According to a study forecast, by 2050, electricity demand for air conditioners could account for 45% of India's peak electricity demand, compared with 10% in 2016. Second, in India/Cambodia, Indonesia/Vietnam, cutting coal-fired and gas-fired power generation will make renewable power generation facilities (with energy storage) more valuable. SES Power believes that even though the current international economic environment is not ideal, people's desire for energy will only increase day by day, because we all want to live a comfortable life.

　　(1) System results under the reference scenario

　　In the absence of any carbon emissions policy, the research team estimates that by 2030 India could generate 46% to 67% of its electricity from renewable sources.

　　(Basic Parameters and Reference Cases)

　　Notably, the future renewable energy deployment rates simulated by the research team are much higher than they are today: in 2019, for example, India installed 3GW of wind and 10GW of solar. Using the research team's reference case on renewable energy deployment constraints, total renewable electricity generation deployed by 2030 helps reduce carbon emissions by 56% compared to 2020. But carbon emissions still increased by 47% over the same period due to load growth. Simulated emissions in 2050 under the Reference Scenario are also still higher than in 2020. The installed capacity of renewable energy deployed by 2050 is 3.2 times that of 2030, compared to 362 GW in 2030 and 1,148 GW in 2050 (Figure 7.11).

　　The cost of lithium-ion battery energy storage systems is not competitive until 2040, but by 2050 about 244GW/1,091GWh of lithium-ion energy storage systems will be deployed to balance the power system and minimize renewable energy curtailment.

　　As shown, lithium-ion battery storage systems are dispatched to divert power from solar power generation facilities to meet peak power demand at night, with storage systems lasting less than 5 hours on average by 2050.

　　(Hourly generation dispatch and load curves for three days in summer (left) and winter (right) in India in 2050)

　　(Regional Capacity and Utilization Trends for Power Generation and Transmission in India to 2050)

　　(2) Influence of air-conditioning demand

　　The research team used a demand forecasting model to assess electricity demand for a high air-conditioning demand scenario, assuming that India would close the gap in its high air-conditioning demand in line with the global weighted average.

　　The research team's modelling approach suggests that applying optimal air-conditioning demand standards could result in a 13% reduction in electricity generation but a 4% increase in annual carbon emissions by 2050. According to the research team's reference case, the electricity demand for air conditioners accounts for more than 40% of the peak summer nighttime demand (8pm-12am). It contributes less than 20% in the case of high air conditioner power demand. Reducing the demand for air conditioning reduces the demand for electricity generation. The reduction in peak demand also results in a flatter demand curve, which reduces the demand for peak generation provided by natural gas-fired power plants and battery storage systems.

　　The research team's modeling results point to a relationship between the deployment of grid-scale energy storage and air conditioning demand: Under baseline demand conditions, 1,091 GWh of energy storage would be deployed in 2050, rather than 649 GWh. The 40% drop in energy storage capacity in the air conditioner high demand scenario can be directly attributed to the 55% reduction in the contribution of air conditioners to peak demand. Grid-scale energy storage systems primarily take electricity from solar generation facilities and discharge them at night to meet peak demand. Notably, India still deploys a large number of lithium-ion battery energy storage systems, accounting for 38% of the global grid-scale energy storage capacity projected by the research team in 2040. Finally, improving the efficiency of air conditioners can also reduce the investment in deploying energy storage systems that would otherwise require delaying grid upgrades in the short term (2030).

　　(3) The influence of distributed energy storage system (DLS)

　　The deployment of lithium-ion battery energy storage systems helps meet peak demand at the distribution level, thereby changing the demand curve seen in the transmission system.

　　The research team calculated this "transmission-level" demand under two scenarios of distributed energy storage system (DLS) deployment: (1) a reference demand case (demand driver); (2) a low-cost storage system (technology-driven) case factor). Because more distributed energy storage systems (DLS) will only be deployed if it is economically feasible to delay upgrading the grid—in other words, the value of the battery storage investment is less than the value of avoiding grid upgrades. The distributed energy storage system (DLS) can be regarded as a zero-cost load transfer mechanism for the transmission system.

　　The impact of a distributed energy storage system (DLS) on the transmission system is captured by the demand case generated when the energy storage system is deployed, and does not represent the capital cost or operating cost of the distributed energy storage system (DLS). In India, modeled by the research team, cost-optimized distributed energy storage systems (DLS) have a duration of 2 to 4 hours, which is consistent with peak power demand overloads limited by grid capacity and charging durations during off-peak availability.

　　Distributed energy storage systems (DLS) are charged during off-peak periods, which do not necessarily coincide with peak periods of solar generation because, as shown in the model, distributed energy storage systems (DLS) are designed to minimize peak demand and grid upgrades cost, rather than maximizing charging by generating electricity at a lower marginal cost. This results in a decentralized charging process for distributed energy storage systems so that energy storage needs are met by the cheapest available generation resources.

　　(Deployment of Distributed Energy Storage System)

　　As a result, the deployment of distributed energy storage systems tends to shift the installed capacity mix away from solar power facilities and battery storage systems to wind power facilities, which typically have higher capacity factors at night and early morning. Due to growing demand, distributed energy storage systems (DLS) are no longer cost-effective as an alternative to grid upgrades by 2050.

　　The correlation between energy storage systems and peak demand is most pronounced in low-cost energy storage scenarios, where peak shifts enabling distributed energy storage systems (DLS) have a knock-on effect on generation design: less energy is required during peaks energy storage capacity.

　　Overall, factors such as the deployment of distributed energy storage systems and increased air-conditioning power demand shifted or reduced peak demand. At the distribution level, distributed energy storage systems or providing air conditioning efficiency can clearly save costs and help distribution companies minimize capital investment.

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