As explained in Sections 2.2 and 2.3 above, the analysis of network impacts and requirements makes use of two separate models, which each entail a number of simplifications.
The transmission model is based on a simplified representation of the European transmission systems. This simplified model aims at capturing the impact of congestion not only on national borders but also within individual countries. However, it is clear that the necessary simplifications and the use of a DC representation lead to substantial limitations. Among others, the scope of the transmission model has on purpose been limited to regional exchanges and constraints. Conversely, it does not aim at addressing
possible congestion at a local level, for instance for connecting a large number of RES-E plants to the local transmission grid.
Secondly, the design of the distribution model principally provides for a fully realistic representation of existing distribution networks and the possible issues, which may arise when connecting additional supply or demand at different locations and voltage levels. However, as explained in Section 2.3 the European scale of the analysis has made it necessary to restrict the use of this tool to a range of typical networks. Despite the necessary degree of simplification and standardisation, the distribution model can be expected to provide for a robust view of the resulting effects and the necessary changes and
investments at the distribution level. Nevertheless, it is clear that the results will not be 100% accurate. Further limitations arise from the connection between the pan-European transmission model, on the one side, and the use of typical distribution networks, on the other hand. As explained in Section 2.2 the transmission model is based on different network zones, which are each represented by one single node. In contrast, the typical networks considered by the distribution model are deemed to be connected to the transmission network at a number of notional Grid Supply Points. Depending on the future development and expansion of the transmission network, the number, location and structure of these Grid Supply Points may principally change as well, but this is not explicitly modelled within either of the two models. This implies that the distribution analysis may either over- or under-estimate the need for network expansion mainly at the HV level.
2.4.2 Use of simplified assumptions
In the previous Section, we have already commented on the use of simplified assumptions, resulting for instance from the aggregation of generation technologies by type or the use of typical networks for the distribution analysis. With regards to the representation of conventional generation, arguably the most important simplifications relate to the assumption of standardised technical and commercial properties and the aggregation of all units of a given technology into a single plant in each network zone in the final market model. As explained, these simplifications lead to clear limitations, which have to be considered when interpreting the results of the quantitative analysis in this study.
It is furthermore important to consider further simplifications related to the representation and treatment of RES-E. Among others, these are related to the use of standardised assumptions for different RES-E technologies and the associated production patterns (compare Section 2.1.2.3 on p. 9 above). However, such simplifications appear inevitable when considering the regional scope of the study and the uncertainty related to the future development of smaller RES-E installations in the time horizon until the year 2030.
In addition, we have used standardised assumptions for the connection of DG-RES to different voltage levels. As explained in Section 0, the corresponding assumptions are mainly based on experience from a few selected countries. These standard assumptions may fail to account for other possible outcomes, for instance with regards to the size and connection level of solar PV facilities. A different distribution of DG- RES in terms of size and connection level may lead to different infrastructure needs and costs. We therefore specifically comment on this issue in Section 4.4 below.
Although the methodology applied for this study considers the situation in every single hour of a given year, it is important to note that we have not considered truly critical or extreme situations. All
simulations have been carried out for a single set of hydro and RES production profiles, i.e. they do not consider the impact of dry years with limited availability of hydropower or exceptional situations with a prolonged period with minimal production available from wind and/or solar power, which may lead to an under-estimation of the requirements for back up capacity.
2.4.3 Issues related to the use of PRIMES scenarios
As explained in Chapter 3 below the different scenarios and sensitivities considered by this study are largely based on the analysis carried out in the PRIMES model for the Energy Roadmap 2050, which was published in December 2011.
Apart from consistency with other analytical work by or on behalf of the European Commission, this approach has had the main advantage that we had access to a fairly detailed set of data and
assumptions, which are based on a consistent modelling framework. Among others, the corresponding work was based on broader macro-economic models, which should ensure consistency between the overall economic development, on the one hand, and the specific assumptions used for more detailed analysis of the European power systems, for instance with regards to demand or the evolution of CO2 prices.
In contrast, the PRIMES model did only provide for a much more simplified representation of the physical constraints of the European power systems, for instance in terms of the need to hourly load and RES-E production profiles, or the impact of limited transmission capacities. Moreover, the development in recent years – especially the rapid cost digression of solar PV – implies that some of the cost
assumptions used for the original analysis in the Energy Roadmap 2050 have been partially changed for the current analysis.
These aspects apply that the optimised expansion of different RES-E technologies in the Energy Roadmap 2050 may no be longer optimal from the perspective of the analysis carried out under this study. Consequently, some of the results presented below partially represent underlying changes in assumptions and the different focus of the models used for the original analysis and the current study. These differences should be taken into consideration when interpreting and comparing the results of the different scenarios and sensitivities, in particular with regards to infrastructure requirements and overall costs.
3 DESCRIPTION OF BASIC SCENARIOS AND SENSITIVITIES
3.1 Outline of Selected Scenarios and Variations
This study considers three main scenarios that are differentiated mainly by the future penetration of RES-E, i.e. an optimistic, middle and a pessimistic case. These main scenarios are directly based on the Energy Roadmap 2050 as follows:
1. Optimistic Scenario (Scenario 1)
Based on Energy Roadmap 2050, 'High RES-E' scenario; 2. Middle Scenario (Scenario 2)
Based on Energy Roadmap 2050, 'Diversified Supply Technologies' scenario; and 3. Pessimistic Scenario (Scenario 3)
Based on Energy Roadmap 2050, 'Current Policy Initiatives' scenario.
As illustrated by Figure 29 below, these three scenarios mainly differ by the structure of electricity generation. Conversely, they are characterized by a very similar level of demand. At the same time, a comparison with other studies highlights the fact that there exists considerable uncertainty on the future development of load and energy efficiency. For this purpose, we furthermore consider the two variations of the scenario 1:
- Sensitivity 1a: Optimistic scenario with high demand
Based on the consumption in the 'Reference Scenario' of the Energy Roadmap 2050, but with the same share of RES-E as in the High RES-E scenario; and
- Sensitivity 1b: Optimistic scenario with high energy efficiency
Based on the consumption in the 'High Energy Efficiency' scenario of the Energy Roadmap 2050, but with the same share of RES-E as in the High RES-E scenario.
Figure 29 shows that the combination of the 3 main scenarios with the additional two variations covers a fairly broad range of different developments, including those considered by a variety of other studies27. Moreover, these scenarios specifically allow assessing the impact of different types and levels of RES-E, including in particular decentralised RES-E.
Figure 29 Overview of main scenarios and variations of scenario 1
Based on these assumptions, Figure 30 shows the evolution of final electricity demand in the period from 2010 to 2030 for all five scenarios28. Similar to Figure 29, this illustration clearly shows that the
development of the three main scenarios is broadly comparable. Conversely, scenarios 1a and 1b are characterised by much higher and lower electricity consumption, respectively.
Figure 30 Development of final electricity demand in the individual scenarios
The scenarios in the Energy Roadmap 2050 are characterized by a limited share of solar energy in comparison with other studies; see for instance Figure 31. Against the background of this study, which specifically assesses the impact of decentralized RES-E on distribution networks, it appears desirable to increase the volume of solar energy (and other types of DG-RES) in some scenarios. For this reason, we have considered three additional scenarios with an increased share of DG that are based on the
28 PRIMES data is available for 5-year intervals only. The assumptions for the remaining years have therefore been determined by linear interpolation. 1.500 1.750 2.000 2.250 2.500 2.750 3.000 2.750 3.000 3.250 3.500 3.750 4.000 4.250 4.500 RE S P ro d u ct io n (T W h )
Net Annual Demand (TWh)