As India moves towards a low-carbon energy future, managing electricity demand has become as important as increasing supply. Traditionally, power sector planning has focused on expanding generation and transmission capacity to meet rising demand. However, the nature of the electricity grid is changing. The growth of variable renewable energy, decentralised rooftop solar systems, and electric mobility has made grid management more complex. In this evolving context, flexibility on the demand side offers a valuable opportunity to improve efficiency and stability.
Among the tools that support demand-side flexibility, such as energy efficiency and storage, demand response is gaining interest. Demand response allows utilities to reduce or shift electricity consumption during periods of peak demand. This can lower costs, reduce stress on the grid, and delay expensive infrastructure investments. However, in India, demand response remains underutilised. Beyond time-of-day tariffs, regulatory guidance is still evolving and large-scale implementation is absent.
To address this gap in evidence and policy, Tata Power Delhi Distribution Limited (TPDDL) and Centre for Energy, Environment and People (CEEP) partnered to carry out a pilot project. The focus was on a manual, behavioural demand response programme involving domestic electricity users in Delhi. This blogpost highlights key insights, economic outcomes, and future directions based on the findings of the pilot.
What is Demand Response?
Demand Response (DR) is an electric load management programme that seeks to manage electricity demand at the consumer’s end by encouraging them to increase or decrease their consumption. This is often done through financial incentives or penalties. Such programmes are typically designed to manage peak electricity demand, enabling optimisation of power procurement costs and improving the capacity utilisation of generation, transmission, and distribution.
In India, demand response has not yet been fully integrated into power sector planning. Regulatory frameworks have only recently started to recognise the role of demand-side interventions. Until 2021, regulations focused mainly on supply-side solutions. The Central Electricity Regulatory Commission’s Ancillary Services Regulations in 2021 marked a significant step forward. These regulations included demand response as a recognised service that can help manage power quality and reliability.
Despite this progress, implementation remains limited. A few small-scale pilots have been conducted in Delhi, Mumbai, and Jaipur. Most have targeted commercial and industrial consumers. The potential of residential demand response remains largely unexplored.
Demand response allows utilities to reduce or shift electricity consumption during periods of peak demand. This can lower costs, reduce stress on the grid, and delay expensive infrastructure investments.
Demand response allows utilities to reduce or shift electricity consumption during periods of peak demand. This can lower costs, reduce stress on the grid, and delay expensive infrastructure investments.
The Delhi Pilot on Behavioural Demand Response
The CEEP-TPDDL pilot aimed to test whether a manual demand response programme could work for domestic consumers. Automation infrastructure was not used. The goal was to understand whether consumers would voluntarily reduce their electricity use during peak hours if given clear communication and small incentives.
The programme identified 4,449 domestic consumers with smart meters and sanctioned loads of at least 5 kilowatts. These consumers were spread across six distribution zones in Delhi. A total of 2,041 consumers enrolled in the programme. Over a period of three months, TPDDL scheduled 16 two-hour events during periods of expected high demand. Consumers were informed about each event in advance by text messages, emails, and letters.
Smart meter data was used to measure how much each consumer reduced their usage compared to their usual baseline. If a consumer reduced usage by more than 10 percent, they received an incentive of ₹250 for that event. Consumers also received ₹200 for signing up.
Participation and Demand Reduction
The programme achieved a high level of engagement. Out of the 2,041 consumers who enrolled, 1,990 participated in at least one event. On average, 56 percent of enrolled consumers participated in each event. The highest participation was 75 percent, achieved in Event 6, after personalised letters were sent to consumers.
Across the 16 demand response events, participating households reduced their electricity usage by a total of 15.3 megawatt-hours during peak periods. On average, this was a 21 percent reduction compared to their baseline consumption, which was calculated based on usage during the same time blocks over the ten previous days. The highest reduction was recorded in Event 6, at 36.9 percent.
Most participants had sanctioned loads between 5 and 12 kilowatts, placing them in the medium-to-high usage category. Consumers who typically used more electricity were able to reduce a greater number of units during demand response events. However, the proportion of reduction compared to their normative usage was fairly similar across all consumers. For example, a household using 10 units a day might reduce by 2 units, while one using 5 units might reduce by 1 unit—both cutting back by 20 percent.
This suggests that consumers across usage levels were equally responsive to the programme, which is a promising sign for scaling such initiatives more broadly and equitably. It also highlights the behavioural flexibility among residential users, which is critical for managing peak demand, reducing the need to expand generation infrastructure.
Costs, Benefits and Economic Viability
The pilot provided useful data on the economic feasibility of residential demand response. By reducing consumption during peak periods, TPDDL avoided purchasing expensive electricity from the market. This saved approximately 43 percent of the total incentives disbursed. However, reduced consumption also meant lower billing revenue, resulting in a revenue loss of about 25 percent of the total payout. After subtracting this, the net short-term benefit was approximately 27 percent of the total disbursed amount. It is important to note that the high gains resulted from prevailing high prices in the electricity exchange for at least four events.
The more substantive benefit of demand response lies in deferring or avoiding future capital investments if such instruments are integrated into the power procurement planning. Because peak demand can be altered, the utility could potentially delay investments in generation and transmission infrastructure. Based on conservative estimates, the savings from deferred generation and transmission capacity were significantly higher than short-term gains. The total estimated benefits from DR programmes are likely to far outweigh the cost of implementation.
The more substantive benefit of demand response lies in deferring or avoiding future capital investments if such instruments are integrated into the power procurement planning.
The more substantive benefit of demand response lies in deferring or avoiding future capital investments if such instruments are integrated into the power procurement planning.
Insights on Consumer Behaviour
The behavioural demand response programme offered several observations on consumer participation and response patterns.
Participation was highest in Event 6, which followed the dispatch of customised letters to enrolled consumers. In contrast, announcements of additional incentives through a lucky draw, made before Events 5, 10, 13, and 16, did not result in any significant improvement in participation or demand reduction. This suggests that consumers responded more positively to personalised communication than to promotional incentives.
The incentive structure was simple: ₹200 for enrolment and ₹250 for each event in which the consumer reduced electricity consumption by at least 10 percent compared to their baseline. A total of ₹39.65 lakh was disbursed in incentives during the programme, translating to a cost of approximately ₹258 per unit of curtailed demand. The incentive offered was disproportionately high compared to the utility’s potential benefit. As such, the study does not offer certainty about consumers’ willingness to participate in a long-term programme with lower incentives.
The programme also required significant effort to manage communications and data manually.
Implications for Policy and Planning
The findings from the behavioural demand response programme demonstrate that even a manually operated model, targeted at domestic consumers, can deliver measurable benefits to the grid. However, translating this into a scalable and reliable resource requires deliberate shifts in planning, regulation, and operational design.
To begin with, demand response needs to be recognised as a core element of electricity sector planning. It should be integrated into demand forecasting and long-term resource adequacy frameworks, rather than being treated solely as an instrument for short-term or emergency demand management. Its primary value lies in reducing peak demand and deferring costly investments in generation and transmission infrastructure. These benefits are often overlooked in conventional planning models that focus primarily on physical assets.
For utilities to adopt demand response at scale, there must be market mechanisms that allow recovery of programme costs and encourage investment in the necessary infrastructure, particularly automation and data systems. Strengthening the technology infrastructure, including improving the time resolution of smart meters from 15 to 5 minutes, can enhance targeting precision and programme efficiency.
Building operational certainty is equally important. So far, demand response pilots in India have been limited in duration and scale. Sustained, large-scale programmes are necessary to understand how consumer behaviour evolves over time, how incentive strategies perform under real-world conditions, and whether the model can deliver consistent results. Short-duration, annual programmes focused on managing daily peak periods could offer a practical starting point while building confidence in net benefits.
The scope of participation should also be expanded. While this pilot focused on households with sanctioned loads above 5 kilowatts, future programmes should include smaller domestic consumers. This segment offers two important advantages. Their large numbers make them a valuable aggregate resource, and their lower tariff rates reduce the financial impact on utility revenues when demand is curtailed.
Finally, the success of demand response as a strategic resource depends on a shared understanding of its value. Many of its benefits, such as avoided investments, are not immediately visible and require coordinated recognition across regulators, utilities, and other stakeholders. A regulatory roadmap that incorporates these longer-term advantages and supports the evolution of demand response from pilot to policy instrument will be critical.
For utilities to adopt demand response at scale, there must be market mechanisms that allow recovery of programme costs and encourage investment in the necessary infrastructure, particularly automation and data systems.
For utilities to adopt demand response at scale, there must be market mechanisms that allow recovery of programme costs and encourage investment in the necessary infrastructure, particularly automation and data systems.
A Way Forward
The CEEP-TPDDL pilot confirms that behavioural demand response is both technically and economically viable. It provides a replicable framework that can inform future regulatory and planning decisions. However, unlocking its full potential will require targeted reforms and institutional readiness.
Demand response offers measurable benefits, particularly in reducing peak demand and deferring investment in new generation and transmission infrastructure. These benefits are often less visible in conventional power planning. Recognising and valuing demand-side resources appropriately within regulatory and planning processes is essential.
Future efforts must focus on increasing operational certainty through longer-term and larger-scale pilots. Improving the time resolution of smart meters, from 15 minutes to 5 minutes, can enhance programme precision. Including consumers with lower sanctioned loads, particularly those below 5 kilowatts, will also expand reach while keeping revenue impact manageable.
Realising the value of demand response as a grid management tool will require a clear regulatory roadmap and broader stakeholder dialogue. The learnings from this pilot provide a foundation for such progress.
The article is edited by Anshuman Gothwal, Co-founder and Director-Programs at CEEP.
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