Rajesh Kaushal, Energy Infrastructure & Industrial Solutions (EIS) Business Group Head, India & SAARC, Delta Electronics India

With 400,000 new chargers being added every year in India alone by 2030, AI will be the driving technological force propelling the country toward a smooth, scalable, and genuinely sustainable future with electric vehicles.

November 24, 2025. By News Bureau

Tags:

articles

Rajesh Kaushal

Delta Electronics India

Electric vehicle (EV) revolution

Battery electric vehicle

EV ecosystem

Grid reliability

Revolutionising EV Charging

EV Charging Infrastructure

Smart Grid Infrastructure

Introduction

India is experiencing an electric vehicle (EV) revolution, with Battery Electric Vehicle (BEV) production projected to surge from 130,000 in 2024 to 377,000 in 2025. This rapid, transformative growth, fueled by a 20 percent annual increase in EV sales and the introduction of new models, strains the nation's power grid. This is precisely where Artificial Intelligence (AI) becomes crucial. AI is strategically positioned to maximise charging efficiency, regulate demand, and safeguard grid stability, ensuring the seamless integration of India's burgeoning EV ecosystem.

EV Charging and Grid Challenges

The Indian EV charging market is projected to grow from USD787.3 million in 2024 to USD 1,059.9 million by 2025 further to USD 5,695.6 million by 2030. In volume terms, it will rise from 179,000 units in 2024 to 1.61m in 2030. Unplanned EV charging, especially during peak demand hours, can overload local power infrastructure, leading to voltage fluctuations, transformer stress, and even power outages. Without proper load management, utilities struggle to balance supply and demand efficiently. This not only affects grid reliability but also increases energy costs and carbon intensity. Smart, scheduled charging is essential to maintain grid stability and support a sustainable EV ecosystem. Around the world, countries such as the United States, Germany and China face similar problems integrating EV charging infrastructure with decades-old grid infrastructure and fickle renewables. AI as a solution AI represents a critically flexible solution throughout all energy ecosystems, from optimising charge schedules and the control of loads, to the increased stability of the grid.

How AI Addresses EV Charging and Grid Stability

Demand Forecasting

AI leverages machine learning to study past data, traffic, weather, and driver habits to estimate EV charging demand. And in cities like Delhi or Bangalore, it can be used to predict peak usage times during office hours or festivals to be able to more efficiently plan the grid.

2.Smart Charging Optimisation

By using AI in advance, electric vehicles (EVs) can be charged during off-peak hours when electricity costs are lower, taking into account real-time grid conditions and user preferences. This not only optimises energy use but also reduces charging expenses. In the case of Vehicle-to-Grid (V2G) systems—where EVs are equipped to send stored energy back to the grid—AI enables intelligent decision-making to discharge power during peak demand periods. This helps stabilise the grid by easing pressure on the system when energy use is highest. V2G essentially transforms EVs into mobile energy storage units, offering both environmental and economic benefits. Smart charging and V2G together reduce electricity bills and even allow consumers to earn revenue by supplying surplus power back to the grid, making EV ownership more affordable and grid friendly.

3. Load Balancing

Artificial intelligence protects the grid against overload by spreading charges among stations. It can reroute charging demand to less congested stations, potentially preventing congestion in places like central Bangalore, Delhi, Mumbai. The below phenomena are also more crucial

Optimising Power Distribution: AI-powered energy management systems (EMS) monitor real-time grid conditions and dynamically adjust charging rates across multiple EVs and charging stations. This prevents sudden spikes in demand that could destabilise the grid.
Prioritising Charging: AI can prioritise charging based on various factors, such as urgency (e.g., a low-battery vehicle needing to leave soon), battery level, and current grid capacity.
Time-of-Use (ToU) Optimisation: By leveraging dynamic pricing and ToU rates, AI can incentivise EV owners to charge during off-peak hours when electricity is cheaper and the grid is less stressed. This shifts demand away from critical peak periods.
Avoiding "Duck Curve" Effect: AI-driven strategies can help flatten the "duck curve" (a common solar power phenomenon where net demand dips during the day and rises sharply in the evening) by encouraging charging during periods of high solar output and discouraging it during the evening ramp-up.

4. Renewable Energy Integration

AI balances charging with renewable supply, such as solar during the day. It can also forecast the availability of renewable energy sources (like solar and wind), which are often intermittent. This allows for better coordination of charging with periods of high renewable energy generation. It aligns with India’s target of 500 GW of non-fossil capacity by 2030 and reducing dependence on fossil fuels.

5. Battery Management

AI monitors battery health by analysing real-time data such as temperature, voltage, and usage patterns to predict battery wear and optimise charging cycles. This helps extend battery life, prevent overcharging, and minimise sudden grid load spikes, ensuring greater efficiency and reliability.

Unlocking Smart Mobility: How AI is Revolutionising EV Charging for Grid Stability, Cost Efficiency, and Renewable Integration

Reduced Blackouts & Improved Power Quality: AI orchestrates charging, significantly reducing the risk of grid overloads and ensuring a stable, high-quality power supply.
Lower Electricity Costs: AI enables pricing by analysing grid demand patterns, energy supply conditions, and real-time consumption data to forecast peak and off-peak periods. It then adjusts electricity rates, accordingly, allowing users to shift EV charging to lower-cost, off-peak times, thereby reducing their electricity bills and easing grid load
Better Renewable Integration: AI aligns EV charging with solar and wind or said to support India’s ambitious target of having net-zero emissions by 2070.
Scalability with EV Growth: AI can scale with increase in EV adoption with basic infrastructure expected to hit 400,000 charger installations per year by 2030to secure the grid for long duration.

Challenges and Limitations: Barriers to Widespread AI Integration in EV Charging Infrastructure

However, there are still many obstacles to AI application into EV charging, despite the light of promise:

Limited Smart Grid Infrastructure: Much of India, particularly in rural areas, does not have the digital infrastructure to support AI-based load management
Data Privacy Concerns: Users have privacy and security concerns regarding the gathering of their data for customised charging optimisation
High Initial Costs: The costs attached to AI systems and smart chargers can be off-putting, particularly for smaller operators
Lack of Standardisation: Heterogeneous charging hardware and AI platforms with no standardised communication protocols make interoperability and scalability difficult

Outlook: Accelerating AI-Driven EV Charging Toward a Smarter, Greener 2030

The road ahead for AI in EV charging is both promising and dynamic:

Emerging Technologies: Reinforcement learning to balance the grid in real-time and edge AI embedded in chargers are taking off for faster, localised decision-making
Policy Support Needed: It is government incentives and regulations that will need to encourage the deployment of AI-driven charging infrastructure, particularly across semi-urban and rural localities
Vision 2030: AI for a frictionless EV future, balancing loads, renewables and grid stability on a massive scale with the right investments and policy

Conclusion

AI-led innovation is changing the face of India's thriving electric vehicle (EV) ecosystem. While EV adoption is growing quickly in cities and semi-urban regions, AI isn’t just helping make the charging network smarter, it’s designing resilient, future-ready infrastructure.

Charging optimisation, demand management and renewable integration are seen as critical roles of AI. Its intelligent control of power flow guarantees grid stability, and it enables Vehicle to Grid (V2G) systems, making EVs dynamic energy resources. This virtuous cycle with renewables is what is accelerating India towards its moonshot 500 GWs of renewable capacity by 2030 and net-zero emissions by 2070.
With 400,000 new chargers being added every year in India alone by 2030, AI will be the driving technological force propelling the country toward a smooth, scalable, and genuinely sustainable future with electric vehicles. This puts India not only at the forefront of clean mobility, but as a global exemplar of intelligent energy leadership.

- Rajesh Kaushal, Energy Infrastructure & Industrial Solutions (EIS) Business Group Head, India & SAARC, Delta Electronics India