1. Introduction

Near-continuous regulatory models refer to regulatory systems in which oversight, monitoring, compliance assessment, reporting, and corrective intervention occur continuously or at very short and regular intervals, rather than through occasional inspections, periodic licensing reviews, or retrospective enforcement.

Traditional regulation often follows a cycle: a regulator grants a licence, conducts periodic inspections, receives annual reports, and intervenes when a violation occurs. Near-continuous regulation changes this model by using real-time or near-real-time information, automated monitoring, digital reporting, performance indicators, market surveillance, and rapid regulatory intervention.

This approach is particularly important in energy law, because electricity grids, gas networks, pipelines, renewable generators, storage systems and energy markets operate continuously. A regulatory failure may therefore create consequences before a conventional periodic inspection can identify the problem.

2. Meaning and Concept

A near-continuous regulatory model has five principal characteristics:

Continuous data collection – information is collected from meters, sensors, market platforms, network-control systems and regulated entities.

Frequent compliance assessment – compliance is assessed daily, hourly, or even in real time.

Early-warning mechanisms – abnormal conduct or technical conditions trigger alerts.

Rapid intervention – regulators can impose directions, corrective measures, penalties or operational restrictions without waiting for a lengthy periodic review.

Continuous learning – regulatory requirements can be adjusted in response to changing market and technological conditions.

It therefore represents a movement from:

“inspect and punish” regulation

towards:

“monitor, detect, prevent and correct” regulation.

3. Importance in Energy Regulation

Energy systems are particularly suitable for near-continuous regulation because their physical and commercial operations are highly dynamic.

For example, an electricity regulator may need to monitor:

frequency and grid stability;

generation and demand;

transmission congestion;

deviations from scheduled generation;

ancillary-service performance;

electricity-market bids;

renewable-energy forecasting;

battery-storage operations;

transmission availability;

consumer supply quality;

cybersecurity incidents; and

manipulation of electricity markets.

A quarterly or annual compliance model may identify problems too late.

Near-continuous regulation therefore attempts to align legal supervision with the operational speed of the regulated system.

4. Main Elements of the Model

A. Real-Time Monitoring

The regulator receives information continuously or at short intervals.

Smart meters, supervisory control systems, automated reporting systems and market platforms can provide regulatory information without requiring physical inspection.

B. Automated Compliance

Certain regulatory obligations can be translated into measurable rules.

For example:

maximum outage duration;

voltage standards;

frequency limits;

emission limits;

renewable-generation obligations;

market-position limits.

Where a predefined threshold is exceeded, the system can automatically generate an alert.

C. Risk-Based Supervision

Not every regulated entity requires the same intensity of supervision.

A regulator can allocate greater monitoring resources to:

systemically important utilities;

critical infrastructure;

entities with repeated violations;

dominant market participants; and

technologically complex operations.

D. Continuous Reporting

Instead of annual compliance statements, regulated entities may provide:

hourly data;

daily market information;

monthly performance reports;

incident notifications; and

continuous operational information.

E. Rapid Corrective Intervention

Near-continuous regulation is meaningful only if the regulator has legal authority to respond.

Possible interventions include:

compliance directions;

temporary restrictions;

remedial orders;

financial penalties;

licence conditions;

market restrictions; and

emergency measures.

5. Relationship With Regulatory Technology

Near-continuous regulation is closely associated with RegTech and SupTech.

RegTech refers to technologies used by regulated entities to satisfy regulatory requirements.

SupTech refers to technologies used by regulators for supervision.

For example, an electricity regulator could use algorithms to identify unusual bidding patterns in a wholesale electricity market. Instead of waiting for a complaint, the regulator can investigate an anomaly shortly after it occurs.

However, technological monitoring does not eliminate legal requirements. Automated regulatory decisions must still comply with:

statutory authority;

procedural fairness;

transparency;

proportionality;

confidentiality;

data-protection requirements; and

judicial review.

6. Case Law: Energy Watchdog v CERC

The Indian Supreme Court's decision in Energy Watchdog v Central Electricity Regulatory Commission, (2017) 14 SCC 80 is important for understanding regulatory intervention in electricity markets.

The case concerned disputes arising from power-purchase agreements and changes in circumstances affecting generation costs. The Court considered the contractual and regulatory framework governing electricity generation and supply.

The case demonstrates an important principle for near-continuous regulation: regulatory intervention must remain connected to the statutory and contractual framework governing the regulated activity.

Continuous supervision cannot become unlimited administrative discretion. Regulatory authorities must exercise their powers within the boundaries established by legislation.

7. Case Law: PTC India Ltd v CERC

In PTC India Ltd v Central Electricity Regulatory Commission, (2010) 4 SCC 603, the Supreme Court examined the powers of the Central Electricity Regulatory Commission under the Electricity Act 2003.

The Court distinguished between regulations made by the Commission and individual regulatory orders.

This case is especially relevant because near-continuous regulatory models depend upon a combination of:

general regulatory rules;

ongoing supervision;

individual directions; and

enforcement mechanisms.

The case reinforces the importance of identifying the statutory source of regulatory power. A regulator cannot rely on continuous monitoring technology to acquire powers that Parliament has not granted.

8. Case Law: Gujarat Urja Vikas Nigam Ltd v Essar Power Ltd

In Gujarat Urja Vikas Nigam Ltd v Essar Power Ltd, (2008) 4 SCC 755, the Supreme Court considered the regulatory jurisdiction of electricity commissions under the Electricity Act.

The decision illustrates the breadth of sector-specific regulatory jurisdiction where disputes arise within the electricity industry.

For near-continuous regulatory systems, this is significant because effective monitoring must be accompanied by a legally defined jurisdiction. Monitoring information may be collected continuously, but intervention must remain within the regulator's statutory competence.

9. Case Law: Cellular Operators Association of India v TRAI

In Cellular Operators Association of India v Telecom Regulatory Authority of India, (2016) 7 SCC 703, the Supreme Court examined regulatory action by the telecom regulator concerning quality-of-service standards.

Telecommunications provide a useful comparative example because network performance is inherently continuous.

The regulatory framework involves measurable service-quality parameters and regulatory supervision of service providers.

The broader lesson applicable to energy law is that continuous service industries require measurable performance standards. Regulation becomes more effective when legal obligations can be translated into objectively observable indicators.

10. Case Law: Modern Dental College v State of Madhya Pradesh

In Modern Dental College & Research Centre v State of Madhya Pradesh, (2016) 7 SCC 353, the Supreme Court discussed proportionality in the context of regulatory restrictions.

Although the case was not an energy case, its proportionality reasoning is relevant to technologically intensive regulatory systems.

Near-continuous supervision can produce enormous quantities of information and potentially lead to frequent intervention. The legal response must therefore remain proportionate to the regulatory objective.

A minor technical deviation should not automatically result in the same regulatory response as a serious systemic violation.

11. European Union Perspective

European energy law increasingly incorporates continuous monitoring through market-surveillance mechanisms, network codes, reporting requirements and regulatory cooperation.

The REMIT framework is particularly significant because it addresses wholesale energy-market integrity and transparency.

Continuous or frequent market surveillance enables regulators to identify:

insider trading;

market manipulation;

suspicious transactions;

abnormal price movements; and

attempts to distort wholesale energy markets.

The model demonstrates how digital market infrastructure can allow regulation to operate much closer to the time of the regulated conduct.

12. Advantages

1. Early Detection

Problems can be detected before they become systemic failures.

2. Better Grid Reliability

Continuous monitoring can help identify operational risks affecting electricity networks.

3. Market Integrity

Frequent monitoring can identify suspicious trading behaviour more quickly.

4. Evidence-Based Regulation

Regulators can make decisions using actual operational data rather than relying exclusively on periodic reports.

5. Reduced Compliance Costs

Automated reporting can reduce repetitive manual inspections.

6. Faster Enforcement

Regulators can respond to violations without waiting for the next inspection cycle.

13. Legal and Institutional Risks

Near-continuous regulation also creates important legal challenges.

A. Excessive Surveillance

Continuous data collection may create privacy and confidentiality concerns.

B. Algorithmic Bias

Automated systems may incorrectly identify lawful conduct as regulatory violations.

C. Due Process

A regulated company should generally have an opportunity to understand and challenge adverse regulatory decisions where legally required.

D. Regulatory Overreach

Continuous monitoring does not itself create substantive regulatory authority.

E. Data Security

Energy-sector regulatory databases can contain commercially sensitive and critical-infrastructure information.

F. Accountability

When an automated system generates a regulatory alert or decision, responsibility must remain attributable to identifiable regulatory institutions and officials.

14. Near-Continuous Regulation and Natural Justice

The closer regulation moves toward real-time intervention, the greater the tension between speed and procedural fairness.

Emergency intervention may sometimes be necessary where grid stability or public safety is threatened. However, ordinary enforcement should generally maintain appropriate procedural safeguards.

The regulatory system should therefore distinguish between:

Emergency decisions → immediate intervention may be justified

and

Ordinary enforcement → notice, reasons and opportunity to respond may be required.

This creates a model of continuous monitoring but legally structured intervention.

15. Near-Continuous Regulatory Model in India

The Electricity Act 2003 provides an institutional foundation for intensive regulation through bodies such as:

Central Electricity Regulatory Commission;

State Electricity Regulatory Commissions;

Central Electricity Authority; and

system and market institutions operating under the electricity regulatory framework.

Modern electricity markets increasingly depend upon:

automated metering;

deviation settlement;

real-time market operations;

ancillary services;

renewable forecasting;

grid-security monitoring; and

digital market surveillance.

These developments make electricity regulation increasingly data-driven and continuous rather than purely periodic.

16. Difference From Traditional Regulation

17. Future Development

Future near-continuous regulatory systems are likely to incorporate:

artificial intelligence;

digital twins;

smart-grid analytics;

automated compliance systems;

blockchain-based energy records;

machine-learning market surveillance;

satellite monitoring;

cybersecurity monitoring; and

predictive regulatory analytics.

However, technological sophistication should not replace legality, transparency and accountability.

The ideal model is therefore not unrestricted automated regulation but technology-assisted continuous regulation under clear statutory authority and judicially reviewable procedures.

18. Conclusion

Near-continuous regulatory models represent an evolution from periodic, reactive regulation toward continuous, data-driven supervision. They are particularly valuable in energy law because electricity and energy markets operate continuously and can produce rapidly developing technical, economic and security risks.

The principal legal challenge is balancing speed with legality and fairness. Cases such as PTC India, Energy Watchdog, Gujarat Urja and Cellular Operators Association demonstrate the continuing importance of statutory authority, regulatory jurisdiction, measurable standards and legally controlled intervention.

Thus, the defining principle of near-continuous regulation can be expressed as:

Continuous information does not mean unlimited regulatory power; continuous supervision must remain bounded by law, proportionality, procedural fairness and institutional accountability.