India energy scenarios 2047

Planning Commission is modelling energy scenario by putting all relevant numbers together into a calculator called the India Energy Security Scenarios (IESS) 2047. 

India needs to make large investments in its energy sector.  So far, policy makers have been focused more on investments on the supply side, and not on efficiencies on the demand side.  This has been a natural outcome of the Indian energy situation wherein our per capita consumption of energy (fuels and electricity), has been much below the global average. Furthermore, if India is to step up energy availability, it will have to make large investments in the energy supply infrastructure.  The additional concern to enhance self-dependence in energy, also calls for major investments in exploration and exploitation of oil, gas, coal as well as in the renewable energy segment. 

The India Energy Scenarios, 2047 exercise reveals that if our demand sectors were to adopt energy efficient technologies, it could help reduce energy demand in a big way, and also help India achieve higher levels of energy security by lower energy demand/imports.  However, energy efficiency requires investments in technology and capital equipment, as well as a shift in energy consuming patterns, all of which have large cost implications.  It is also apparent that investments in raising self-dependence, may not necessarily result in a lower cost of supply, but bring in a number of benefits to the economy including energy security. 

However, investments on demand side also bring financial returns by saving energy costs, and depending on the economics, return the investment over a period of time.  Hence, in an economy such as ours, we also need to consider cost reduction by inducting superior technology and through other measures, which may have upfront cost implications, but are net money savers in the long run. 

This investment decision is, however, more complex on the demand side than on the supply side owing to several reasons. 

  • The principal one being that the investments are often to be made by ‘non-financial actors’ (e.g., households in residential dwelling units, ordinary citizens in purchase of automobiles), who may not wish to make large upfront investment in a consumable item, like LED bulbs/fuel efficient vehicle (EV), or even by a farmer in a more efficient irrigation pump set – all the above decisions involving substitution of lesser efficient equipment.
  • This decision also becomes complex, because the choice requires an accounting exercise to compare upfront expense (which may itself have a loan component), and the savings in reduced energy bills over a period of time. 
  • Government, therefore, needs to simplify the adoption of energy efficiency by helping reduce the upfront cost by a slew of measures including “sweetening” the deal - subsidizing the shift to energy efficient devices. The costing component in the IES, 2047 could help in taking public policy decisions on funding energy efficiency.

Against the above background of cost involvement, both on the energy supply and demand sides, the tool would not achieve its intended objective of helping in evaluating different pathways of achieving energy security, if it were not to provide cost implications (expenses on technology upgrade and savings on higher levels of energy efficiency).  Therefore, it has been developed to provide unit costs for all the sources of energy, as well as the different technologies on the demand side which lead to lower energy usage, for an equivalent level of service.  As the tool undertakes to provide implications during the medium to longer term leading up to the year 2047, it will be necessary to adopt certain assumptions both on the likely prices in the future, as well as deriving the present value of future costs/savings.


The objective of the costing exercise, as mentioned earlier, is to inform the user of the cost of inducting technology in becoming energy efficient, as well as the choice of fuel.  However, higher efficiency levels also imply lower levels of energy consumption.  It has already been explained earlier with each Level is neutral to the level of service delivered/supply of output – the same quantum of service is supplied at all Levels.  Therefore, while the economy realizes the same level of delivery of service/output, the energy consumption comes down, and the degree of energy imports reduces, thereby enhancing self-dependency/energy security.  It has already been discussed separately that energy security is a function of several inputs including lowering of demand and also enhancing domestic levels of production of energy. The latter is in turn, achieved by higher levels of renewable energy as well as higher level of domestic fuel output.
The value offered by the cost related exercise in the IES, 2047 gives cost numbers for comparison between different energy pathways.  The comparison methodology is explained as follows:

  • The user has the choice of adopting combinations of different levels of demand sectors.  A combination of a more efficient level in a particular demand sector, let us say in transport (adoption of EVs/urban metro), with an inefficient level of another sector, let us say in industry (poor progress in achieving PAT targets) could be compared with reverse choices, i.e., inefficient levels of transport and more efficient levels in industry.  These 2 pathways would result in different cost implications, both on the energy supply side as well as the demand side. In the former, energy prices may vary due to difference in the units of energy used in the two different technologies, and also due to different prices of the source of energy (coal or oil) used in transport and industry. On the demand side, induction of technology in transport/industry would have different cost implications. 
  • A comparison between the two (on demand and supply sides) would yield an input to the user, for a decision as to which sector to adopt for interventions in the economy. Costs would be an important determinant.  Therefore, for the same level of energy savings effected by interventions in different sectors, a comparison of overall cost implications would be available for the user to compare. This helps to compare one pathway with another. 
  • The user is also able to notice the net cost implication of a particular pathway by moving up the ladder in the efficiency levels, inter se, within one sector.  E.g., if the user were to move the lever in one particular sector, the Excel model in the tool would yield the differential costs to the economy by this change.

Therefore, the costing exercises in the IES, 2047 is a useful input for financial evaluation of becoming more energy efficient within a sector, as well as across sectors, or compare the cost involved between two different energy pathways.


The Calculator factors in real prices throughout the period leading up to the terminal year 2047.  It, therefore, eliminates the role of inflation. The next issue is of movement in prices. Estimating likely prices, especially for technologies that would kick in/scale up at different points of time, would have rendered the exercise too complex. However, it is not as if the above two factors have not been accounted for in the costing exercise, and both have been included in arriving at costs of pathways as is elaborated below. It is acknowledged that the variation in prices of different technologies in the future would not be of a uniform order.  Some of the newer technologies are expected to see larger reduction in prices in percentage terms than the older ones.  The tool takes care of this varying degree of price reduction.  The capital costs are charged equally over the life of the asset, and then by dividing the annual reduction in value over the service rendered. For example, the cost of an aircraft would be spread over its life, and the annual reduction would be spread over the passenger kilometres covered by the aircraft in a year.

As regards financing cost, which will be a proxy for inflation, the tool makes global assumptions of rate of interest. The period of levy of interest takes into account the life of the asset. In our case, as the cost of pathways has to be derived for the present, the net present value is derived by bringing the cost forward by levy of financing cost. The Calculator also provides 3 options of rates of interest (Low, default and high) for the user to adopt, depending upon his choice to, let us say, apply lower financing rates on investments of public good (public transport/RE) and higher ones on inefficient technologies.  Having taken into consideration capital costs and financing costs, it also includes operating expenditures and fuel costs.  Since fuel costs are already being taken separately, the operating expenditure costs are in a way expected to be insignificant.  It may be pointed that this tool accounts for primary fuels and electricity separately. This further adds value to the analysis, especially in the case of those demand sectors where solid/liquid fuels are used as a fuel/feed stock, as the case may be.  In the case of electricity, the pricing will be dependent on the price of fuel used to generate the electricity, which again will be dependent on the choice of electricity generation (coal based/gas based/ nuclear/RE etc), as selected by the user.  It has separately been indicated that in the event of the user of the IES, 2047, not choosing adequate levels of electricity supply to meet the demand sector, the tool will adopt imported coal based generation. This is important, as the demand for energy must be balanced by providing adequate levels of supply. As is the case with import of coal to meet deficit in electricity, similarly the tool provides for indication of availability for export, should the user choose higher levels of electricity supply than demand.


As has been indicated in the beginning, this tool aggregates the costs of supplying energy to the Indian economy in the period up to 2047, for the chosen combination of Levels of energy efficiency on demand side.

  • The choice of fuels on the supply side gets factored into the costs, by impacting the energy cost in delivering the service/product of demand. Therefore, it is the demand side which along with the choice of energy determines the cost of a pathway. It is evident that a combination of efficient technologies (Levels 2-4) on the demand side will imply higher cost to the economy than Level-1 choice of technologies. 
  • Similarly, on the supply side, if a user chooses to supply energy from cleaner source (Renewables), this would also entail higher costs (RE presently is a higher cost option than conventional energy). Therefore, the supply side gets included in the energy costs in the demand side through price of energy. Therefore, the Excel model in the tool must aggregate the total costs incurred in the delivery of services as per the combination of user choices. 
  • This combination of choices of demand and supply is a pathway. As the user changes his choices (hence, a different pathway), the IES, 2047 will offer the changed costing scenario.

Therefore, the tool is expected to also inform the user of the cost implications of an efficient/inefficient energy pathway.  It may be added that it does not offer total capital costs, but the revenue cost of delivery of services. The capital costs are, however, amortised over the life of the project, and the financing costs are also included. The revenue cost includes the incidence of the amortised cost on units of service delivered (on PLKM or per ton of cement etc.) In other words, when a user opts the choice of an efficient transport level entailing higher usage of public transport and EVs, etc., the per kilometre cost of both passenger and freight transport is expected to rise [but per passenger-km cost of public transport would reduce].  The total cost of passenger travel/freight factors in the financing cost, the capital cost (amortization) as well as operating cost and fuel cost. The cost of rendering transport service is obtained as above, and when multiplied with passenger/freight km, gives us the cost of the transport sector. Similarly, in the case of industry, the tool determines per unit cost of producing the industrial product (cement, iron and steel, etc.) as per the chosen technology. This per unit cost is multiplied with the total unit of the industrial product (tons of cement, iron, steel, etc.) to obtain the total cost of industrial output.

Therefore, the costs are essentially incurred on the demand side, and are impacted by the fuel which may have been used in delivering the service/products.  It is evident that a combination of efficient levels of demand (higher levels) would require higher capital expenditure, but use lesser energy. As we move up the demand Levels (2-4), the cost of the pathway goes up in spite of lesser energy consumption (exceptions may exist).  It may also be noted, that higher energy security may mean greater proportion of renewable energy, which would translate into higher prices due to their being more expensive than conventional energy presently. Therefore, there is a trade-off between higher capital cost impacting per unit cost of delivery, and lower energy consumption. However, as energy/technology costs come down, the more efficient pathways become cheap. The IES, 2047 offers a net submission of these two implications – technology and fuel savings.  Be that as it may, more efficient levels of energy pathways do impose higher costs on the economy, though these are likely to be recovered over time through reduced supply costs and improved energy security.

Sensitivity Analysis

We are all aware that, it is nigh impossible to determine the likely costs of technologies and fuels in the future, all the more, if this tool is undertaking projections 3 decades ahead.  The Planning Commission is not attempting to offer its assessment of the likely costs/prices in the future, nor has it undertaken any such exercise for this tool.  However, it is attempting to offer some information to the user to compare the cost of locking into investments, which may have long asset life.  It is evident that most energy consuming/producing assets, be it buildings, industries, transport infrastructure on the demand side, and coal mines, oil and gas assets, power plants, etc., on the supply side have long gestation periods.   Therefore, the present costs have great significance in determining the return to the investors, and implications to the economy at least in the medium term.  The present costs factored into the IES, 2047 are indeed useful for driving investment decisions in the medium term of 10-15 years by facilitating comparative analysis of indicative costs and benefits of the possible supply and demand pathways.  As regards the longer term, the tool can revise prices, as the IES, 2047 allows changes in cost numbers.  With this broad assumption, the tool, nevertheless, has adopted a feature to capture the likely movements/directions in costing/pricing.

The building up of the tool with the help of knowledge partners included getting their views on broad estimates, of the likely prices of different technologies/fuels in the long term. They have in turn sourced this information from multiple agencies, including the industry. Along with the present day prices, the tool provides their assumptions of change in the cost of technologies, as well as a point estimate between the high cost and the likely lower cost in the time horizon, i.e., 2047.   The IES, 2047, therefore, assumes that the present day prices (if they were not to reduce) would be a high estimate for a particular technology throughout the period 2013 until 2047.  On the other hand, the assumed lower price in 2047 could be expected to be reached by reducing in a straight line (uniformly for that particular technology between now and 2047).  Then, the likely point estimate, which will be closer to 70% reduction in the present prices, is also expected to be achieved by a fall in a straight line through this period. The concept of point estimate has been included as the default cost. Therefore, the user of the tool is offered three prices – a higher one, a low one, as well as the likely (default) price, with all three prices having a linear relationship between now and the end period.

Further, the lower costs, as suggested by the knowledge partners, do not have a uniform percentage drop in costs (from high costs) across different technologies. Newer technologies which are high priced today, namely, EV, CSP, advanced bio-fuels etc. are likely to see a steeper drop in the future, as compared to mature technologies such as internal combustion engines (ICE), oil and gas, etc.  Therefore, the IES, 2047 does provide a bias in favour of greener technologies by providing a sharper reduction in their prices over passage of time.

Having provided these three cost estimates, the tool offers the user, the choice of assuming any of these three costs in the case of each technology for his pathway.  If the user were not to take a deep dive, and make a choice for the costing levels (high/point estimate/low), the tool would adopt the point estimate (default costs).  The objective behind offering three cost estimates is to make a case for greener technologies/higher energy security drivers, and acknowledge that costs of different technologies would fall at varying rates.  Should there be a decision by the policy planners to promote an efficient technology in a particular sector in preference over another (e.g., in industries vis-à-vis the transport sector), the user may want to know whether this would be a more financially prudent decision (there may be a financial support for this change-over). He could do a sensitivity analysis by allowing himself to err on the lower cost side in the technology being overlooked, vis-à-vis the adopted one. In the above illustration, he would, thus, adopt lower cost estimate for the transport sector and high cost estimate for the industrial sector, and compare this cost differential, too.  In other words, the user is assuming if the costs were to fall in the transport sector, and not fall in the industries, what would be the likely financial implication by choice of this pathway.  This offers a sensitivity analysis to the cost exercise by offering choices of various levels of cost in different technologies.  As we all know that in emerging economies like ours, there may be partial State funding by different measures – subsidies, tax benefits, etc., for enhancing energy efficiency. This exercise would be useful in offering information on cost implications, in this area of decision making.

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