4. AI And Energy-Market Manipulation

Introduction

Artificial Intelligence (AI) is increasingly being used in energy markets for electricity forecasting, automated trading, demand prediction, pricing, and grid management. Although AI can improve efficiency, it can also create new risks of market manipulation. AI systems may be used to generate false trading signals, coordinate trading strategies, manipulate prices, exploit market information, or create artificial demand and supply patterns. Therefore, effective legal regulation is necessary to preserve fair and competitive energy markets.

Legal Framework in India

The Electricity Act, 2003 provides the principal legal framework for electricity markets in India. The Central Electricity Regulatory Commission (CERC) regulates important aspects of electricity trading and market operations. The Central Electricity Regulatory Commission (Power Market) Regulations, 2021 provide rules concerning power-market participants and market conduct.

AI-based manipulation may also involve principles under the Competition Act, 2002, particularly where technology is used to coordinate anti-competitive conduct or abuse market power. Where computerized systems involve unauthorized access, alteration of data, or other cyber offences, the Information Technology Act, 2000 may also become relevant.

Judicial Principles

Indian courts have developed important principles concerning market regulation and competition. In Excel Crop Care Ltd. v. Competition Commission of India (2017), the Supreme Court examined anti-competitive conduct and emphasized the importance of protecting competition in markets. The principles of competition law can become relevant when automated systems are used to facilitate coordinated or exclusionary conduct.

In Competition Commission of India v. Steel Authority of India Ltd. (2010), the Supreme Court considered the powers and role of the Competition Commission of India in investigating anti-competitive conduct. The decision demonstrates the importance of effective regulatory investigation where market conduct may harm competition.

In Gujarat Urja Vikas Nigam Ltd. v. Essar Power Ltd. (2008), the Supreme Court examined disputes within the electricity-sector regulatory framework and recognized the importance of specialized electricity regulation. The case illustrates that electricity markets operate within a specialized statutory framework rather than ordinary commercial arrangements alone.

AI-Specific Risks

AI-based trading systems can operate at speeds beyond ordinary human supervision. Multiple algorithms responding simultaneously to market conditions could potentially produce abnormal price movements without traditional forms of human coordination. AI could also be used to identify weaknesses in market rules and exploit them repeatedly. Another concern is algorithmic collusion, where independently designed systems may produce similar pricing or trading behaviour without an explicit agreement between their operators.

Regulators may therefore require market participants to maintain records of algorithmic decisions, conduct testing before deployment, monitor unusual trading patterns, and maintain effective human oversight. Transparency and explainability are particularly important when automated systems significantly influence electricity prices.

Future Regulatory Approach

Future energy-market regulation may require AI developers and energy traders to implement algorithmic risk-management systems, audit mechanisms, data-governance standards, and real-time monitoring. Regulators may also need access to relevant trading records and algorithmic logs when investigating suspected manipulation. Clear rules concerning responsibility will be necessary where harmful conduct results from autonomous AI systems.

Conclusion

AI can substantially improve electricity-market efficiency, but its use also creates new forms of market-manipulation risk. Existing electricity regulation, competition law, and cyber law provide important foundations, but increasingly sophisticated AI systems may require more specialized regulatory standards. Judicial principles concerning fair competition, regulatory oversight, and electricity-market governance, together with stronger algorithmic monitoring and accountability, can help ensure that AI contributes to efficient and transparent energy markets rather than undermining market integrity.