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Introduction

Renewable energy is booming. In 2024, the world added a record 585 GW of clean power, and grids everywhere are stepping up to welcome the surge. India mirrors this momentum: its renewable capacity crossed 234 GW in June 2025, putting the nation in a strong position to save fuel and cut carbon at scale. The next leap is smarter orchestration that turns torrents of weather, market, and asset data into real-time decisions. When utilities trade static spreadsheets for digital twins and AI-driven dispatch, they can trim curtailment fees, ease local bottlenecks, and unlock the full value of every new megawatt, keeping solar parks productive and neighborhood feeders reliably green.

Tata Power tackles this data‑to‑action gap head‑on. Satellite imagery identifies conflict‑free sites, GIS layers trace every conductor, hyper‑local forecasts, and AI dispatch engines squeeze maximum output into tight trading windows, and digital twins surface design flaws long before construction. Each layer transforms raw information into clear, rapid decisions that cut losses, lift utilization, and keep India, and the wider world on track for net‑zero targets.

The pages that follow unpack how these tools, processes, and people turn intermittent resources into round‑the‑clock reliability.

Building strong data foundations with GIS and satellite data

Mapping every detail of the network

A well-managed power network requires detailed knowledge of its infrastructure. Tata Power’s enterprise GIS holds the full anatomy of its network: Extra High Voltage corridors, HT and LT feeders, substation locations and customer nodes down to the low-voltage level. These layers drive Advanced Distribution Management Systems (ADMS), outage analytics and customer service. In-house tools such as the Mobile-GIS assisted system for Restoration & Care (maRC) pin trouble calls to exact poles, allowing quick dispatch of repair crews, significantly reducing downtime and service interruptions. Comprehensive mapping supports advanced grid management systems, precise outage analytics, and efficient customer service.

Transforming site assessments with satellite imagery

Satellite imagery has transformed renewable energy site selection. A joint study with MIT proved the value of satellite imagery when scouting microgrid sites in remote villages. Roof geometry, tree shade, and road access that once took weeks of fieldwork now arrive in minutes on a browser. For utility-scale projects, this satellite imagery also helps identify land-use conflicts, biodiversity concerns, and proximity to transmission infrastructure long before physical visits occur.

 

Sovereign AI is important to develop homegrown AI capabilities

Sovereign AI is important to develop homegrown AI capabilities

Weather intelligence & forecasts that save money

Partnering with Tomorrow.io for precision

A partnership with Tomorrow.io streams proprietary observations. Using advanced mesoscale weather models and low-earth-orbit satellite feeds, operators receive precise forecasts for temperature, wind speed, cloud cover, and solar irradiance up to ten days in advance.

Lowering costs through improved accuracy

Better forecasting significantly reduces scheduling errors, thereby decreasing deviation penalties imposed by grid regulators. Two critical workflow improvements include:

1. Day-ahead schedules. By predicting solar and wind generation with tighter error bands, deviation penalties were slashed under the Deviation Settlement Mechanism.

2. Intra-day adjustments. Real-time updates allow our control rooms to re-balance, and re-shuffle energy purchases, reserves, and storage dispatch within minutes inside the trading window.

Internal analyses consistently demonstrate that even a 1% improvement in forecast accuracy dramatically reduces penalties and enhances renewable energy utilization.

Intelligent optimization with AI simulations and market analytics

Intelligent market decision-making

Algorithms digest historic demand curves, market prices from DAM (Day-Ahead market), GDAM (Green Day-Ahead market), and RTM (Real-Time Market), plus regulatory limits to propose optimized buying and selling strategies. These buy-sell strategies not only increase profitability but also ensure a consistent reduction in carbon intensity.

Digital twins for long-term viability

Before beginning work on a project, numerous AI-driven simulations assess potential sites by integrating weather variability, local terrain characteristics, infrastructure parameters, and grid limitations. These "digital twins" predict 25-year energy yields, identify possible curtailment issues, and flag environmental concerns such as wildlife corridors that require design tweaks, ensuring long-term project sustainability.

Proactive maintenance through predictive AI

Real-time Supervisory Control and Data Acquisition (SCADA) combined with AI models proactively identify anomalies such as equipment wear or inverter issues before a power outage. Maintenance teams can thus schedule preventive actions during low-demand periods, ensuring minimal disruptions.

Gen-AI tender reviews

Generative AI platforms quickly summarize lengthy tender documents, identifying potential risks and opportunities, reducing review times from days to mere hours

BluWave‑ai: Real-time efficiency with AI-driven dispatch

Real-time market conditions often impose strict penalties for inaccuracies in energy scheduling. AI-driven platforms help utilities generate precise day-ahead and intra-day dispatch plans. After extensive testing that demonstrated superior performance compared to traditional tools, leading utilities have integrated these AI solutions for continuous, real-time decision support.

A pilot that became a three‑year agreement

India’s real-time market imposes stiff penalties when schedules miss the mark. To stay ahead, Tata Power piloted BluWave-ai’s cloud platform, which uses neural networks to generate intra-day and day-ahead dispatch plans. After a six-month pilot that outperformed legacy tools, Tata Power signed a three-year deal with BluWave-ai to generate 35,000-plus dispatch recommendations each year.

Solving India’s new scheduling rules

The platform ingests live weather feeds, historical plant output, and grid constraints. A control-room dashboard shows risk bands and suggests re-bids within minutes of a weather change. The collaboration earned a Diamond Trophy from the India Smart Grid Forum, validating both the technology and its impact.

Highlighting this, Sanjay Banga, President, T&D, Tata Power, said, “We are working with BluWave-ai to operationalize Artificial Intelligence in our day-to-day power distribution in Mumbai. Working with AI-enabled system improvements via cloud computing in real-time operations enhances our baseline systems, resulting in higher operational efficiency and accuracy.”

The result: Scheduled deviation penalties drop, power-purchase costs stay lean, and operators gain a real-time co-pilot instead of spreadsheets.

Optimized generation still needs a responsive grid; that is where ADMS, microgrids and storage come in.

 

AI and technology integration helps in achieving renewable energy targets

AI and technology integration helps in achieving renewable energy targets

Advanced grid management solutions

 

India’s first ADMS-enabled network

Tata Power-DDL merged SCADA, DMS, and Outage Management into one platform that suppresses fault waves and restores supply in minutes. Integrating Advanced Distribution Management Systems (ADMS and forecasting outages ahead of adverse weather conditions, grids can prepare backup reserves, drastically reduce downtime, and improve overall service reliability.

Digital-first microgrids

Microgrids now rely on digital design tools and low-cost smart meters, allowing remote monitoring and management. These self-sufficient grids can operate independently (island) during outages, providing uninterrupted service, and can even feed excess renewable energy back to the main grid.

Battery energy storage systems

Grid-scale battery storage systems efficiently manage excess solar power, absorbing midday surplus and supplying peak demand during evening hours. Intelligent dispatch algorithms optimize battery operations, balancing cost efficiency with reliability.

These insights underline the critical role of AI and technology integration in achieving Tata Power’s ambitious renewable energy targets.

Tech-led impact on India’s clean energy push

Effective technology integration clearly impacts energy distribution efficiency and profitability. Globally, renewable energy systems leveraging advanced technologies have successfully reduced transmission losses and improved operational performance significantly.

Highlighting AI’s operational impact, Praveer Sinha, CEO, Tata Power, emphasized, “In a place like Delhi when we started many years back, the AT&C loss that is technical and commercial loss used to be 53%. Now we are at 6% and that is the saving that has happened. In the last 17 quarters, we have shown improvement in our performance and this has been the 17th consecutive quarter of growth in our PAT compared to the previous year same quarter and we expect that this will continue.”

Further discussing clean energy prospects, Dr Sinha further stated, “India has very ambitious plans to add nearly 300 gigawatts of clean energy between now and 2030 which means that we will add nearly 40 gigawatt every year. Our run rate in the last six-seven years was 15 gigawatts. So, we would see a huge amount of capacity in addition to clean energy, and we are now transitioning from just pure solar and wind to 24x7 clean energy solutions."

These insights underline the critical role of AI and technology integration in achieving Tata Power’s ambitious renewable energy targets.

Building robust, localized AI capabilities

For any nation, developing homegrown AI capabilities is crucial. Localized AI capabilities ensure that data-driven decisions are contextually relevant, secure, and tailored to specific regional needs.

Tata Sons chairman N. Chandrasekaran framed the larger mission:

“Sovereign AI is very important. If we don’t develop sovereign AI capabilities, we have a major risk of having all our activities processed by systems that do not understand India.”

He outlined four layers: Foundational computing, model capability, application suites, and governance, and four pillars: technology, data, talent, and oversight. Tata Power’s roadmap maps neatly to that structure:

 

Pillar

Tata Power actions

Foundational infrastructure

Creating centralized data hubs consolidating GIS, SCADA, and market analytics.

AI model development

Building indigenous models that predict energy demand, pricing dynamics, and detect equipment anomalies.

Application development

Deploying practical AI-driven tools such as tender review automation, guarantee management, and hyper-local forecasting.

 

Governance

Implementing strict security protocols and transparent auditing processes to manage AI applications responsibly.

 

Complementing this technological backbone is the development of skilled local talent. The Green Energy Skill Centre launched by Tata Power Skill Development Institute in Delhi trains technicians in solar PV, energy storage, and pumped-hydro systems, ensuring India’s AI workforce speaks the language of power engineering.

By knitting local data, local talent, and open-source tooling, Tata Power aligns with the India AI stack vision while cutting reliance on overseas black-box models.

Innovative solutions shaping the future

Pumped hydro for round-the-clock storage

Globally, pumped hydro storage is re-emerging as a vital technology to manage renewable energy intermittency. An MoU with the Govt. Maharashtra will deliver 2,800 MW of pumped-hydro storage at Shirawta and Bhivpuri. The scheme shifts daytime solar into night-time peaks and operates for decades with minimal degradation.

Grid-scale batteries

Tata Power Renewable Energy has signed its first Battery Energy Storage Purchase Agreement  - 30 MW / 120 MWh in Kerala to flatten evening peaks and smooth wind ramps, complementing an existing 100 MW solar-plus-storage project in Chhattisgarh.

Vehicle-to-Grid pilots

In 2024, in Delhi, Tata Power Delhi Distribution Limited (Tata Power-DDL), which supplies electricity to around 7 million residents in North Delhi, signed a Memorandum of Understanding with the India Smart Grid Forum (ISGF). The partnership will support a Vehicle-to-Grid (V2G) technology demonstration project to show how electric vehicles can both draw power from the grid and feed stored energy back, improving grid flexibility and advancing Delhi’s shift to a smarter, more resilient network.

Scaling targets and capital

The global transition towards clean energy demands ambitious targets. Utilities globally are significantly ramping up renewable capacity additions, aiming for substantial growth by 2030 -

In October 2024 at the FT Energy Transition Summit India, CEO & MD Praveer Sinha said Tata Power would reach about 31 GW of capacity by 2030, with roughly 70% (~22 GW including hydro) from renewables, aligned to a net-zero-before-2045 goal and supported by “drastically” declining prices. The company then had 15 GW installed (about 6 GW renewable) and a 5 GW pipeline. Framing the task, he said, “The understanding we as a power utility have is that during different hours of the day, during different periods of the year, (customers) will have different requirements… At some stage, I will give them 100% renewable power when I bundle it with battery storage, pump storage, and hydropower.” Tata Power Renewable Energy later signed an MoU with Andhra Pradesh to explore up to 7 GW of solar, wind, and hybrid projects, an investment of about ₹49,000 crore.

Bottomline

The successful future of renewable energy hinges on precise, technology-driven decision-making. Comprehensive real-time weather modeling, advanced GIS mapping, AI-powered predictive analytics, and intelligent grid management solutions are crucial for transitioning renewable energy from intermittent to dependable power sources. By deploying digital simulations that anticipate decades of operational conditions and AI-driven systems that optimize daily grid performance, renewable energy can achieve unprecedented levels of reliability. Furthermore, nurturing localized AI capabilities ensures these innovations remain relevant, secure, and tailored to specific regional needs. Ultimately, achieving global net-zero targets demands that every renewable energy decision be informed, timely, and integrated across systems. With robust technological infrastructure, insightful analytics, and skilled local talent, the vision of sustainable, 24x7 renewable energy is becoming a reality, not just an aspiration.