Day2 session 3: Morocco

Euro-Mediterranean
Energy Market Integration Project

Germany

France

Lebanon End Use Energy Efficiency:
National Plans for Regional Energy Challenges
Belgium

Presentation of Budget Allocation Charts - Morocco
Germany Tunis, 26th – 27th, July, 2010

M.Mohammed HMAMOUCHI
BAC Expert – Morocco

“The contents of this publication are the sole responsibility of the author
and can in no way be taken to reflect the views of the European Union”.
This project is funded
by the European Union 1

 Country Energy Overview
 Country Potential EE and RE Technologies
 Budget Allocation Chart (BAC) Objective
 Methodology for the BAC
 Methodology for the BAC RE/EE
 BAC Output
 Next Steps

by the European Union

 Contribution of energy to the national economy

 Energy bill (facture énergétique)

 Royalties received from the transit pipeline Maghreb Europe

 Evolution of energy balance

 Evolution of electricity consumption

 Evolution of the electricity demand (Gwh)

 Electricity demand in 2030
3

Contribution of energy to the national economy

1euro = 11 DH (Dirham) 2002 2006 2007 2008 2009

Tax Revenue (Billion DH) 12 12,5 15 16 -

Energy Bill (Billion DH) 19,1 44,4 51,8 70,6 54,2

Energy Consumption (Mtoe) 10,5 12,9 13,7 14,8 15,1

Investments (Billion DH) 5 8 10 17 -

Consumption (Toe/capita) 0,36 0,42 0,45 0,47 0,48


Energy bill (facture énergétique)

(Billions of dirhams) 2002 2006 2007 2008 2009

Crude Oil & petroleum 16,2 39,7 45,9 61,5 45,5
products
Coal 2,5 3,6 4,3 6,5 4,4

Electricity 0,4 1,1 1,6 2,6 4,3

Total 19,1 44,4 51,8 70,6 54,2


Royalties received from the transit pipeline Maghreb
Europe

(in Million Nm3) 2002 2006 2007 2008 2009

Total royalties 613 785 757 813 658


Evolution of energy balance
( in ktoe) 2002 2006 2007 2008 2009
Production 330 370 365 374 820
Oil and Natural Gas 61 66 60 59 50
Hydro 219 256 235 238 668
Wind 50 48 70 77 102
Consumption 10461 12901 13734 14794 15118
Petroleum products 6445 7713 8069 9115 9181
Coal 3337 3878 3910 3723 3379
Hydro 219 256 235 238 668
Naturel Gas 48 479 540 533 586
Imported electricity 362 527 910 1108 1202
Wind 50 48 70 77 102
Share of Petroleum Products (%) 61,6 59,8 58,8 61,6 60,7
Energy Dependence (%) 96,8 97,1 97,3 97,5 94,6


Evolution of electricity consumption (ONE)

Evolution indicielle de la consommation
d'électricité, du PIB et de la population
(base 100 : 1988)
350

300

250

200

150

100
1988 1993 1998 2003 2008
Population PIB Consommation d'électricité


Evolution of the electricity demand (Gwh)


Electricity demand in 2030


 Renewable Energies and Energy Efficiency are major
components of the current Moroccan energy strategy.
 In 2020, the part of Renewable Energies should represent
nearly 20% of the total energy consumption and 42% of
electricity consumption.
 The main objective of the Energy Efficiency measures is to
save in 2020 over 15% ( 19% for housing).
 For the case study, the selection of the EE and RE
technologies was based on the avalable data and information
on the new national energy strategy and meetings established
with some concerned organizations like Ministry of Enegy and
Mines, Office National de l'Electricité et l'Agence de
développement des énergies renouvelables et de l'efficacité
énergétique (ex. CDER).
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Renewable Energies

 Solar;
 Wind;
 Biomass;
 Geothermal;
 Hydro;
…


Place of RE in the national mix power (ONE)

National Energy Strategy:
RE 42% in 2020

Energy Efficiency
Four pillars:
 Legislative and regulatory frameworks;

 The institutional and organizational arrangments for promotion
and facilitation;

 Sectoral action programs or transverse, national and local
(industries, tertiary, services, households, housing);

 Funding mechanisms.

National Energy Strategy:

Save in 2020 over 15% ( 19% for housing )

 BAC shows the additional energy savings and
net costs of several technologies/options (from
the societal perspective);
 Policy-makers can see on the BACs:
 technology / option with the highest energy savings
 most cost effective technology / option
 With BACs, policy makers can identify easily the
best option according to the priority:
 Cost savings
 Energy savings

15

 BACs also shows :
 Maximal benefit (minimal net costs) by implementing all
measures with negative net costs/ improvement of the
competitiveness;
 Maximal energy saving without extra-costs/improvement of the
security of energy supplies;
 BACs deliver information in a simple way to policy
makers
 on one single chart: energy potential and cost-effectiveness
 of several technologies/options
 ranking of options (according to increasing net-costs)
 With BACs: policy makers see clearly where to act.


Scenarios and scenarios comparison
Additional Energy Savings
Net Costs of Energy Saved
Scenarios and scenarios comparison
BAC is a method to compare 2 scenarios.
 Main difference between scenarios and forecasts:
 forecasts and prognoses aim to describe how the future will be;
 scenarios aim to describe how the future might be under certain
assumptions or to show a possible path in order to achieve a
goal in the future.
 Different options for choice of baseline: Depending on the
objective of the analysis.

17

The scenarios considered are:
 Business As Usual Scenario (BAU or Reference Scenario)
=>market shares of Energy Efficiency Technologies increase according
to the actual trend, same for the RE capacities
 Energy Efficiency Scenario (EE Scenario):
=> EE Technologies market shares are high (if EE = Best Available
Technology, BAT market share is almost 100%), fast build up of RE
capacities.
BAC:
 X-Axis: Additional Energy Saving Potentials (for EE) and/or
Additional Energy Generation Potentials (for RE)
=>Additional Energy Savings Potentials (of the conventional electricity mix)
 Y-Axis: Net Costs of Energy Saved (for EE) and/or Net Costs of
Energy Generation (for RE)
=>Net Costs of Energy Saved (of the conventional electricity mix)


Additional Energy Savings
 Determination of Specific energy consumption in BAU and EE
scenarios
 Calculation of the whole stock of EE technology: estimation of the
Additional Number of BAT technology Units (ANBU) in EE-scenario
(compared to BAU scenario)
ANBU2020 =NBU2020,EE − NBU2020,BAU
NBU2020 = NBU2015- NRBU2020-2015+ (SG2020-2015 + NRU2020-2015) x
MSB2015-2020
NBU: Number of BAT technology Units
NRBU: Number of Replaced BAT technology Units (lifetime exceeded)
SG: Stock Growth (stock in 2020 – stock in 2015)
NRU: Number of Replaced technology Units (all: BAT and not BAT)
MSB: Market Share of BAT technology.

 Calculation of Additional Energy Savings=ASES (Additional
Specific Energy Savings) x ANBU(Additional Number of BAT technology Units)

Costs of Energy Saved (CES)
Only the additional costs of the BAT technology have to be considered
Calculation of the levelised additional costs per year (ΔA): ΔA = A(ΔI0) + CF;
with:
A(ΔI0):annuity of additional investment of BAT vs. not BAT technology
CF: average annual cash flows (saved energy and O&M costs)

CES = ΔA/ASES
Net Costs of Energy Saved (NCES)
Net costs
=Additional costs of technical or organisational energy efficiency
measures (additional compared to the baseline case)
- Long-run avoided system costs for the supply of energy (including or
excluding external costs)
- Avoided maintenance costs of the technology (or plus additional
maintenance costs)
NCES = CES – LASC
With LASC (Long-run Avoided System Costs) include: Full generation costs at
border crossing, For electricity: long-run avoided system costs for transmission and distribution,
grid-losses, and reserve capacities.

Case Study
Data collection: documentation analyses from the government
institutions (Ministry of Energy & Mines, Electricity authority, agency
of development of renewable energies and energy efficiency),
meeting and discussion with some Moroccan experts
Primary, generation, consumer energy prices considered:
Primary energy prices: default values
Generation, consumer: information collected from the Ministry of
Energy & Electricity authority
Avoided electricity costs for end users: determined on the basis of
data we nomally use in the studies of energy planning completed by
information from Electricity authority
Avoided energy supply costs for national economy: ditto
21

 Renewable technologies country
potential.

 Resultsof the excel sheets RE Potential
for each RE technologies.

 Conclusions.

22

Methodology for the BAC/RE: Potential


Methodology for the BAC/RE: Results of the excel
sheets RE Potential for each RE technologies


Methodology for the BAC/RE: Conclusions
 The potential of Renewable Energies will
grow from 2024 MW in 2010 to 7542 MW
in 2020.

 This evolution means that the grow rate of
installed capacity for the RE will be about
14% per year.

 During the same period, the production of
energy from the RE will be multiplied by
four, it will go from 4 Twh/a to nearly 18

 Efficient technologies country potential.

 Resultsof the excel sheets EE Potential
for each EE technologies.

 Conclusions.

26

Most efficient fridges EE1.11/ Results


A++ clothes washers EE1.12 / Results


CFL instead of Incand. light EE1.13 / Results


More efficient compressors EE2.9 / Results


Daylight sensor EE2.10 / Results


Good housekeeping EE3.9 / Results


Heating EE3.1 / Results


High pressure sodium EE3.10 / Results


Methodology for the BAC/EE: Conclusions

Tech. Technically feasible total electricity saving in 2020: 2,56 Twh
equivalent to 6% of projected domestic demand in 2020

EE1.11

EE1.12

EE1.13

EE2.9

EE2.10

EE3.9

EE3.1

EE3.10

 Output intermediate result

 Output (ThinkCells)

 Budget Allocation Charts

 Budget Allocation Charts (Accumulated net costs)

36

Output intermediate result


Output (ThinkCells)


Budget Allocation Charts


Budget Allocation Charts (Accumulated net costs)


 Information and dissemination of the BAC-model and its
results.

 Workshops to the attention of departments, agencies or
communities concerned with targeting receptive and
players can multiply and reproduce the actions of
dissemination.

 Assistance to (cooperation with) specific sectors or
communities for the implementation of concrete actions.

41

Thank you

42

Day2 session 3: Morocco

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