Service quality regulation in electricity distribution
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Service Quality Regulation in Electricity Distribution. Necmiddin BAĞDADİOĞLU Orçun SENYÜCEL. Objectives. Incorporate service quality measure into electricity regulation. New in literature : Growitsch et al (2008), Coelli et al (2008-Draft)

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Service Quality Regulation in Electricity Distribution

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Service quality regulation in electricity distribution

Service Quality Regulation in Electricity Distribution

Necmiddin BAĞDADİOĞLU

Orçun SENYÜCEL


Objectives

Objectives

  • Incorporate service quality measure into electricity regulation. New in literature : Growitsch et al (2008), Coelli et al (2008-Draft)

    Determine technical efficiency of Turkish electricity distribution utilities

  • Focus on exogeneous determinants of inefficiency

  • Analyze effects of electricity losses and illegal usage on TE.


Turkish electricity reform

Turkish Electricity Reform

  • Electricity Sector Reform and Privatization Strategy Paper (2004): TEDAS  2012

  • Transitory period: 20 utilites through mergers of 79 distribution utilities.

  • ESRPSP: mergers determined by operational problems, technical & financial features.

  • Turkey accession country. EU Energy Acquis

  • EMRA has not announced regulatory framework


Briefly sfa v dea

Briefly SFA v DEA

Average Cost (all noise)Syrjanen, M., P. Bogetoft, P. Agrell (2006)


Briefly sfa v dea1

Briefly SFA v DEA

Deterministic frontier (all ineff  u)Syrjanen, M., P. Bogetoft, P. Agrell (2006)


Briefly sfa v dea2

Briefly SFA v DEA

Stochastic frontier (both noise v and ineff u) Syrjanen, M., P. Bogetoft, P. Agrell (2006)


Briefly sfa

Briefly SFA

  • Two component error terms, first captures statistical noise

  • Second captures effects of TE.

  • Half normal, exponential, truncated dist.


Distance functions

Distance Functions

  • DF: Distance of the prod to PPB

  • Two different types: input & output DF

  • Input DF: How much input vector can be contracted (output constant)

  • Output: Vice versa.


Distance functions1

y

y0

xo

x/λ

x

L(y)

Distance Functions

Kumbhakar & Lovell (2003)


Distance functions2

Distance Functions

  • Deviations from 1 is technical inefficiency

  • h(.) represents deviation exp (-u)

  • exp (-u) one of the component error terms.


Distance functions3

Distance Functions

  • Adding random error term, imposing homogeneity rest.

  • We preffered translog input DF.


Methodology

Methodology

  • Following Coelli, (M outputs K inputs)


Methodology1

Methodology

  • Following Coelli and Battese,

  • Two environmental variables


Models

Models

  • Model I: Input: TOTEX+L&IEU (TOTEXL)

  • Model II: Input: + Interruption Time (ITC)

  • Output: Energy supplied (ENG) and number of customers (CUST)

  • Environmental factors:

  • Village Cust Density (VCD)

  • Geographic Conditions (GEO)


Model i

Model I


Model ii

Model II


Descriptive statistics

Descriptive Statistics


Model i1

Model I

Note: ***, ** and * denotes significance at the 1, 5 and 10 % levels.


Model i2

Model I

RTS=0.93=


Model ii1

Model II

Note: ***, ** and * denotes significance at the 1, 5 and 10 % levels.


Model ii2

Model II

RTS=1.06


Average efficiency scores

Average efficiency scores

QoS has significant effect: TE decreased by 16.5%

LLR test also states QoS important


Average efficiency scores1

Average efficiency scores


Conclusion

Conclusion

  • QoS impact on TE. GEO & VCD are crucial environmental variables.

  • Excl. losses and illegal electricity usage overestimates TE.

  • Privatization: Eight utilitiesare established far from the optimal size and have low average efficiency scores (0.43). TPA may merge other six utilities.


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