there are huge storms, so maintenance can be delayed by several days. The wind speed onshore is very much higher compared to onshore because there are no obstructions, so this can cause the blades to damage more often as compared to onshore wind turbines. All these issues can cause unexpected failures as well, and maintenance can be delayed by several days because of these bad weather conditions.
What happens is that Expected Energy Not Served (EENS) increases. Developers will calculate the expected units of electricity at the very beginning of a lifespan of a wind farm, to communicate to consumers how much electricity they’ll be able to provide. However sometimes, due to unplanned maintenances they are unable to provide that.
To do those calculations more accurately, I am working on a statistical model. The current model that we use uses an exponential distribution for the useful lifetime of a wind turbine, which means that it assumes that every time a wind turbine is repaired it goes back to its original state. Basically, exponential distribution does not remember that it ever broke down. So, I am trying to move away from that assumption and use different distributions. Currently I’m working on using a viable distribution to do the calculations and I’m using a Bayesian inference for calculations. The end goal is to prepare a tool that can be used by developers to estimate the output of a wind farm more accurately as compared to right now.
Why did you choose to focus you research on offshore wind and not onshore?
Well, I would say that when I was doing my masters in 2019, offshore wind energy was sort of novel then because the use of offshore wind only started in the early 1990’s. One of my professors introduced us to offshore wind energy and it sounded so fascinating so I did more research about it, naturally you have so many questions when you look at the wind turbines placed in the sea.
So, in regard to attracting investment to offshore wind energy, would you say failure rates that we currently have will be an issue with attracting investment?
Yeah, that is a huge issue, the main problem with any renewable energy right now is that it’s not constant. There are spans of time when the wind energy is very high and then there are times when there’s no wind and the turbines come to a complete halt. Then sometimes even if the wind energy is working, the grid is not equipped to take that much load. So sometimes there’s an issue from the grid side, or we have storage issues as well. The infrastructure can be high maintenance and combined with high failure rates can mean offshore wind projects are billion-pound projects. Despite the expense the government is trying to do as much as they can to promote offshore wind energy right now, especially since the UK is one of the leading countries for offshore wind.
In your paper you mentioned the Green Revolution set out by the UK government, and how under their ten-point plan the UK is set to quadruple its wind energy production. Do you think this goal is achievable?
So right now, wind energy has achieved approximately 50% of the power that is applied to the grid, I would say that the UK is really committing to green energy currently. There are dozens of wind farms that are planned and some that are in construction right now. Because they are putting more funding and research into this technology, it is becoming cheaper. Bids currently are showing a decrease in the Levelised Cost of Energy (LCOE) for wind energy.
I see you are intern for Kinewell energy, could you talk more about your work with them?
The CTO of Kinewell was another PhD student from Durham University and she was an amazing student who developed a tool for calculations of different scenarios using technology for wind energy and this tool was adopted by Kinewell. This tool now uses hydrogen as well as wind energy. Users can develop several scenarios for constructing their wind farms using different technologies, so I am working on that tool with them to develop a few case studies.
Link to her research paper:
https://iopscience.iop.org/article/10.1088/1742-6596/2767/6/062002