7th International Scientific Conference Energy and Climate Change

1. 7th International Scientific ConferenceEnergy and Climate Change Athens – Greece 9 October 2014

2. Reforming Energy Subsidies for a Better Implementation of Renewable Energies in Tunisia Asma DHAKOUANI Dr. Essia ZNOUDA Pr. Chiheb BOUDEN Université de Tunis El Manar, Ecole Nationale d’Ingénieurs de Tunis Laboratory Materials, Optimization and Energy for Sustainability

3. Content • Energy Situation in Tunisia • Overview • Demand Evolution • Supply Evolution • Potentials and Effects • Strategy • Energy Systems Modelling • Generalities • Classification • Characteristics • Identification of suitable ESM • Which models are suitable? • Open Source Models • Examples of Open Source Models

4. Energy Situation in Tunisia

5. Historical Overview  The government intervention has tried to adapt to the different situations through the implementation of institutional, legal and regulatory framework.

6. Actual Challenges

7. Evolution of Energy Demand Source: Ministry of Industry, Energy and Mines - Tunisia

8. Evolution of Primary Energy Consumption Petroleum Products Natural Gas Others

9. Evolution of Natural Gas Demand Electricity Production End Uses Source: Tunisian Company of Electricity and Gas

10. Evolution of Electricity Demand • Annual growth rate: 5% • 150 MW installed/year • Rapid development of the peak 11%

11. Evolution of Oil Production Annual Production in 2012: 67 000 Barrels/day Marginal Fields Decline in resources

12. Evolution of Natural Gas Supply Production in 2012: 2.8 millions toe Consumption in 2012: 5.4 millions toe 16% Fiscal rent 31% Imports

13. Electric Mix in 2012 • Wind : 350 GWh • Solar : 9 GWh • Hydraulic : 59 GWh • Part from production : 2.5 % • Saved conventional : 100 ktoe (80 MTND) • CO2 avoided : 230 000 TCO2

14. Costs of Renewable Energies

15. Potentials: Other Energy Sources

16. Potentials: Electricity Access  Length of lines (Low and Medium Voltage): Around 150 000 Km

17. Energy Deficit Source: The Ministry of Industry, Energy and Mines - Tunisia • In 2013, the deficit has achieved 2.4 Mtoe: • Evolution of primary energy consumption (doubled) • Decline in domestic production

18. Macro-economic effects: Energy Subsidies The ministry of Industry, Energy and Mines estimated energy subsidies in 2013: 5 200 millions TND ≈ 2261 millions €, including direct and indirect subsidies, where: • 43% for petroleum products • 41% for electricity • 16% for natural gas Evolution of direct Subsidies Source: Ministry of Finance

19. Macro-economic effects: Natural Gas International Prices

20. Other effects of Subsidizing Energy • Economic efficiency losses : • Reduction in the incentives designated for more efficient energy. • The subsidies targeting consumption decrease energy suppliers’ profits and their ability to invest in new infrastructure  Interest in investing into cheap and dirty technologies  Energy shortages • Augmentation of imports or a decrease in exports which creates a high dependency on other nations or the spreading of smuggling fuels • Environmental effects: • ES to end-users lower the prices  Increase the consumption  Augmentation of emissions and pollution. • ES to producers  Increase production  Raise pollution. • ES for fuel decrease deforestation and lower carbon emissions Switching to modern forms (fuel and electricity) highly favourable. • Social effects: • the social benefits don’t reach rural areas % Producers, rich and high consumers, and suppliers who are most likely to benefit • ES ended up in capital intensive projects causing a displacement of communities or affecting the health of poor neighbours unable to move away, alongside with the improved conditions of power and infrastructure, reflecting hence the contradictory effects of E.S.

21. Main axes of the energy strategy • The strategy of Tunisia on energy sector is based on the following pillars: • The development of resources and energy infrastructure. • Enhancing Energy Efficiency and the Rational Utilization of Energy. • Diversification of energy resources: • Development of Renewable Energies • Intensification of Research in fossil fuelled energies • Strengthening interconnectionsbetween Maghreb countries and in the Mediterranean. • The implementation and reorganization of institutional and budgetary reforms in the energy sector. • Strengthening the North African and international cooperation (training, research and development and technology transfer)

22. 30% RE and 70% FFE Source: The Ministry of Industry, Energy and Mines - Tunisia

23. Energy Systems Modelling

24. Generalities Definition: ‘‘Energy system models are formulated using theoretical and analytical methods from several disciplines including engineering, economics, operations research, and management science.’’ Hoffman and Wood (1976) Objective: The various models that have been appearing lastly aim in general to introduce a better energy supply system design with an improved understanding of the present and future interactions between demand-supply, environment, and economy. • The models that have been designed for industrialised countries cannot be transferred for usage and application in developing countries for the non-adequacy due to the several socio-economic changes •  Need of adapted models • Energy modelling has a long history: Since the early 1970s, a wide variety of models became available for analysing energy systems or sub-systems, such as the power system

25. Classification • The classification of ESMs differ based on the perspectives and objectives of the research. • Presented Methodology: Historical evolution • There are three periods which marked the development of ESMs: • Firstly: Following the oil crisis that occurred in the 1970’s, energy demand managementappeared • Secondly: During the 1980’s the shortage in energy supply has led to the development of supply and demand management models • Lastly: With the appearance of the climate change concerns in the 1990’s, the models were targeting as well environmental concerns alongside with the decrease in energy consumption.

26. Classification

27. Classification

28. Classification

29. Classification

30. Characteristics

31. Identification of suitable ESM

32. Which models are suitable? • Previous ESMs comparative studies: Bottom-up accounting models are the most appropriate for developing countries • Pros: Flexible+ require limited skills + able to capture imperfections + consideration of non-price policies. • More suitable than econometric models which don’t capture informal sector or traditional energy. • Cons: Inability to analyse price induced effects + Problems of subsidies and shortages are not adequately captured as the demand is not explicitly covered in these models. • End-use models suffer from information burden which is substantial, especially that these models cover many fields, e.g. consumption, income, location, end-use types…

33. Which models are suitable? • Econometric models: analyse the effects by identifying statistically relationships using economic theories  These models didn’t capture several of the characteristics of developing countries: • Energy access • Rural-urban divide • Difference in consumption behaviour and supply conditions within income classes • Traditional energy usage • Informal economies • Technological diversities and inequity and inefficient technologies • Misallocation of resources and choices • Non-monetary transactions (inefficient institutional arrangements) • Transition to modern energies • Data limitation (quality and quantity) ESM is incapable of reflecting specific features of energy systems that are affecting the results of decision making in developing countries.

34. Which models are suitable? • Decisions makers have to take into consideration some challenges that play an important role in the diffusion of efficient and environmentally sound technologies: • Insufficient capital stock • Tariff and non-tariff trade barriers • Organization of international trade • Inadequate R&D policy • Lack of institutions for upgrade • Inadequate human resources • Infrastructure development • Modellers should use effective software, introduce high quality of input data and be as a user well trained. • Economic, environmental and social barriers differ + There isn’t a fit-all model Software sources might be difficult to adopt, adapt and combine for re-use in other contexts

35. Open Source Models Modern models: Complex interactions and high quality of analytical tools and data  Using them correctly require: • Validated models must be available and appropriate for the target environment. • Suitable data must be available for input into the model and for verifying model-based results. • Models must be operated by people trained in the use of the tools and in interpreting the outcomes for local conditions. Satisfying these conditions: Development of Open Source Software (OSS) + Accessible data.

36. Open Source Models • Advantages: • Set targets and monitor outcomes • Design strategies and policies • Make evidence-based decisions • Enable citizens to make informed choices. • Open data sources are an application of transparency and avoid efforts of replications and data collections. • All OSSs represent a common paradigm: High adaptation + Promising characteristics to be used in developing countries + Able to meet high standards relative to the proprietary software sources. • Capacity building and education in the field of energy modelling should be accessible to satisfy the condition of trained users vision.

37. Examples of Open Source Models

38. Global Trade and Environment Model GTEM • This model was designed to capture harmful energy subsidies and presents scenarios tackling this burden on the state budget. • GTEM is characterized by multi-region and multi-sector coverage and dynamic general equilibrium taking into consideration the world economy reflected through global change policies. • The origin of this model: MEGABAR and GETAP models • The added value of GTEM: The interactions between different sectors of an economy + Estimation of the impacts of policies on key economic variables(price of consumer goods, inputs into production, sectoral and regional outputs, trade and investment flows, regional income and expenditure levels) • Environmental aspect: Modelling emissions, i.e. CO2, methane and nitrous oxides. • GTEM uses a business as usual simulation and presents a commodity disaggregation since it has been used in 45 regions and over 50 industries. • The GDP used as an input is obtained from IMF.

39. Open Source Energy Modelling SystemOSEMOSYS • Flexibility: OSeMOSYS is modifiable depending on the target of the modelling, e.g. it has been applied to South Africa for energy planning. • OSEMOSYS: is composed of three main parts • Plain English description • Algebraic formulation • Detailed description of the model inputs, outputs and parameters. • OSeMOSYSis an optimization model and aims to calculate the lowest net present cost of an energy system to meet given demands. • It is used for long-term energy planning by developed and developing economies’ researchers even though developing countries are characterized by high CO2emissions, high resource use and an elevated demand for energy services. • The model is easily updated and modified under the form of series of components “Blocks”

40. Open Source Energy Modelling SystemOSEMOSYS • Each block is composed of: • a plain English description- of sets • Parameters • Variables • Constraints • Objectives  The plain English description helps on matching the policy maker and energy system analyst’s expectations.

41. Conclusions • Initially: ES were adapted to ensure that all the social classes have access to energy and to assure local industrial growth. • Nowadays: Subsidies distort price signals + Fail to reflect the true economic cost of supply + Represent a burden on the government budget + Crowd out other necessary expenditures or investments. • Results: Over-use, inefficient and wastage of energy + Extra-pollution. • Keeping or implementing subsidies to overcome market failure  harmful for the economic efficiency. • The removal of energy subsidies: increases energy efficiency and decreases environmental damages.

42. Conclusions • The removal of energy subsidies: increases energy efficiency and decreases environmental damages. • A reform of energy policy plans should prioritize ancillary services, such as storage, long term energy generation planning projects with tax incentives • The choice of a model is critical and should be fully scoped prior to selecting the software to use, and the results of one model should be fully validated by another similar model. • Choosing the adequate model is based on the criteria characterizing the energy planning  There are some general characteristics shared by all models + specific ones that the developer judges necessary at a certain situation.

43. Conclusions • The increasing number of programs and the huge criteria that could be taken into consideration  Classifying ESM is very complex • Selecting the proper model requires an overview of the different classes  An overview covering all classes arbitrary is not yet examined by the literature Classification of models based on their evolution within time and therefore adopting their main purposes, i.e. demand side, supply side, or energy system. • Bottom-up, accounting models are the most suitable for capturing developing economies characteristics. • Developing countries specifications differ greatly. Tunisia may be quoted as an example for the dilemma of energy access which is presenting most of developing states major problem. Depending on the flexibility of the model and its transparency, the case of open-source models, researchers might develop the adequate model depending on the needs and conditions.

44. Thank you for your attention