With the growing share of wind and solar energy in India’s power mix, ensuring the smooth integration of these sources into the grid poses a major challenge. The variable nature of these renewable sources, influenced by weather conditions, creates uncertainty in terms of generation predictability and stability. To ensure grid stability, forecasting and scheduling (F&S) and deviation settlement mechanism (DSM) regulations were brought in, requiring grid operators and developers to accurately forecast renewable energy generation. Inability to do so – within a prescribed range – would invite penalties.
In several of our conferences, industry stakeholders have highlighted the difficulty in complying with the stringent F&S and DSM regulations. The issue was further underscored when a Renewable Watch team recently visited various project sites across Gujarat and Rajasthan. Interactions with site and operations and maintenance (O&M) managers gave a first-hand view of the on-ground complexities faced by developers, especially small developers, in accurately forecasting generation, particularly during unexpected cloud cover, and, therefore, having to pay penalties. Following these visits, our team interviewed some more developers and researchers to understand the issue in detail and, more importantly, come up with possible policy solutions to improve forecasting accuracy and reduce the penalty burden on developers.
A look at the F&S and DSM regulatory landscape, the challenges faced by developers, and some policy suggestions based on our learnings…
Background
To address the challenge of integrating large-scale renewables, India introduced F&S regulations to help system operators plan despatch efficiently while ensuring grid stability. The DSM framework was established to enforce discipline by keeping power generation and consumption within predefined limits. By curbing excessive deviations in energy injection or withdrawal, DSM regulations help safeguard the grid. The Forum of Regulators has provided model regulations for F&S, which various states have adapted according to their specific grid conditions and renewable energy penetration levels.
While there are some variations between the state regulations, Rishu Garg, Policy Specialist, CSTEP, summarises the key highlights of the F&S regulations:
- Mandate for renewable energy generators to submit day-ahead generation forecasts and schedules to the respective state load despatch centres. These forecasts are used for despatch planning and commercial settlements.
- Provisions for managing deviations from scheduled generation, such as deviation charges, tolerance bands and penalties for persistent deviations.
- Coordination mechanisms with central agencies like renewable energy management centres and regional load despatch centres to enhance forecasting accuracy and ensure seamless integration with the national grid.
- Incentives and support mechanisms such as financial incentives, technical assistance and capacity-building programmes to encourage the adoption of F&S practices by renewable energy generators.
Challenges and solutions
Despite a robust regulatory framework in place, sector stakeholders have faced several challenges. One of the biggest hurdles in renewable energy forecasting is its dependence on weather conditions. Wind forecasting requires accurate wind speed and direction predictions, particularly in regions with complex terrain or microclimates. Even minor shifts in atmospheric conditions can significantly impact wind energy output, making precision crucial. Similarly, solar forecasting depends on cloud cover and radiation predictions, where sudden changes in weather can lead to substantial deviations in expected generation.
Extreme weather events, such as storms or rapid cloud movements, further complicate forecasting. These unforeseen conditions can cause significant generation fluctuations, exposing developers to substantial penalties under DSM regulations. While advanced forecasting tools help mitigate errors, the rigid penalty structure does not always account for unpredictable weather shifts. Meanwhile, for grid operators, high forecasting errors make managing grid congestion and frequency challenging.
As a solution, Nathsai Parashar, Manager, ACME, suggests a more flexible penalty system that considers extreme weather as a force majeure event, as rigid charges disproportionately affect smaller developers and projects with lower tariffs. He adds that for developers, penalties remain a challenge when extreme weather events occur unexpectedly, and they believe more flexibility in penalty structures could be beneficial, especially for rare, unpredictable weather phenomena. The quantum of penalties can vary, but on days with extreme weather events such as storms or sudden changes in cloud cover, penalties are typically substantial, particularly when energy generation deviates significantly from the forecasted values.
Financial viability is another concern. Developers face financial strain, as DSM charges can be disproportionately high, especially for smaller projects. The current penalty framework often imposes fixed charges regardless of project size, creating an unfair financial burden on smaller developers. This discourages investment in renewable energy and increases electricity costs for consumers. As a solution, Garg suggests an adaptive approach – DSM charges based on a percentage of the tariff (rather than as a fixed amount) – which could be beneficial for developers.
Advancements in artificial intelligence (AI), machine learning (ML) and big data analytics have significantly improved renewable energy forecasting accuracy. AI-driven models analyse historical weather data, satellite imagery and real-time measurements to refine predictions. These technologies not only improve day-ahead forecasts but also provide short-term and probabilistic forecasts that quantify uncertainty, enabling better risk management.
ML models have proven particularly effective in reducing forecasting errors during extreme weather conditions. They continuously adapt based on real-time data, improving their predictive capabilities over time. The integration of high-resolution meteorological data further enhances forecast precision, especially in regions with rapidly changing weather patterns.
Parashar shares that in one wind project he worked on in his previous organisation, he was able to prevent significant penalties due to an unexpected weather shift by relying on a forecasting system that provided real-time data on wind speed and direction. This allowed the company to adjust turbine output and scheduling efficiently. Similarly, in one solar project, the integration of localised solar radiation forecasts helped in quickly reacting to cloud cover changes and adjusting operations accordingly. Leveraging advanced forecasting technologies in both wind and solar projects has allowed them to reduce forecast errors and minimise penalties despite weather uncertainties. Furthermore, integrating real-time data from operational sites into these systems helps in refining models continuously, enhancing the precision of future forecasts.
For this, collaboration between renewable energy developers and meteorological agencies plays a key role in ensuring accurate forecasting. Access to forecasting models and localised weather data gives developers a competitive edge. Specialised forecasting solutions, such as cloud cover predictions for solar plants or turbulence assessments for wind farms, can help optimise generation planning. Additionally, the aggregation of forecasts across multiple generators can balance out individual forecasting errors, improving overall accuracy at the grid level.
Overall, the current penalty structure under DSM regulations needs to evolve to accommodate the realities of renewable energy generation. A more flexible system that accounts for extreme weather events could provide relief to developers while ensuring grid stability. Policymakers could consider transitioning from fixed DSM charges to a percentage-based system linked to project tariffs going forward. This would create a balanced approach where penalties remain proportional to project economics without impacting financial viability. Additionally, regular monitoring and revisions of DSM charges are necessary to align regulations with market conditions and technological advancements. Incentives for accurate forecasting could also drive innovation and investment in forecasting technologies.
Going forward, energy storage solutions can also play a crucial role in mitigating forecasting risks. By integrating battery storage with renewable energy projects, developers can compensate for deviations and reduce dependence on real-time grid adjustments. Storage solutions can serve as a buffer against fluctuations, improving reliability and reducing the financial impact of DSM penalties. “Enhancing the uptake of storage systems for managing variable renewable energy should be considered for aiding a smooth transition towards a more sustainable and resilient energy system,” says Garg.
The way forward
India’s energy transition hinges on the effective integration of renewable resources into the national grid. While F&S regulations are indispensable for maintaining grid reliability, there is significant room for improvement.
As distributed renewable energy sources become more prevalent, it will be essential to integrate them into the F&S framework. Garg adds that the increasing deployment of distributed renewable sources calls for revised regulations that account for generation at the distribution level. Currently, distributed renewable energy sources are not mandated to follow forecasting norms, but as their contribution grows, integrated F&S mechanisms will be essential. Further, bringing uniformity to DSM regulations across states could enhance regulatory consistency and reduce compliance complexities for developers operating in multiple regions. Standardised penalties and incentives across states would create a more predictable policy environment, encouraging greater investment in renewable energy.
Regular monitoring and revisions of DSM charges are essential to align regulations with market conditions and technological advancements. The regulations should be simple and clear. “As state regulations have different frameworks and charges, they may appear complex. Therefore, more clarity should be provided on forecasting aggregation, tolerance bands and intra-day revisions, in accordance with the states’ geographical features and policy and regulatory environments. Further, considering the falling prices of renewable energy tariffs and the lack of accurate forecasting, the current penalties are very steep. Regulations should consider reviewing the penalty structure.” says Garg.
Market-based solutions, such as real-time electricity markets and balancing mechanisms, could provide economic incentives for accurate forecasting. These mechanisms would allow price signals to naturally encourage better forecasting accuracy without relying solely on administrative penalties. Aligning with global best practices, such market-driven approaches, could enhance the efficiency of India’s renewable energy sector while reducing regulatory burdens.
With India’s ambitious clean energy targets, policymakers must continue refining regulatory frameworks to encourage innovation, ensure fair compliance mechanisms and create a resilient energy system. F&S and DSM regulations are some of the most important regulations in the renewable space, requiring the focus of regulators to address stakeholders’ concerns and ensure efficient grid balancing.
Preeti Wadhwa
