The impact of extreme weather on renewable energy plants
Extreme weather has a severe effect on renewable energy plants, mostly due to the fact that many renewable energy types rely on weather to produce energy, so extreme weather events can cause over- or under-production of energy. The vulnerability of renewable systems is also an issue. Many plants are also placed in exposed locations - such as wind turbines - in order to capitalise on weather conditions that help them to produce more energy, but this also means equipment and infrastructure become damaged in the instance of more frequent and severe climate events, which sees rising costs of weather-related outages.
Assessing risk: mapping weather vulnerabilities in energy assets
Using historical weather data to forecast plant performance
Collecting and analysing data on previous outages, downtimes, and damages helps predict how renewable energy assets may perform during future weather events.
Creating regional hotspot maps for risk assessment
Forecasting tools help identify vulnerable regions and optimise asset placement. Hotspot mapping also supports pre-construction risk evaluations.
Building climate-resilient energy infrastructure
For a truly stable grid, it’s imperative that our infrastructure is resilient from both a hardware and data perspective so we can predict when and where an asset might be damaged and how that event might be responded to.
Upgrading renewable installations
Integrating IoT sensors for predictive maintenance
IoT sensors allow continuous monitoring of energy assets, detecting weaknesses and enabling predictive maintenance before failures occur.
Bridging legacy equipment and smart grid components
IoT integration also facilitates communication between outdated fossil-fuel infrastructure and upgraded renewable systems.
Operational strategies for weather readiness
Maintenance, emergency drills, and backup energy
It’s clear that holistic views of an energy plant's operation, such as seasonal maintenance and inspections, are crucial to the smooth running of an asset. Once regular maintenance and inspections are in place, it’s important to implement emergency response plans and drills to respond to the findings of these inspections.
Advanced weather forecasting can also aid in designing emergency response plans and drills. In the case of keeping energy fulfilling demand, introducing battery storage to allow backup energy to kick in during downtime during storms is a robust method of emergency response. Investing in battery storage backup is one method of disaster response; however, implementing decentralised systems may also be appropriate, which involves designing smaller sub-grids that aren’t connected to the wider grid. The benefit of this is that emergency response can be more tailored to react quickly during downtime due to extreme weather events.
Curtailment and safety protocols during grid stress
In the instance that the grid is flooded with energy due to an extreme weather event, e.g. wind energy during a storm, we may have to introduce energy curtailment as an emergency response, which prevents a plant from generating energy at all, which can be used to stabilise the grid in an emergency. If a site is frequently subject to extreme weather conditions, certain safety protocols may have to be introduced, for example in the case of human engineering in exposed coastal locations. Suppose a wind turbine is damaged due to a storm. In that case, human intervention may be required to repair the asset, and robust safety systems, as well as emergency response plans, must be created for use during these incidents. This might include workforce training for disaster scenarios or introducing or strengthening existing health and safety protocols specifically designed for emergency response during extreme weather events.
Technology and forecasting tools for climate resilience
In the future, we may look to technology such as smart grids, AI, and real-time monitoring for a full 360-degree view of how plants are operating and how we can minimise downtime in extreme weather occurrences.
Using AI and satellite data for weather prediction
Developments such as AI and satellites will be crucial in predicting how extreme weather events may affect renewable assets. Using data gathered from satellites, we can instruct AI to identify patterns within the weather data gathered and in regards to the behaviour of plants in certain regions during extreme weather events. AI can then generate algorithms to stabilise forecast usage during these extreme weather events. These recommendations can then either be actioned in an automated way or used to inform human operatives who can decide the maintenance or machine health plan for a plant.
Smart grid integration for predictive and real-time response
We can also go further with automated monitoring and analytics by integrating IoT with AI. The IoT can be so accurate in the mapping of an asset that it can pinpoint exactly where machine failure occurs in a plant during these events, allowing predictive maintenance to happen before total asset failure occurs. Connections on the demand side of energy assets - such as smart meters - can also be useful as they can show how demand increases or decreases during extreme weather events, for example, if energy spikes occur due to increased air conditioning due to droughts.
Real-time monitoring and automated alerts
We can analyse weather data to help us stabilise the grid and manage energy demand in real-time, stabilising the grid. Monitoring in real-time involves analysing both the demand and supply of energy during extreme weather events and adjusting the amount of energy generated to fulfil the demand. To make sure an asset is truly reactive, automated alerts can be set up to allow an asset to react to events that are happening in real time. This is another instance of where the IoT can be utilised successfully.
Policy, regulation, and industry collaboration
In the future, it's expected that businesses will have to comply with policy-led initiatives such as climate resilience standards. These standards involve companies examining their current energy infrastructure setups and developing strategies that outline how they might deal with long-term climate changes. This means examining the areas of business that might be affected negatively or positively by climate change and assessing how they will approach withstanding these events.
Extreme weather events are an increasing threat to renewable energy reliability. By investing in smart infrastructure, forecasting tools, and policy alignment, energy producers can build resilient systems ready to withstand future climate challenges.
