Artificial Intelligence and Machine Learning in Energy Distribution

The evolution of energy management has progressed rapidly over the past few years in diverse ramifications—from sheer size through modes of energy storage and delivery to security. This maturity is evident in innovative concepts such as decentralised grid systems, prosumption, smart charging, vehicle-to-grid (V2G) charging, the Internet of Things (IoT), etc.

Most of the above examples can comfortably be categorised as artificial intelligence (AI) and machine learning (ML) products. These two interwoven branches of technology have combined to shape the culture of energy management and distribution in profitable instances.

To understand the connection and synergy between AI/ML and energy management, it’s best that one first grasp the grassroots definitions.

What is Artificial Intelligence?

Artificial intelligence is an offshoot of computer science and technology that enables the simulation of human intelligence in machines. The root words “artificial” and “intelligence”, when split, explain it better to mean “man-made intelligence”. It generally involves training a machine to solve complex problems using reinforcement learning algorithms and deep learning neural networks. Apple’s Siri, online video games, customer support chatbots, and smart humanoid robots are popular applications of AI.

What is Machine Learning?

On the other hand, machine learning is a branch of AI that is data-driven, uses these sets of data—usually large and structured- and builds models that can make predictive and prescriptive analyses based on these past datasets without having to be programmed. ML has been widely incorporated into applications such as search engines for search algorithms that improve user experience, Facebook for friend suggestions and advertisements, online recommenders, and models for weather prediction.

Relationship Between AI/ML and Energy Distribution - Applications and Benefits

Integrating AI/ML into energy distribution has yielded nothing but an upturn in grid management, demand-response adequacy, and efficient fostering of energy communities. Below are some benefits that energy supply and distribution executives can derive from AI/ML.

In Power Grids

1. Enablement of Smart Grids: It is no news that smart grids are the heart of renewable energy (RE) sustainability. With the world tending towards RE sources, smart grids are proving to be inevitable in the foreseeable grand scheme of things, and this is where AI/ML plays its supervisory role.
   AI/ML is the technology that runs smart grids and helps decentralise energy management. It not only transmits electricity from and to the grid but also analyses, evaluates, and controls user data for accurate decision-making.
2. Sector Coupling: Sector coupling involves decarbonising the environment and enhancing a region’s electric capacity by merging all energy-producing and energy-consuming sectors into one electricity-producing sector—the grid. To achieve this, AI/ML technology is heavily utilised to convert consumer data to useful resources and automate processes as effectively as possible.
3. Grid Maintenance: With AI technology, grid operators and distribution managers can easily determine the best times for network maintenance. It can also detect faults in the grid and swiftly notify operators to have rapid solutions at the ready. This advantage helps reduce maintenance costs that may spring from delayed checks.

1. Grid Monitoring: AI offers ease to the grid and distribution managers by facilitating demand-response. This ultimately means that it prevents likely grid collapse by monitoring consumer energy usage and helping both users and suppliers even out energy supplied and energy used.
   The FLEXO community manager stands as the quintessence of this service. With this AI-driven software, distribution managers enjoy seamless control over their energy jurisdictions, have access to prosumer information, and can adjust energy consumption to accurately meet demand.

More so, the world is fully going cloud, including smart grids, and there is always a likelihood of cyber attacks. To ensure cybersecurity against malware, AI can be one of the best options.

In Virtual Power Plants (VPPs)

VPPs possess attributes similar to microgrids in that they are a network of storage devices such as electric vehicles (EVs), home appliances, and smaller plants that can be interconnected to supply energy during peak periods when the grid is experiencing overloading. AI controls the affairs of VPPs through:

Decentralised Plants Coordination: For the productive construction of a VPP, relevant plants and appliances must be well-coordinated to prevent collapse or failure. Here, AI technology interferes in two steps: first, by orchestrating a community of these devices that can be masterfully implemented with the FLEXO community manager, then, by facilitating energy transfer from the VPP to its destination. The FLEXO smart charge, for instance, can help distribution managers and EV owners execute V2G flawlessly.

In Power Consumption

Smart Homes: Smart homes are powered by AI technology. From the IoT, through the EVs and smart charging to the smart meters. AI gives grid operators the privilege to make correct maintenance judgments and accurate supply demand-supply adjustments based on data obtained from smart homes.

In Electricity Trading

Forecasts: Businesses require effective predictive analyses to be successful, and this condition does not exclude energy distribution.

Adequate energy distribution, especially where RE sources are concerned, must be preceded by forecasts, including weather predictions, population growth and density, energy demand and utilisation, etc. ML data science models use these datasets to provision distribution executives with the necessary information for better decision-making regarding future electricity trading.

The Future of AI/ML in Energy Distribution

Technology is speeding forward, and the world is panting to catch up. The growth of AI in the energy market in recent years has been astonishing. In 2021, the global size of AI in the RE market was valued at $8.24 billion. With an impressive growth rate of 27.9% from 2021 to 2030, this value is expected to exceed $75.82 billion.

The global RE market has survived long on the back of AI technology, and the strong synergy between the two suggests that it will continue.

Moreover, the statistics indicate that the sustainability of RE and smart energy distribution relies heavily on AI technology. This is why our AI-powered FLEXO solutions are indispensable to the future of grid management.

Book a slot with our team to understand how Hive Power FLEXO solutions can power your energy management and V2G projects.