Optimising renewables integration with disruptive technology

Integrating renewable energy sources is becoming indispensable for utilities. Employing disruptive technologies to optimise operations are key to manage this process.
Published: Fri 20 Jul 2018

Utilities across the globe are facing increasing demand to integrate renewable energy sources.

However, whilst the benefits of doing so are significant, integrating and managing renewables is not without its challenges, as it implies that utilities must overhaul a large part of their operations to accommodate this new integration demand.

Technological innovations such as augmented reality, artificial intelligence (AI) and the Internet of Things (IoT) are thus emerging as viable tools to optimise this growingly complex process, maximise efficiency and reduce related operational costs.

In an Engerati webinar, 'How Iberdrola maximised operational efficiency in wind technology with disruptive technology', technology solutions expert Indra outlines the challenges that come with this process. With insights from a project with Iberdrola, Indra shows how to utilise innovative technology to tackle such difficulties and optimise operational efficiency.

Challenges for renewables integration

 

Juan Prieto, Head of Smart Grid Practice at Indra, explains that the challenge to integrating and managing renewable energy assets comes in large part from the complex nature of renewable generation. As the production patterns for solar and wind power sources are intermittent, fully utilising generation assets is key. In addition, other challenges include the geographical distribution of assets, such as offshore wind farms, and optimising maintenance costs. 

"The first challenge is to maximise the production, getting as much energy as possible from those assets. We need to minimise the number of failures, optimise the way we maintain those elements and increase the lifespan of different assets, and get the tools to continually monitor and identify failures before they actually happen," says Prieto.

"Another big challenge is related to the continuous optimisation of the operational maintenance cost, which is related to everyday activities run on generation assets. Lastly we have the geographic distribution of the generation assets. There is a difficulty in managing offshore wind farms, but we are also starting to face distributed energy generation across different levels of the electrical grid. We need to understand the different business models that will allow for distributed generation to be integrated into energy management."

Indra and Iberdrola demonstrate the shortcomings of a traditional maintenance model, as opposed to the innovative condition-based maintenance approach they employ.

Real-time condition-based monitoring

However, there is a vast range of technologies that can be used to sidestep such challenges and maximise operational efficiency for renewable generation management.

In recent projects to optimise the efficiency of wind energy assets, Iberdrola and Indra have demonstrated the use cases of such innovative assets. "Multiple technologies can be used for wind turbines monitoring, from statistical models to multi-layered models based on AI," says Miriam Diaz Ureña, Senior Performance Analyst at Iberdrola.

"These systems are used to optimise maintenance models, increasing wind turbine availability and minimising costs. The industrial revolution 4.0 and the increasing complexity of wind turbines require a robust management infrastructure."

Indra and Iberdrola demonstrate the shortcomings of a traditional maintenance model, as opposed to the innovative condition-based maintenance approach they employ.

 

Ureña compares a traditional maintenance approach, reliant on corrective and preventive maintenance, to a real-time condition-based approach and the outcomes it is capable of achieving. "Traditional maintenance strategies are based on a combination of corrective and preventive actions. Corrective maintenance includes actions carried out to return the turbines to a state in which they can function properly, whereas preventive maintenance is carried out regularly to reduce the probability of failure or degradation of a component."

"However, the industry is now transitioning from this reactive and preventive approach to a condition-based maintenance approach. Condition-based maintenance relies on monitoring to determine conditions and schedule maintenance when wind turbines show evidence of component degradation or upcoming failures.”

Ureña says that compared to corrective maintenance, condition-based maintenance can help to reduce costs by reducing wind turbine downtimes, which increases the overall wind farm availability. “It also decreases the number of visits to the wind farm, therefore improving the logistic strategy, and avoids replacing components that are still in an adequate state, reducing the overall material costs."

For this end, Iberdrola is using the Advanced System of Predictive Analytics (ASPA). "It is based on big data and AI techniques that aim to reduce failure detection times and increase the reliability and accuracy of wind turbine monitoring systems," explains Ureña.

"ASPA is based on modelling the normal behaviour of wind turbines from which deviations can be detected, which could imply component degradation or an upcoming failure. Normal behaviour modelling could potentially prove to be more accurate than a statistical solution for wind turbine monitoring."

Optimising training with augmented reality

Maximising the operational efficiency of wind energy assets also means investing in optimal training for maintenance staff. Improving the efficiency of crews to manage offshore wind turbines, for example, is essential, "because it is a risky environment, the costs are high, and we need to make sure that our crews react in the fastest, most effective and secure way," explains Prieto.

"In this case, we are applying virtual training environments. We create a virtual model of the turbine and are able to develop different kinds of risks and missions in order to test the staff's knowledge and reaction times.

"We are now finding more and more projects where we are able to demonstrate the value of this technology, especially in difficult environments such as offshore wind farms. It really helps to improve the efficiency of maintenance staff training. In our typical ratio, training 1 hour on a virtual environment is worth around 10 hours of actual experience because you can put the operator in difficult conditions which, in reality, only happen very rarely."

 

Juan Prieto, Head of Smart Grid Practice at Indra, outlines the business model evolution that the energy industry is to face in the upcoming decades.

New business models for the industry

Though the solutions proposed by Indra and Iberdrola are practical and have several proven use cases, the industry will continue to face challenges around renewable energy integration in upcoming years.

As such, it is important for the industry to continuously evolve and adapt to the market. "We need to start thinking about different business models that the market is moving towards," suggests Prieto.

Firstly, it is important for utilities to turn renewables into reliable power sources. According to Prieto, "as we replace conventional generation with renewable generation, the volatility of the power system will increase. We will become an environment where the more reliable is the generation, the more value we will get for that energy.

"To be able to adopt these new business models, we need new technologies. For example, storage technology would help make this possible by evening out generation patterns; blockchain would help us manage transactions with different partners that we will collaborate with in deviation minimisation processes; and edge intelligence would allow us to automate the response from different resources that will be helping to provide a reliable energy source.”

He says that in the next step, there will be a lot of power being produced by consumers. “Instead of considering that a competition to the classic renewable generation model, in this model renewable energy utilities apply their experience in energy management into aggregating distributed generation capability in a virtual power plant model, joining and aggregating the capacity of many customers together."

Finally, to Prieto, this business model evolution will lead utilities towards a transactive energy market. "In this model, companies allow energy trading between consumers, distributed generation sources, industries and others. The market would become more granular and energy exchanges would be more open and real-time.”

Therefore, to fulfill the demands of this future energy landscape, utilities will not only need to update their business models to a transactive, decentralised approach, but also employ disruptive technologies that will enable the market to function seamlessly. Blockchain, IoT, edge intelligence, AI, augmented reality and several other pieces of innovation will prove to be key enablers for the energy transition.

Watch the webinar

To learn more about the opportunities for new technologies optimising renewable integration, watch the webinar 'How Iberdrola maximised operational efficiency in wind technology with disruptive technology', on-demand now.