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Distributed Autonomous Energy Organizations 219

exchanging distributed energy resources often involves intermittent sources
of energy that need load leveling and balancing to function reliably and
efficiently.
In this context, blockchain smart contracts could help reduce energy use
during peak hours by automating the curtailment of nonessential electricity
use. AI algorithms would learn end user’s energy-use patterns and consumers
would agree on their flexibility of curtailing certain nonessential loads. Smart
contracts currently have the capability to be defined and improved via
machine-learning algorithms. But computational errors may still occur, rais-
ing additional questions for future research. Who will be held responsible
when there is an error or when a blockchain smart contract is not successfully
executed? While the data and exchange of value captured in blockchain
might be immutable, or at least very hard to manipulate, what if the algo-
rithm that establishes the terms of the contract executed is written by an
autonomous AI agent? What if the agent is wrong? How do you change
an immutable contract? What additional challenges and potential solutions
should be explored through AI-enabled blockchain solutions to distribute
and automate the IoT in a more secure way?
This study explores some of these questions and other pertinent energy
security and optimization questions through an innovative application of
blockchain that gives impetus to DAEO. This use case highlights how
AI-enabled blockchain solutions may help increase cyber resilience and
optimize complex exchanges of distributed energy resources by encrypting,
monitoring, and automating transactions to remove third parties. With bil-
lions of IoT devices sensing and exchanging information, AI-enabled block-
chain solutions could also help to better analyze data sets with thousands of
variables (e.g., industrial control system anomalies, frequency, load, and
voltage changes) and to organize them into weighted relationships that could
be tracked through next-generation AI blockchain solutions. As data pat-
terns in these variables are better understood via machine-learning neural
networks, the smart blockchain contract could be updated to better secure
and exchange critical energy data and devices.

12.2 DISTRIBUTED ENERGY SUPPLY CHAIN

These advances are important as the US power grid is a complex system of
systems that requires a secure, reliable, and trustworthy global supply chain.
This complexity is especially true for the grid’s increasing number of net-
worked energy delivery systems (EDSs), industrial control systems (ICSs),