The ordinary citizen may not know much about the electricity sector. But she is familiar with power-cuts and weird, distorted tariff policies. The situation has improved over the years, especially in large cities. But much of our population still suffers from informal connections and frequent outages.

Before we can improve, it is important to understand what India’s demand for electricity is and how it is served today.

Data is now published in various websites of Government departments and Utilities. But these datasets are not easy to collate and work with for researchers and analysts. So Earthmetry has created a repository of important datasets for India in sectors like electricity, oil & gas, air quality and climate change.

Using these processed and cleaned datasets¹, we can characterize the demand for electricity in India.

Let us start with the big picture. The weekly average load for the last one year demonstrates significant variation in electricity demand².

Some of the variation you see is the expected seasonality. You can see a dip in the winter and slow rise in demand in the spring. This trend halts due to the second wave of the pandemic. A steep rise towards the high summer demand has followed as the lockdowns are removed and monsoons are delayed in several places.

The peaks in summer see a significant contribution from the need for air conditioning. This is only expected to rise as the world gets hotter and more cooling is need. Efficient cooling is therefore an important topic for technology and policy research.

What about a typical day? Here is the chart for a recent summer day.

You can see that demand picks up as people wake up and start work. A high peak is observed during late morning through afternoon. This drops off towards the end of the work-day. There is an evening peak as the lighting load and appliances at home turn on, followed by a drop off to the day’s lows as people sleep.

A winter day is different. In the chart below, the same summer day has been squished due to the higher variation we see in the winter. This could be due to the absence of cooling demand, especially at night.

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Many places in India do need heating in the winter. But most of the heating seems to happen through other, more polluting, energy sources.

If we summarize the variation in the last one year by using hourly averages and ranking them, we get a “load duration curve” used often by system planners. Rank 1 is the hour with the highest average load in the year and so on. The blue line is the load varying with the rank of the hour.

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The yellow line marks the minimum demand seen during the year. We must always generate at least this much power.

The peak demand is about 195 GigaWatts (GW) while the minimum is about 105 GW. The top 100 hours in the year need more than 183 GW of generation.

This advises how we plan our power generation capacity:

• We must have a capacity above the peak demand with some buffers
• Many power plants will be idle for significant periods of time while helping meet peak demands
• Demand can suddenly rise or fall and power generation must cope with it on time

Moreover, due to climate change we have to switch to renewables. Here is how a typical day looked like in terms of energy sources. The Y-axis is not truncated, so things look comparatively squished.

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You can see how solar energy helps meet the day-time peak so that coal generation stays flat. But as the sun sets, hydro and coal generation have to rise to accomodate the evening peak.

Our switch to renewables, therefore, needs to account for the mismatch between when energy is generated and when it is consumed. This can be addressed using:

• peaking power plants that use fossil fuels
• energy storage using batteries or pumped water in hydro plants
• external purchases

We need to understand climate patterns to properly characterize renewable generation. Earthmetry provides climate data using ECMWF’s (European Centre for Medium-Range Weather Forecasts) reanalysis datasets that enables such analysis. We will cover this in a separate post.

Coming back to demand, we need to track it at the state level. This is necessary because:

• The demand profile of each state varies due to their climate and socio-economic characteristics
• In India, the state is responsible for power procurement and delivery

On a winter day, Uttar Pradesh (UP) is colder than Madhya Pradesh (MP) and Tamil Nadu (TN) so its power usage climbs later and drops off earlier. The higher evening peak in UP could be driven by the greater need for heating.

A good understanding of demand at multiple levels is essential for policy analysis and planning. It is also a requirement to use simulators such as GenX from MIT-Princeton or Rumi from Prayas to model energy systems.

In the next few articles we will delve into electricity scheduling, generation and purchase.

Earthmetry helps our users work with a wide variety of datasets on one platform. Please reach out to learn more.

[1]: Data sources: All India and state-level power demand published by the Ministry of Power on its websites

[2]: What we call “demand” in this article is really consumption. The true demand will be higher as there will be some unserviced demand. This is a simplifying assumption.

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