09/04/2013

Authors: Rodrigo Calili

Reinaldo SouzaAlain Galli

Margaret ArmstrongAndré Marcato

4th Latin-American Meeting of Energy Economics (ELAEE)

Uruguay, Montevideo

Estimating the cost savings in Brazil by implementing energy efficient policies

Motivation Questions Methodology Results Conclusion

An increasing of the electricity cost, coupled with the global economic growth;

The rising scarcity of energy resources; The increasing emissions of CO2 in the atmosphere; The fact that many market players see investment in

energy efficiency projects as high risk.

Will improved energy efficiency enable us to avoid costly investments in new power-plants?

How can the cost savings be evaluated in an economic environment that is subject to uncertainty?

The expected demand for electricity for Brazil is known (scenario 0).

The stochastic demand for electricity was computed by replacing the deterministic EE forecast in the demand forecast (called the standard scenario) by 100 stochastic forecasts obtained using the 100 simulations of the energy efficiency.

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GWh Standard scenario Scenario 0

The third step was to determine the dispatch model for each of the 100 demand forecasts, and hence the corresponding marginal operating costs.

This was done using a program called MDDH (Model of Hydrothermal Dispatch) that was developed by PUC-Rio and UFJF as part of a strategic R&D project.

For each period of time, we computed the difference between the operating cost in scenario 0, OC(0), and operating cost in each scenario "s", OC(s), with "s" from 1 to 100, called OCdif(s).

)()()0( sOCdifsOCOC

Once we have the operating cost, it is easy to calculate the investment avoided with energy efficiency policies, with the next expression:

where I is the total avoided investment with energy efficiency policies and is a discount rate.

The next step was to compute the breakeven investment (i.e. when NPV = 0).

Two scenarios, a pessimistic one with a high discount rate of 12%, and an optimistic one with a discount rate of 7.5%, were considered.

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ItsubsEEPtsubsOCdif

NPV

We ran the MDDH software 101 times to estimate the operating cost in each demand scenario, including scenario 0.

0

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R$/MWh

Scenario 0 Scenario 1 Scenario 2 Scenario 3 Scenario 4

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R$/MWh

Scenario 0 Scenario 1 Scenario 2 Scenario 3 Scenario 4

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R$/MWh

Scenario 0 Scenario 1 Scenario 2 Scenario 3 Scenario 4

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Scenario 0 Scenario 1 Scenario 2 Scenario 3 Scenario 4

Operating cost for Southeast Operating cost for South

Operating cost for Northeast Operating cost for North

After that we calculated the difference in operating cost between scenario 0 and each scenario (OCdif).

Southeast South

Northeast North

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Scenarios

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Finally, we calculate the avoided investment due to energy efficiency using equation:

Conservative scenario

(MMR$) Optimist scenario

(MMR$)

Mean 236.84 268.26

Minimum 165.38 185.86

Maximum 339.92 384.30

To illustrate how large the savings can be, we compare the amounts that could be economized with the cost of building a new hydro-electric power plant, using the new Belo Monte project to illustrate our point..

Investment in one year (MMR$)

Percentage of demand

Investment to meet 1% of demand

(MMR$)

Conservative scenario 47.37 0.54% 87.96

Optimist scenario 53.65 0.54% 99.63

Belo Monte power plant 866.67 6.42% 134.97

We have demonstrated that even for a modest improvement in energy efficiency (<1% per year), the savings over the next 5 years range from R$ 237 million in the conservative scenario to R$ 268 million in the optimistic scenario.

By comparison the new Belo Monte hydro-electric plant will cost R$ 26 billion to be repaid over a 30 year period (i.e. R$ 867 million in 5 years). So in Brazil EE policies are preferable to building a new power plant, even a hydro-electric one.

We can also conclude that an increase of the energy efficiency measures/policies in Brazil would reduce the operating cost, and would lead to avoiding investment in new power plants.

As future work we suggest studying the option to invest in energy efficiency policies, which could give a curve of NPV and also the threshold where it is preferable to invest in energy efficiency policies than to build a new power plant.

Thank you!Muchas gracias!Merci beaucoup!

Obrigado!

First, we fit an exponential regression to the PNEf’s energy efficiency goals;

We generated 100 simulations of energy efficiency over the next 5 years on a monthly time step using a geometric Brownian motion (GBM) because its mean is exponential.

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GWh PNEf energy PNEf estimative

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Estimating the cost savings in Brazil by implementing energy efficient policies

KeywordsGeometric Brownian motion (GBM); Stochastic dual dynamic programming (SDDP); Energy efficiency policies; Brazil; Hydrothermal power system