[L-R] Solarad.ai Co-Founders Bhramar Choudhary (CTO), Ravi Choudhary (CEO), and Haider Abbas (COO)
It all started with Haider Abbas’s research project with Renew Power, a solar energy company in India.
While working on this project, the solar scientist realised the need for better energy forecasting in the renewable energy sector.
“There were some uncertainties in the renewables sector that led to lower energy selling prices and penalties for deviation from energy schedules. This impacted the profitability and stability of solar power projects,” says Abbas, an IIT Delhi graduate.
He sensed an opportunity to improve the accuracy of energy generation forecasts by leveraging advanced technologies like deep learning, satellite imagery, and data analytics to enable solar plant operators to make informed decisions, optimise their operations, and maximise their revenue potential.
That led to the birth of Solarad.ai, a startup providing accurate energy generation forecasts for solar plants and battery storage.
Established by Abbas, Ravi Choudhary (IIT Delhi alumnus) and Bhramar Choudhary (IIT Bombay, ex-JLR), Delhi-based Solarad.ai wants to empower solar plant operators with the tools and insights needed to overcome the challenges of renewable energy generation and trading.
How Solarad works
Solarad.ai uses satellite imagery, numerical weather prediction, and historical solar photovoltaic (PV) generation data to provide “accurate” energy generation forecasts for solar plants and battery storage. Its forecasts are updated hourly and provided in 15-minute time steps, allowing for better energy trading and improved pricing in the energy markets.
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“Imagine a solar plant located in a region where weather conditions greatly impact power generation. Our deep-tech models analyse satellite imagery to assess cloud cover, atmospheric conditions, and other relevant factors. It then combines this information with historical PV generation data and numerical weather prediction to generate forecasts,” he elaborates.
“Let’s say it’s morning, and our deep-tech models predict that the weather will be partly cloudy with intermittent sunshine throughout the day. Solarad.ai’s software predicts the expected power generation for each 15-minute interval based on this forecast. These forecasts enable solar plant operators to optimise their energy trading strategies, making informed decisions about when to sell excess energy or purchase additional power from the grid,” Abbas shares.
As the day progresses, Solarad’s software continuously updates the forecasts to account for real-time weather conditions and fine-tune the accuracy of the predictions. Solar plant operators can access these forecasts through its interface, allowing them to align their energy production with market demands and minimise penalties for deviation from energy schedules.
“By leveraging deep-tech models and advanced data analysis, Solarad.ai empowers operators to maximise their energy generation efficiency, improve pricing decisions, and optimise their overall energy trading strategies,” he claims.
A B2B SaaS platform, the firm already works with a few commercial and industrial companies, but the focus is players with 10MW+ plants.
Tremendous opportunities globally
According to the company, India presents tremendous opportunities as it is one of the world’s fastest-growing markets for solar energy. With the government’s focus on increasing the share of renewable energy in the overall energy mix, there is a significant need for accurate energy generation forecasts and improved energy trading strategies.
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“Solarad.ai can capitalise on these opportunities by providing its innovative solution to solar plant operators in India. By helping them optimise their energy generation, improve pricing decisions, and avoid penalties, Solarad.ai contributes to the growth and profitability of solar power projects in the country,” adds Abbas.
Furthermore, India’s geographical diversity and varying weather patterns make accurate forecasting crucial for efficient energy management. Solarad.ai claims its deep-tech models are designed to handle the complexity of India’s diverse climatic conditions, including monsoons, cloud cover, and extreme temperature variations.
But the Indian solar industry faces several challenges, including:
Uncertainty in renewable energy generation: Solar and wind power generation are dependent on weather conditions, which can be unpredictable. This uncertainty leads to challenges in planning and trading energy effectively.
Grid integration: Integrating renewable energy into the existing power grid infrastructure is complex, requiring accurate forecasting and balancing supply and demand in real-time.
Policy and regulatory framework: Frequent changes in policies and regulations related to deviation settlement mechanisms, tariffs, subsidies, and land acquisition can create uncertainties and impact the financial viability of solar projects.
Financial viability and return on investment: Solar projects require a significant upfront investment, and ensuring a reasonable return on investment over the project’s lifecycle is crucial for sustainability.
Despite the challenges, Solarad doesn’t restrict itself to India. It has identified several key European markets for expansion, such as Germany, Spain, Italy, France, and the United Kingdom. These countries have a significant presence and growth potential in the renewable energy sector, with high adoption of solar power.
“Europe has been actively promoting renewable energy sources and has set ambitious targets for increasing the share of renewables in its energy mix. With a strong focus on sustainability and reducing carbon emissions, European countries offer a conducive environment for our energy generation forecasting solution,” he shares. “Our deep-tech models, which have proven accuracy in forecasting complex and interconnected systems, can help European solar plant operators optimise their energy generation, reduce costs, and maximise revenue.”
Similarly, the US also presents significant opportunities for Solarad.ai. It has a large and rapidly growing solar energy market, with numerous solar plants and a favourable regulatory environment. With the increasing adoption of renewable energy and the need for improved energy forecasting, Solarad.ai can provide its services to solar plant operators across different states.
The startup operates on a subscription-based business model. It charges plant operators a monthly fee for access to its energy generation forecasts and related services. The subscription fee is based on the number of plants a customer has and the value our product provides in terms of increased revenue and savings from penalties.
“As we expand our market presence and enter new regions, such as Europe and the United States, our subscription-based revenue model will remain the core source of income. Additionally, we are exploring opportunities to offer value-added services and advanced features to cater to the evolving needs of our customers and increase revenue streams,” Abbas remarks.
Early this month, Solarad.ai announced the closing of a seed funding round led by India Quotient. The funds will help it in its international expansion.
With the consequences of climate change manifesting and the world slowly transitioning into renewable energy, deep-tech solutions such as the ones developed by Solarad.ai can have a massive role to play. A helping hand from world governments and the private sector could help Solarad co-founders go a long way.
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