The RESlion model is implemented as linear program in the modeling software GAMS 23.9.1 (General Algebraic Modeling System) which uses CPLEX 12.4.0.1 by IBM to solve LP problems (GAMS, 2013). The mathematical solution of the objective functions and the equations depends strongly on the data input and the scenario assumptions which should be solved. The expansion
CHAPTER 4. Development of the electricity market model RESlion 85
planning problem consists of about 10 million nonzero elements. The scenarios of chapter 5 require a solving time of the CPLEX solver for the expansion planning problem between 2 and 8 days depending on the problem formulation and input parameters (The GAMS program runs on a desktop computer with 48 GB RAM and 8 CPU cores.). The hourly dispatch problem can be solved within 4 to 8 hours
5 Model-based analysis of future
electricity scenarios for North Africa
In the previous chapter, model development and implementation of RESlion is explained by a description of the model approach which is suitable to analyze the existing North African electricity system and its long-term expansion with increasing shares of RES-E until the year 2050. Different scenarios are applied to the electricity system in this chapter. By setting long- term targets for the RES-E share in the electricity systems, detailed technology choice and site selection as well as effects on conventional power plants, grid structure and demand for energy storages are investigated. Furthermore, results for a continuous development path of the power sector are presented in form of a closed technology and system roadmap from today (reference year is 2010) to the year 2050 by a long-term outlook.
The expansion planning is based on an analysis of each fifth year (2010, 2015, 2020 etc.). The analysis of future electricity scenarios is split in two scenario groups. As many problems and barriers face large-scale electricity transport to Europe, export of electricity is only a potential option for the electricity systems in North Africa. Therefore, general feasibility, economic benefits and total system costs of RES integration in North African electricity are analyzed in a first group of scenarios without effects from other international electricity markets. In a second group, export of RES-E to Europe is possible.
In scenarios of group 1, RES-E share is evaluated with starts to increase from a value of 7% in 2010 to different shares between 50%, 80% and 100% in year 2050 depending on the scenario definition. In contrast to electricity scenarios mainly based RES, a business-as-usual (BAU) scenario projects a slow development of RES in North Africa and very limited RES-E share of 20% in 2050. Another scenario without any technology target purely focuses on lowest total system costs. With detailed sensitivity, the change of technology costs, fuel costs, technology potentials and regulatory framework conditions in the electricity markets are analyzed. The analysis of scenarios of group 2 provides more information on optimal technology choice, site selection, grid expansion and economic effects including generation and transmission costs for an expansion of electricity export to Europe.
5.1 Scenario assumptions
The scenario analysis aims to show the long-term development of the electricity by using renewable energy technologies. As the RE integration should be assessed for different RES-E shares from a cost-optimal perspective, explorative, normative scenarios are implemented in the RESlion model (see section 2.1). Technical constraints of the infrastructure clearly influence the scenario results as the model results should represent a system configuration which provides secure and feasible energy supply for all system conditions.
CHAPTER 5. Model-based analysis of future electricity scenarios for North Africa 87
Some general assumptions regarding future development of electricity markets in North Africa and integration of RES-E are set for all scenarios identically. It has to be noticed that these assumptions have a strong influence on the results of the scenarios. However, the time horizon of 40 years until 2050 provokes high uncertainties of some system intrinsic boundaries. In addition to the uncertainties regarding the framework condition of the electricity system in North Africa, technology options and technological parameters underlie a continuous development process. Technology assumptions are included based on current technology roadmaps for technical and economic features. However, disruptive changes are hardly to include in the model.
The following assumptions for the framework conditions of the electricity system and the energy technologies are implemented for the scenario analysis:
• Status-quo of electricity system: The existing electricity system of North African countries (power plants, transmission lines, electricity demand, and annual generation per type) is given for the reference year 2010 as described in chapter 3. Power plant projects in planning stage are in the database and will be commissioned according to plans of the year 2010, although the Arab Spring has strongly postponed some of the projects.
• National supply: As dependency of electricity imports from other countries increases the risk for economy and society during crises, national energy security is a key policy target in many countries. The security of energy supply on a national level is satisfied by an explicit requirement of 75% national electricity generation on the final electricity consumption in each modeled hour.
• Target fulfillment: The fulfillment of the RES-E targets in a certain year is mandatory in the model by satisfying the specific condition for the share of RES-E contribution compared to overall electricity generation from all sources. Over- and undersupply by RES-E is not possible. Different deployment paths of RE development are covered by the scenarios.
• Curtailment of RE technologies: In all scenarios, curtailment of RE power plants such as wind and PV is possible to avoid over-investment of grid capacities for a few hours per year when RES-E generation shows high feed-in peaks or demand is relatively low. • RE potential: The RE resources are given according to the site selection in section 4.2.
At all sites, sufficient land is available to install power plants and transmission lines. RE power plants could be distributed at one site over several kilometers. But the same wind speeds or solar irradiation are used for all power plants at one site.
• Cost development of technologies: In section 5.3, cost assumptions for electricity generation technologies are given based on learning curve models (Kost et al., 2012b). • Fuel prices: Prices of coal, oil and natural gas from the moderate scenario of Nitsch et
al. (2011) are used as reference. Due to local reserves of oil and natural gas, the prices for both fuels are reduced by 20% to take lower transportation cost into account, compared to German prices. Nevertheless, this price scenario only can be a reference for opportunity costs in countries such as Algeria or Libya as these countries calculate the price of fossil fuel consumption lower due to their national reserves of oil and natural gas.
88 CHAPTER 5. Model-based analysis of future electricity scenarios for North Africa
• Price for CO2 emission allowances: Targets of CO2 emission reductions and prices for
CO2 emission allowances are not relevant for North African countries today. However,
from 2025, the price for CO2 emission allowances is assumed to increase from 7.5 EUR/t
to 40 EUR/t in 2050 the BAU scenario. In scenarios with higher shares of RES-E, this price is 20 EUR/t from 2015 on, in order to facilitate the deployment of renewable energy. This assumption is based on a potential increasing importance of CO2 emissions
also in North Africa.
• Transmission constraints: Land for transmission lines is sufficiently available in all scenarios. New transmission lines are not subject to land constraints or social acceptance. Therefore, transmission expansion is not limited to any constraints in terms of capacities. In reality, planning of large-scale transmission lines between North Africa and Europe include the assessment of suitable geographical corridors and routes to be able to construct the required transmission lines in an acceptable period of time (in European and North African countries).
• Interest rates: Due to the economic and political system, project risks and inflation rates are generally higher in North Africa compared to Europe. Therefore, interest rates (as weighted average cost of capital) for infrastructure investments are assumed to 8% for all technologies. In principle, the model is able to include technology and country specific interest rates into the calculations.
• Discount rate: In the expansion planning model, a discount rate of 3% per year is used to discount costs of different time periods.
Today, the electricity markets of North African countries are weakly interconnected and exchange of electricity is very limited to some GWh per year as explained in chapter 3. Expansion planning, definition of targets and system operation in the power sector are task of the national governments, utilities and grid operators with limited exchange of information with neighboring countries. If a large-scale integration of renewable energy should be accomplished in North Africa, cooperation and electricity exchange have to be increased due to fluctuating RES-E feed-in which causes local over- or undersupply which can be balanced more efficiently in large areas covering a wide distribution of RE power plants. To analyze the future development of the electricity systems properly, the following assumptions regarding higher cooperation and integration of the different electricity markets are defined:
• Integrated electricity market: An integrated electricity market between the North African countries is assumed in the majority of the scenarios. This assumption strongly reduces the restrictions on exchange of electricity between the countries. In scenarios with integrated electricity markets, expansion planning and operation of power plants are modeled from an integrated, international point of view considering an optimal path for the energy system of the total region.
• Combined RES-E targets: National RES-E targets by 2020 and 2030 exist in all North African countries as presented in chapter 3. To obtain a long-term cost-optimized electricity system for the total region with large shares of renewable energy, a single long-term RES-E target for the total region is defined for each time step. This target can be met by different national contributions depending on the national RE resources and cost perspective in each country.
Further assumptions and input parameters regarding the modeled technologies and the electricity market model RESlion are given in chapter 4.
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