On 9 June 2025 and 31 December 2025, India’s power system met almost the same peak demand—about 241 GW. On paper, the two days look identical. In reality, they represent two fundamentally different power systems, facing entirely different reliability challenges. Treating them as equivalent is one of the most persistent analytical mistakes in India’s power planning.
The difference lies not in how much electricity was demanded, but when it was demanded and which resources were available at that moment. Using 15-minute source-wise generation and demand data, these two days expose why annual peak demand is a poor proxy for system adequacy.
1. June 9, 2025, 3:30 PM: A Flexibility-Limited System
The June peak occurred in the afternoon around 3:30 pm to early evening window, when solar generation was still substantial and wind generation was meaningful. Solar output reached around 55–60 GW, wind contributed close to 20 GW, and hydro played a clear balancing role. Thermal generation backed down sharply during solar hours and then ramped up aggressively toward the evening. On the other hand, maximum Net Demand of 217.9 GW (~90% of Solar peak demand) was met on the same day was during non-Solar Hours of 22:45 hrs when Solar contribution was nil and Wind generation was 19.2 GW (~8.8% of Net Demand).
The defining feature of the day was the net-load curve. Midday net demand collapsed to about 155–160 GW, followed by a steep evening ramp of more than 50 GW within a few hours. This is the Indian duck curve in its purest form.
Crucially, system stress did not coincide with peak demand. The most difficult operating window was the post-solar ramp, not the demand peak itself. Capacity adequacy was not the binding constraint; ramping capability, regulation, and flexibility were.
On this day, solar and wind had real capacity value. At the peak, solar alone supplied nearly one-fifth of system demand, and wind and hydro together contributed another ~15%. The system problem was not too little capacity, but too little fast, controllable response.
(data source: https://grid-india.in/en/reports/daily-psp-report)
2. December 31, 2025 , 10:45 AM : A Capacity-Constrained System
December presents a completely different operating regime. The peak occurred at around 10:45 am when solar generation was already declining and wind output was negligible. Thermal generation never dropped below about 140 GW and rose to nearly 175 GW. Hydro appeared in sharp, narrow pulses, characteristic of peak shaving rather than balancing. Nuclear ran flat, while gas remained marginal. On the other hand, maximum Net Demand of 209.3 GW (86.8% of the Solar Peak Demand) was met on the same day was during non-Solar Hours of 18:30 hrs when Solar contribution was 0.24 GW and Wind generation was 3.3 GW (~ 1.6%of Net Demand).
The net-load curve had no duck. Net demand remained high throughout the day and peaked almost exactly when total demand peaked, exceeding 205–210 GW. There was no solar cushion, no midday relief, and very little operational slack.
Here, peak demand and peak net load coincided. Reliability hinged entirely on the availability of thermal and hydro capacity and on reserve margins. A single large unit outage during the peak window would have immediately stressed frequency and reserves. Despite similar peak MW, the December system was materially more fragile than the June system.
(data source: https://grid-india.in/en/reports/daily-psp-report)
3. Same Peak Demand, Radically Different Capacity Contributions
At the June peak, thermal supplied roughly 62% of demand. In December, it supplied about 70%, an increase of nearly 20 GW for the same total load. Wind’s contribution collapsed from a meaningful share in June to statistical irrelevance in December. Solar’s role shifted from a peak contributor to a pre-peak energy supplier with little reliability value. Hydro lost depth due to seasonal water constraints.
4. Capacity Contribution at System Peak
9 June 2025 – Summer peak (solar-assisted):
Thermal: ~149 GW (≈62%)
Solar: ~46 GW (≈19%)
Wind: ~19 GW (≈8%)
Hydro: ~19 GW (≈8%)
Nuclear: ~5 GW (≈2%)
Gas: ~4 GW (≈2%)
31 December 2025 – Winter peak (thermal-anchored):
Thermal: ~168–170 GW (≈70%)
Solar: ~15–20 GW (≈6–8%) - While Solar Peak Generation was ~55.6 GW at 13:15 hrs.
Hydro: ~12–13 GW (≈5%)
Nuclear: ~6 GW (≈2–3%)
Gas: ~3–4 GW (≈1–2%)
Wind: ~1–2 GW (<1%)
5. Seasonal Capacity Credit (ELCC-Style Interpretation)
Using revealed capacity at the 15-minute system peak, a clear seasonal pattern emerges. Solar and wind have non-trivial capacity value in summer, but their winter ELCC collapses. Thermal and nuclear remain the only true winter reliability anchors, while hydro’s peaking value is constrained by seasonal water availability.
Indicative ELCC outcomes:
Summer (June): Solar ~50–55%, Wind ~40–45%, Thermal ~70%.
Winter (December): Solar ~15–20%, Wind ~0–5%, Thermal ~80%.
(disclaimer: This is only indicative ELCC and not simulated with Resource Adequacy Softwares like PLEXOS etc.)
6. The Core Insight: India Does Not Have a Single Peak Problem
India has multiple peak problems, each requiring different solutions. Summer peaks are energy-rich but flexibility-poor, demanding storage, demand response, and ramping products. Winter peaks are capacity-constrained and contingency-sensitive, requiring dependable capacity and reserves. A single MW number hides this distinction.
7. Why This Matters for Policy and Market Design
These two ordinary days expose several uncomfortable truths.
· Annual peak demand is a poor planning metric. Resource adequacy must be season- and time-specific.
· Renewable energy targets cannot substitute for capacity planning.
· Battery storage has asymmetric value, with its highest system value in winter evening peaks.
· Energy-only markets under-price reliability, and tariffs and procurement must reflect time and season.
The Resource Adequacy Guidelines issued by the Ministry of Power / CEA (https://static.pib.gov.in/WriteReadData/specificdocs/documents/2023/jun/doc2023628218801.pdf) do not mandate the use of Effective Load Carrying Capability (ELCC) for assessing capacity contribution, even in systems where renewable energy capacity exceeds 50%. Instead, the Guidelines continue to rely on deterministic capacity credit approaches, which implicitly assume fixed, average availability values for different resource types. While earlier guidance and technical discussions had referenced the use of production-cost and adequacy models such as PLEXOS, recent official communications have increasingly promoted STELLAR, an indigenously developed resource adequacy tool. Notably, the launch version of STELLAR had explicit limitations in modelling ELCC for variable renewable resources, although it is now claimed that these limitations have been addressed through a subsequent plug-in. However, despite these assertions, almost all of the Resource Adequacy Reports published so far—at national or state level (https://cea.nic.in/resource-adequacy-study-report/?lang=en) —have applied an ELCC-based methodology; all continue to use capacity credit assumptions. This creates a clear disconnect between the theoretical importance of coincidence-based capacity valuation in high-RE systems and the methods actually being used for adequacy planning in India.
Conclusion
June 9 and December 31 both reached 241 GW. The summer peak stressed ramps and flexibility; the winter peak tested the foundations of system adequacy. Planning frameworks, market designs, and policy narratives that fail to distinguish between these realities will continue to misallocate capital and misprice risk.
The lesson is simple but profound: 241 GW in June is not the same as 241 GW in December—and designing the power system as if it were is a mistake India can no longer afford.