Costs

Costs in the IESS 2047

Objectives: why include costs

The first version of the IESS 2047 didn’t include cost information. As the Indian economy is significantly cost sensitive, common reactions to analysis of future energy pathways are “How much will the energy security cost?” “What will sustainable development cost?” and “How much will my pathway cost?” In the Version 2 of IESS we have undertaken an exercise to add information relating to cost implications to the tool to answer some of these questions. However, it may be added that this is an ‘energy calculator’ and not a ‘cost calculator’. Hence, it does not provide the total cost of energy related investment or costs, but the ones related to additional cost or savings that are obtained by changing the efficiency of the energy pathway including fuel switching (choice of levels on both Demand and Supply sides). This cost analysis extends the feasibility debate, allowing users to consider the economic implications of their energy choices.

"The cost analysis of IESS 2047 reflects all of the energy related monetary implications of migrating from one pathway to another"

[Note: - The model calculates the differential cost of moving from a baseline pathway (which is all Level 2) to any other pathway. Hence, the baseline costs are normalised to zero and a different choice results in increment or reduction by the number generated. The four effort levels of choice (Level 1-4) that are available to the user are based on what is technically possible, without any consideration of the financial consequences]

Emissions

Methodology

Predicting future costs for technologies and infrastructure is near impossible. And even if costs are estimated through complex simulations, it is being realised that almost all of these costs i.e Fuel, Capital, Operational and Financing are highly un-predictable in the long run (forecasted vs actual) by virtue of technological breakthroughs, research and innovation. The IESS is a tool that offers users an aggregate picture of likely energy demand, domestic supply and implications of the above two factors on India’s energy security. As noted earlier, an estimate of cost of different choices adds value to the analysis of future pathways. Therefore, while acknowledging that it is not possible to predict future costs, and neither does this tool capture all the costs, particularly infrastructure costs, an exercise has been undertaken to bring some realism by offering a range of costs in this analysis. The IESS offers an opportunity to the user to select from three cost choices (scenarios) High, Low or Point estimate for each technology on the Demand side and also for the fuels on the Supply side. The Excel model in IESS sums up all the costs as per the cost choice (of the three scenarios) for the chosen pathway (combination of Demand and Supply). Thereby, the user can see the implication of his/her choice (pathway) on the overall cost of the chosen pathway, and also see the cost of specific categories/sectors and the ratio of the cost to the overall economy GDP, till 2047.

It may be noted that in order to simplify the analysis, the tool uses only ‘real prices’ and not nominal ones. Hence, the impact of inflation is not factored-in and only price movements are captured (only to avoid estimating inflation). To capture the range of future costs, three (user defined) estimates have been made for each intervention based on exhaustive literature review and available domestic estimates, the components of these ranges are -

High Cost Scenario – This is said to be the maximum possible cost that anyone would possibly be paying from now till 2047 for supply technologies, efficiency improvements, infrastructure, fuel costs and financing etc. It is logical to presume that new technologies will only become cheaper as scale of deployment increases. Therefore, the present cost is taken as the ceiling. However, this may not be true in some cases (e.g: Nuclear) which has been factored in based on expert consultations. The reasoning behind falling or rising high costs are as discussed below -

  • Even in case of some conventional (well established) technologies where most of the technical innovation and research breakthroughs have already happened, and with low hanging fruits having been availed, the cost would increase. Hence the estimated cost upto 2047 will be substantially higher from today’s cost. Eg – in case of Coal and Gas based TPP.
  • But, as regards new technologies, the high cost could be a straight line suggesting that with further research, innovation and technical breakthroughs, costs would only come down. Therefore, even the highest cost in 2047 will be the same as what we a paying today. Eg – CCS, LED, etc.
Low Cost Scenario – This is said to be the minimum possible cost that we believe we would possibly be paying from now till 2047for any particular technology, infrastructure, fuel type or financing. This is the expected lowest price to which the costs may fall/or remain for the relevant technology/fuel etc. This varies significantly as –
  • In case of established technologies the low cost range will either remain the same or reduce marginally. This will be true for those technologies where costs are rising from the present for the High cost scenario (as mentioned above).
  • In case of new technologies the low cost estimates suggests that the price will reduce substantially till 2047 due to research and innovation. Eg –Solar PV, On shore and Off shore wind. Here, expert consultations have been undertaken to arrive at the level to which the prices may fall.
Point cost Scenario - is the simple average of both the high and low cost estimates of each year. This is the default cost assumed in the tool only with an aim to keep the baseline outcomes devoid of any bias from our side. However, the user can play around with choosing any of the three cost estimates as per his/her choice. Adopting different estimates for technologies while building an energy pathway is a value-add in the IESS V2.0, as it allows the user to estimate the range of costs that the economy risks when substituting one technology for another.

Decoding Costs Estimates

To capture the high and low range estimate of all future costs for present and upcoming technologies of 45 sub sectors with more than 100 technologies is a big challenge. Hence, the tool merely captures the annualised costs related to the technology related choices, estimated for one unit consumption of the level of service. The tool offers information of cost of delivering a PTKM, BTKM, units of irrigation by pumps, producing a unit of an industrial product say steel, cement etc and so on. It goes on to estimate the cost of delivering the above services by different technologies in each sector. Hence, there will be a cost incidence by changing the technology on the demand side, and saving in energy on the supply side (as the fuel efficiency of technologies is different). For example, on the Transport side, for the same quantum of transport (measured in Passenger Line Km basis), if the user chooses to enhance the share of let us say, public transport instead of private transport mode, or induct EV instead of IC engine powered transport, the tool captures the net additional cost that will accrue in the rolling stock (vehicle cost, fuel cost, financing cost and operating cost). Hence, the following energy related costs are captured in the model –

  • the capital costs,
  • operational costs,
  • fuel costs and
  • financing costs
Note: You can find all the consolidated cost data in the cost absolute sheet of the model.

Capital expenditure:

This relates to the capital cost of the asset that will directly be involved in the delivery of service – car/ bus, railway rolling stock, efficient irrigation pump, efficient tractor etc. But, the tool only captures the cost of the efficient technology and not the infrastructure. For e.g. the difference in the cost between the conventional and efficient technology (process) in Industry sector is captured, and not the cost of steel mill or cement mill etc. When the process changes, then there will be a cost implication – either a hike due to efficient technology (when we move from level 2 to Level 3 or 4) or reduction in cost if we move to an inferior technology (level 1). The tool merely captures costs associated with the change in technology. Capex values have been estimated by the knowledge partners based on inputs form government agencies and extensive literature reviews. Sector specific capital costs are at the bottom of each sector sheets which is then linked to the final cost absolute sheet. In the capex we tried to capture the full costs of capital components, from the air conditioner installed in individual homes, through to large infrastructure projects.

Operating and maintenance costs:

In order to simplify estimation of this cost, a fixed percentage of capex is captured at the bottom of individual sector sheets and finally linked to the final cost absolute sheet as the opex. We captured full cost of running and maintaining all of the required technology and infrastructure. Naturally this will vary across the three cost scenarios due to the base costs being different.

Fuel costs:

Here again, the tool offers a range (high, low, point) of costs of all energy fuels i.e coal, oil, gas, uranium, bio mass etc. The forecasted fuel costs are mostly derived from GoI estimates, IEA, EIA and other sources. For domestic supplies, wherever the government policy is of pricing different from internationally traded prices, the same has been captured. However, for imported fuels, the estimates of international agencies have been adopted. In the long run, however, it is assumed that domestic prices will also align with international prices. This exercise, is however, without prejudice to the decisions that Government may take, and is no reflection of the thinking in the later of pricing policy.

Financing costs:

Many of the assets in the IESS 2047 involve significant upfront investment – in particular, electricity generation technologies, gas infrastructure etc. The cost of financing these lumpy investments can be a significant component of their costs. Here again, there is a possibility that private and public investments may receive different interest rates (steel plants versus metro rail projects). However, the default costs capture the point estimate (the middle range) rates, leaving the user of the tool to adopt the estimate as per his/her expectations. Interest rates in India are much higher than international ones, but in the long run, there may be a convergence. Moreover, the rates are also real rates and may be considered as devoid of the nominal rate (inflation) component itself. Hence, the rates offered may be considered on the above rationale. However, it may be noted that as the tool uses real prices, when calculating the present cost of the pathway, there is no discount rate applied as no interest rate is applicable. However, if the same costs were to be added up into a future date, let us say 2047, then the interest rate would apply from the year of expend until 2047.

Choice of interest rate - the interest rate a project faces is likely to depend on the risk premium associated with the technology and with the source of funding, for example through private markets, government bonds, or general taxation. In the High case we have taken the interest rate as 6% and in low as 2% but the user has a choice to change that in the model.

Choice of loan period - The period over which the cost of financing a project is repaid can vary in response to a number of factors. When considering loan periods, it is worth distinguishing between:
  • Asset life – the period of time an asset could be used for, determined by technical factors. For example, a CCGT gas plant could be used for a maximum of about 30-35 years.
  • Economic life - the period of time over which an asset is likely to be economically viable to use. This may be less than the asset’s technical life due to rising maintenance costs or obsolescence. For example, the CCGT plant mentioned above will typically be retired after around 25 years.
  • Typical investment horizon – lenders may wish to recoup their costs before the end of an asset’s economic life. For example, investors may not be prepared to wait until the end of a nuclear power plant’s 40 year economic life to see a full return on their outlay.
The most technically accurate approach would be to use the economic life of assets to determine when to build new capacity in the relevant technologies, and then spread the relevant finance costs across the typical investment horizon for that technology which is what we adopted in our model.

Important caveats and limitations of the analysis

There are a number of important caveats to bear in mind when interpreting results from the IESS 2047 -

No impact on electricity or fuel prices - Results from the tool are presented as Rs/person/year, but this should not be interpreted as the effect on end users’ energy bill. The impact on energy bills of, say, building more wind turbines will depend on how policy is designed and implemented (e.g. via tax, subsidy, regulation, etc). Taxes and subsidies are out of the purview of this work, as this tool captures economic costs. The Government uses perhaps, more sophisticated models to examine the effect of specific policy interventions on electricity and energy prices.

Incremental costs principle - The model calculates the differential cost of moving from a baseline pathway (which is level 2) to any other pathway. The model presents cost results using the default costs (point estimates) unless the user adjusts the cost assumptions. In this instance, the incremental cost of one pathway over another is calculated very simply as the difference between the two pathways. For example, if “baseline” pathway costs Rs 1,000 and the “abatement pathway” costs Rs 1,200, then the incremental cost of the abatement pathway over and above the baseline is Rs 200. Hence, this is NOT a cost Calculator and merely helps compare the cost of migration from one energy pathway to another. The information provided in the IESS v2.0 could help the policy makers/users to estimate the cost of achieving higher energy security or reducing carbon emissions from the energy sector, and nothing more. It does not, anyway, capture the large infrastructure involved with the usage of major energy shifts (to more metros rather than roads). Neither does it calculate the cost of constructing a facility but only the energy use related differential costs (in a steel mill it captures the cost of changing the process to a different one, and not the cost of the entire steel mill).

Estimates exclude important costs associated with the move to a low carbon economy. Specifically:

  • welfare costs such as inconvenience of living in buildings with less comfortable temperatures and potential inconvenience of travelling less
  • wider macroeconomic costs
  • R&D costs
  • the cost of most existing infrastructure (e.g. the capital and finance costs associated with existing power stations)
  • the policy costs associated with regulating and enforcing future policy
  • opportunity cost (e.g. the opportunity cost of investing in low carbon technologies rather than, say, better schools or hospitals, is not captured)
  • public safety risks (perceived or actual) associated with incumbent technologies e.g. oil extraction, nuclear, CCS
  • long term, not short term analysis. The Calculator is best suited to long term analysis of the energy system in 2047 rather than policy implications over 2020s.
  • User driven model, not market based. The IESS costs the combination of technologies chosen by the user. Consequently it does not take into account price interactions between supply and demand. For example, if the cost of, say, electricity generation increases then the Calculator does not capture any elasticity of demand response from the electricity user. Cost optimising models better handle such price responses.
  • Costs are exogenous. Technology costs do not vary depending on the level of technology roll out. However if the user has beliefs about how they would expect the unit costs of particular technologies to change in their pathway, they can sensitivity test the effect of varying these assumptions.
In Summary: A scenario building exercise is incomplete without offering the cost of achieving the stated objective. If India has to make ‘shifts’ in the way transport service is provided, it is easy to say that public transport is the way to go, but we must also know the cost associated with it. Similarly, renewable energy would reduce our dependence on coal and reduce emissions, but would come at a higher capital cost. The Calculator does not offer complete capital cost as the infrastructure cost associated with a technology is not fully captured, but does give the cost of electricity over the long run. Hence, IESS V2.0 is an improved version of the previous one in many ways, but the most significant difference is the cost related information. Now, the user can see more well informed choices as to the way forward for reduction in import dependence or emission reduction. However, the interest of different stakeholders would be different – somebody may be interested in capital costs as it is not easy to obtain large doses of capital, while others may be interested in cost to the consumer as adoption of technology is not easy if the shift is for a more expensive one. The cost information herein meets the expectation more of the latter than the former.