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Energy Tech: Blockchain and Artificial Intelligence - The Catalyst for Microgrids?

  • Market Insight 15 July 2021 15 July 2021
  • UK & Europe

  • Energy & Natural Resources

'Traditional' electricity supply is predicated on a centralised system operated by major energy and utility companies, whereby energy is produced at large power stations, transmitted via a national grid and distributed to consumers through an extensive, centrally managed distribution network. According to the IEA, around 770 million people in developing countries are denied access to electricity, in countries which have limited or no national grids. However, smart technology holds out the hope of bypassing traditional national grid-style energy supply, enabling wider access to electricity and boosting the use of renewable power generation.

What is a Microgrid?

The term microgrid refers to a localised electricity grid which can operate autonomously from the national grid. Microgrids harness locally produced (distributed) energy and serve local consumers. Uniquely, microgrids offer consumers with their own energy production capacity the opportunity to sell their surplus energy through the microgrid, becoming 'prosumers'.

A move towards microgrids has the potential for significant socio-economic and environmental benefits. Microgrids promote localised energy production and consumption, leading to significant distribution and transmission efficiencies which can in turn reduce consumer and producer cost. Equally, microgrids can be powered by renewable energy such as rooftop solar panels or small wind turbines, offering consumers autonomy over the energy they consume and assisting with the reduction of global greenhouse gas (GHG) emissions. Microgrids can also improve network resilience in the event of natural disasters through their ability to operate in isolation.

The Role of IT in Microgrids

Operating a decentralised energy system is not straightforward, though. A microgrid would have to understand the usage patterns and demands and production capabilities of a large number of independent prosumers. Specifically, the system would need to know how the energy is produced and consumed at different times and points in the microgrid. This requires the efficient and accurate monitoring and recording of usage statistics and coordination between multiple energy sources and the central energy network, so that demand and supply are balanced at all times. In a distributed system, advanced communication and data exchanges between different parts of the grid network are required, making central management and operation more challenging.

Put simply, localised control and optimisation will be needed to accommodate a decentralisation of production. This in turn will require "smart infrastructure" capable of processing the inevitable increase in data transfer and transactions. The Internet of Things – i.e. the connection of any operating device to the internet, and therefore to each other, will enable the capture of a vast amount of data regarding domestic energy use. Automated data analysis and machine learning – "artificial intelligence" (AI) - can enable the use of this data to establish consumption and usage patterns, identifying times of peak demand as well as "down times" when stored energy can be sold to other households.

The main challenge for AI in the microgrid system is optimising the relationship between heterogeneous devices through learning to adapt device consumption against pricing signals and in doing so balancing the grid load. A notable example of success in this area can be seen at the Port of Rotterdam. Here, a renewable energy trading platform has harnessed AI and Blockchain to enable commercial energy consumers at the Port to purchase and consume energy more efficiently. The trading platform provides each consumer with an AI enabled 'energy trading agent' software which learns their energy needs, preferences and consumption patterns. Consumers are provided with access to dynamic local energy prices which accurately reflect the balance between supply and demand on the Port microgrid. Use of the technology saw an 11% reduction in costs for consumers, a 14% increase in revenues for producers and led to 92% of the solar power generated on site to be consumed.

This serves as a notable example of how AI can predict the energy generation and usage trends on a micro-gird whilst monitoring real-time electricity prices so that the most profitable production and efficient consumption will take place whilst avoiding system disturbances or outages.

Blockchain and Smart Contracts

However, the actual operation of a microgrid would still be impossibly cumbersome due to the vast number of transactions involved in the sale of energy between prosumers. Blockchain and smart contracts provide a solution. A blockchain is a shared and distributed data ledger that can securely store digital transactions without the need for a central authority. Importantly, in the context of microgrids, blockchain allows for the automated execution of smart contracts in peer-to-peer (P2P) trading networks. Smart contracts are executable programs that make automated changes to a ledger. When certain conditions are met, for example, the agreement to buy or sell electricity on specified terms, or the balancing of energy on a micro grid, a smart contract is created, executed and recorded in the ledger at an automatically predetermined price. Instead of central management, network members form a consensus on the valid state of the ledger and each may access copy of the blockchain records.

Such technology makes it possible for consumers and prosumers to trade energy flexibly, on demand, on a P2P basis, which offers potential financial rewards for all stakeholders. Prosumers can gain a stable return on investment for installing green energy production units, as profit and value remains within the microgrid and local community. This in turn creates socio-economic incentives for users to add additional local green energy production, serving to further reduce net GHG emissions. Equally, consumers who are unable to afford their own renewable generation, either due to a lack of capital funding or limited space, are able to buy certified local green energy at affordable prices. And, in a developing world context where no connection to a national grid is available, a microgrid could offer electricity supply where there is currently none.

The Brooklyn microgrid is a leading example of a blockchain based microgrid. Here, surplus energy is measured by specifically designed smart meters and turned into equivalent energy tokens that can be traded locally. The blockchain ledger records contract terms, transacting parties, volumes of energy injected and consumed and the chronological order of transactions. In addition, payments are automatically initiated by self-executed smart contracts. Every member of the community can have access to the ledger and verify transactions themselves.

In such a system, blockchain establishes optimal automated bidding strategies between devices based on inputted user preferences, such as; increasing energy self-sufficiency, reducing cost or bypassing main grid supply. This active consumer participation in the market is secured and recorded in a transparent way. The enabling of automated trading is also an efficient way of delivering price signals and information on energy cost to consumers, which further stimulates efficient consumption and serves to reduce overall costs.

Barriers to adoption/challenges

Decarbonisation and decentralisation (and, arguably, "democratisation") are targets for both EU and UK energy policy, amongst others. However, the current electricity market structure is impractical for achieving this vision quickly and there are significant barriers to adoption of an alternative. Despite the proven potential of microgrids and the rapid advancement in the blockchain and AI technologies which can underpin them, microgrid systems have not yet been implemented widely.

A significant issue is the regulatory environment in which microgrids exist, or lack thereof. Traditional regulatory models are predicated on vertically integrated utilities being subject to heavy regulation in exchange for exclusive access to customers. In a complex distributed system many questions will need to be answered, including: issues of ownership and access, the terms on which prosumers/consumers can trade energy, how the main grid interacts with the microgrid, how service issues will be managed and disputes settled. It will also be critical to establish a regulatory framework to deal with issues of data privacy.

The scarcity of commercially functioning microgrids means that operational expertise is limited. This is in part due to the complexity of microgrid projects. The idea that either a utility or a neighbour will purchase the excess power of prosumers is straightforward in the context of small scale microgrids. However, due to intermittency issues, adding additional renewable capacity to a grid creates potential instability, inefficiency and outages. Therefore, the widespread installation of green microgrids will only occur in conjunction with the associated battery storage and smart infrastructure capabilities necessary to safely support the grid.

The above issues, amongst others, have so far stifled investment. Investors perceive microgrids as riskier than other green investments, in part because it is difficult to model the risks or accurately forecast returns. Microgrid production has not been standardised, meaning each grid is unique and must be assessed individually. This comes with issues of economies of scale for investors. Additionally, the lack of government subsidy models or financial support from utilities has served as another disincentive for private investment.


If these barriers can be overcome, and Blockchain and AI technologies deployed effectively, then microgrids have the potential for significant positive social and environmental change. The concept of centrally managed fossil fuel generated electricity can be replaced with an intelligent and cooperative system fuelled by sustainable energy which both reduces GHG emissions and allows communities of users to harness the maximum economic benefits from energy production and consumption. In a developing world context, microgrids offer the hope of skipping the national grid phase and moving directly to local, sustainable energy production. It is to be hoped that the crucial role microgrids could play in achieving decarbonised energy production and distribution around the world will be recognised to encourage government, transnational organisations and investors to embrace this potential.

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