Towards a smart and resilient grid
Artificial Intelligence and energy storage have the power to change the energy sector, says Stephane Bilodeau, Chairman and Chief Technology Officer, Novacab Inc.
The global energy industry faces fundamental changes in the way it generates, sells and distributes energy. There is strong pressure to improve resilience and, at the same time, reduce CO2 emissions. Therefore, methods must be found to manage the growing production of electricity from renewable sources of energy which are unpredictable and dependent on the eccentricity of local weather, or even on the global climate front when we think about the impacts of climate change.
It is more and more clear that there is a global demand for clean, cheap and reliable energy. This is not only for power grid operators but the reliability of the source of the energy and the cost of electricity is also a concern for consumers, for governments and for civil society actors, as well as for business people who all want to please to whether their customers or their constituents.
Artificial intelligence (AI) could be a very useful and even powerful tool for meeting these needs. And, we will see more and more AI applications in the energy sector. Notably, maximising the growth of green, low-carbon electricity generation through optimal energy storage management is an artificial intelligence application that will have a potentially huge long-term impact.
The capacity of artificial intelligence to integrate diverse sources of energies including storage
Various forms of renewable sources of electricity appear as successors of traditional coal and gas power plants. However, a key problem with renewable production is its intermittency. A cloudy day or a quiet, windless series of afternoons will reduce production and create power outages. Conversely, too much energy can be generated when not needed. This was the case, in March 2018, Portugal faced sunny and windy days where it produced more renewable electricity than it consumed. This potential waste or lack of energy means that it is important to maximise the use of energy storage and in all its forms (electrochemical, thermal, mechanical, etc.) It is also essential that this storage can be activated quickly, if we want to minimise the use of backup energy, for example, diesel generators, coal-fired power plants, or other peaker-plants, which are currently used to smooth out the swift dips into peak periods.
Smart storage or “Intelligent Energy Storage” (IES) solutions are needed to manage excessive peaks. AI can be used to predict and make energy storage management decisions. For example, AI could be used to manage electricity shortages by briefly cutting the demand for electricity on the main grid, while it uses storage in entire communities or regions.
The use of AI would generate forecasts for electricity demand, production and weather can reduce the need for these safeguards by predicting and managing fluctuations in output. The speed and complexity of this task require advanced artificial intelligence.
Artificial intelligence research also studies decision-making with a scale and complexity that begins to surpass that of a human operator. It could be a network of thousands of mixed energy storage units (electrical, thermal, others) installed at consumers, end-users or on highly used sites, such as industrial installations.
AI’s ability to “understand” (or decipher) data sets, but also models or patterns in data, and to make very accurate predictions and simulations will increase opportunities for power grid optimisation, energy efficiency and even a period of growth in demand.
Artificial intelligence (AI), coupled with many advanced energy storage technologies, when it comes with machine learning, deep learning, and advanced neural networks, can demonstrate tremendous potential for energy transformation and the utility sector. With decarbonisation, decentralisation and the deployment of new technologies, utilities, independent power producers and other energy companies are using AI to manage the imbalance in demand and supply caused by the growing share of renewable energy sources.
In addition to making electrical networks and systems smart and flexible, artificial intelligence algorithms help utilities and energy companies understand and optimise user’s behaviour and manage energy consumption in different sectors in a changing context and environment.