NTLs and the Supply Challenge Proving the Yelland Thesis

1
NTLs and the Supply ChallengeProving the Yelland
Thesis

• William C. Erasmus CEM (FSAIEE)

2
Introduction

• In South Africa we have adequate energy (kWhs)
  but we do not have the power capacity (MW or GW)
  to meet the demand for energy
• This status unequivocally creates an opportunity
  to unlock power capacity by reducing energy
  demand through DR and reducing NTLs thereby
  deferring new investment into generation,
  transmission and distribution

3
What are Non-Technical Losses NTLs ?
Administrative
Commercial
Receivables

• Fraud may be
• Energy theft (illegal connections to the network)
• Meter fraud or by-passes
• Meter errors
• Fraud may be implemented by the customer or by
  professionals

4
NTLs
Commercial
Receivables
Administrative

• High cost of managing aging accounts
• Default Customers Delayed Payments and no
  payment
• Defaulter consumer () ? some will delay, some
  will not pay
• Volume and aging of receivable accounts has HIGH
  COT IMPACT ? consumer used energy but did not
  pay on time, which increase companys financial
  expenses
• Usually not accounted as NTL.

5
NTLs
Commercial
Administrative
Receivables

• Internal process flaws and database
  inconsistencies (Average 20 of all problems
  identified by CI Audits in SA)
• Human and system errors ()
• Incorrect tariff ()
• Internal fraud ()
• Usually not accounted.

6
NTLs and the Supply Challenge
Energy
Cost-free DSM
Energy consumption
68
32
Energy paid
NTL detection
Time
Figures from recent studies in Brazil
7
Advantages of NTL Reduction

• NTLs decrease ? double benefit
• Significant energy consumption reduction -
  unlocked significant additional power capacity
• Revenue increase
• Energy consumption reduction
• Diminishes total supply
• Reduces the demand-peak
• Therefore, reducing NTLs has a huge benefit in
  demand management without additional investments
• Cost-free DSM benefits

8
Brazilian Case Studies
Northeast Brasil
Area 1.789 Km2 Consumers 131 thousand NTLs
4
SAELPA Area 54.595 Km2 Consumers 837
thousand NTLs 9
Brazil
Area 17.419 Km2 Consumers 436 thousand NTLs
4
Southeast Brasil
Area 17.331 Km2 Consumers 378 thousand
NTLs 2
Date April / 04
9
Energisa (SAELPA)

• Energisa implemented solutions to reduce NTLs
  from Feb-03 to Nov-04 at their following
  distribution companies
• ENERGIPE Feb/04
• SAELPA/CELB May/04
• CFLCL/ CENF Nov/04
• RESULTS AFTER 1-Year
• SAELPA has 850 thousand customers in one of
  poorest states of Brazil
• Productivity increase 90.25
• Energy consumption reduction 40 GWh
• Additional net revenue in 1 year US 2,9 million

10
Cemar

• CEMAR implemented a solution in 2006 and results
  for 2007 are
• Cemar has 1,35 million customers
• Productivity increase 118.89
• Energy consumption reduction 227 GWh
• Additional net revenue in 1 year US 16,9
  million

11
Measurement of Productivity

• ProdGES ?in 1( ?jm 1 EbcAiCj EiAiCj )
  EcrGES
• __________________________________
  _______________
• ?in 1 ( ?jm 1CostAiCj )

12
(No Transcript)
13
Opportunity Cost/Benefit Differentiator

• Cost to implement a solution to identify sources
  of NTLs for, say, Jhb Metro (1.4 million
  consumers) 20 million USD and deliver result in
  1-year with a ROI in excess of 400
• New thermal plant of equivalent unlocked capacity
  would cost in the region of between 10 to 20
  billion USD and take nearly 9-years to complete
• The opportunity for the economy is a no-brainer

14
The Important ?

• Business/Economy needs to ask Government/Eskom
  why the economy is been held to ransom a
  situation which is critically effecting
  employment, job creation and the countries
  ability to remain globally competitive

15
Thank You
16
Optimization Problem

• There are several activities to reduce NTLs such
  as inspections, anti-theft cable-box-seal, AMR,
  SMART meters etc.
• Activities cant be applied to all customers
  because of economic restrictions hence,
  distribution companies only have budget for a
  portion of consumer base
• The consequential questions are
• What is the most-effective (ROI) activity for
  each customer ?
• Who are the top customers to apply each activity
  ?
• As a result we are confronted with an
  optimization problem