Energy system optimisation

The energy system optimization in REEEM is carried out based on the Pan-European TIMES energy system model (TIMES PanEU). The latter is built with the TIMES model generator REF, developed and maintained within the Energy Technology System Analyses Program (ETSAP) of the International Energy Agency (IEA) to carry on policy and scenario analysis based on technical-economic energy system models. TIMES PanEU is a bottom-up linear partial equilibrium model with the complete European energy system for the time horizon from 2010 up to 2050. The model minimizes the energy system cost according to given energy demands, energy technologies and policy requirements. All costs are discounted to the reference year which is used to calibrate the energy balances and technology stocks based on statistical data. TIMES PanEU covers all European Union member states as well as Norway and Switzerland. Each country is modelled as a single region with implemented trading mechanisms enabling exchanges and interactions between these. The model horizon is divided in five-year intervals, with one year comprising twelve time slices (four seasonal and three day levels). The reference energy system of the model represents all energy and material flows across the entire energy system, starting from the supply of resources and ending with fulling different energy demand services. It is split into seven main sectors (supply, electricity and heat production, industry, commercial, residential, agriculture and transport) reacting different demand structures and transformation steps. All sectors can interact with each other and different indicators (e.g. energy use) are calculated through each step in the reference system. To analyze environmental policies, GHG (CO2, CH4, N2O) and local air pollutants (PM2.5, PM10, NOX, SO2, NH3, NMVOC, CO) are included in the model.

The TIMES PanEU energy system model sits at the core of the integrated framework, and is linked to other modelling and analytical activities (further described in the next sub-sections).

It has undergone some development in this project to ensure robust integration with other modelling and analytical tools. The main steps of the development are here summarised:

  1. Technology innovation outlooks developed in Technology Innovation Roadmaps are integrated, with focus on storage options, renewable energy technologies and heat savings in residential buildings. Those roadmaps provide certain techno-economic figures which are used as input parameters in TIMES PanEU.
  2. An assessment of the health impacts of emissions by the energy sector is carried out. For this purpose, a soft-link is established between TIMES PanEU and EcoSense, where the former takes figures from the latter and uses those as externalities.
  3. A step is to improve representation of some key regional and local specificities of the energy system development of selected EU countries. This part builds on a harmonisation process between TIMES PanEU and case study models focusing on energy supply security and grid and dispatch with the help of the experts in the case study regions, existing base year capacities and electricity trade flow between the regions are improved and the planned capacities from ENTSO-E are incorporated into the model as well.
  4. A further step is the inclusion of impacts of consumers’ technology choices. The main drivers of consumers’ choices regarding heating and transportation are drawn from surveys through a novel discrete choice model. Selected insights are included in TIMES PanEU. The methodology is explained in deliverable D6.1 – Integrated Energy System Model, available here.
  5. The effect of climate changes on heating and cooling demand across the EU is evaluated starting from climate databases. In turn, the effect of these changes on the energy demand-supply balance and investment requirements is assessed through TIMES PanEU.

Finally, economic impacts of the energy transition are integrated to TIMES PanEU with a soft-link with NEWAGE. In this case, the two models have been coupled, with certain data flows related with the electricity generation back to NEWAGE und in return GDP and industrial developments incorporated into TIMES PanEU to update the end-user and industrial demand figures until the models reached convergence. The detailed information for the process is given in deliverable D6.1 – Integrated Energy System Model, available here.

The complete model structure, as well as the advancements carried out for the REEEM project are described in deliverable D6.1 – Integrated Energy System Model, available here.

Main insights

Message 1: Breakthroughs in RES technologies could determine the direction of the energy transition

Innovation in RES technologies could play a key role in the direction of the energy transition. Selected breakthroughs in solar and wind technologies, judged likely by experts within the industrial stakeholder’s network of InnoEnergy, are analysed in deliverable D2.1b - REEEM Innovation and Technology Roadmap: Renewable Energy Integration. One of the breakthrough scenarios is expected in the solar PV industry with the Building Integrated Solar PV technology. Based on the pathway definitions, this breakthrough scenario is applied in the Local Solutions (LS) and Paris Agreement (PA) pathways (see assumptions in Appendix A). The effect of such a breakthrough is seen in the installed capacity deployment in the electricity sector in Figure 4.

Net electricity generation capacity

Figure 4. Net electricity generation capacity in the EU28 [GW].

Another key breakthrough may be in wind offshore, with the diffusion of floating platforms for wind turbines. This is assumed in the CL and PA pathways. According to these figures in deliverable D2.1b - REEEM Innovation and Technology Roadmap: Renewable Energy Integration, offshore wind becomes quite competitive with onshore wind and even with Solar PV. Additionally, the availability factor is higher, due to the higher availability of the resource off the coast. With this competitive advantage, offshore wind has relatively high potential and it is chosen over onshore wind and solar technologies especially after 2030 as a generation technology. Another advantage of offshore wind over onshore is the fact that it does not compete with other sectors for land which -especially in the more densely populated countries- can be an issue. This aspect, however, is not captured in this modelling activity. The technological advancements in certain mitigation technologies may have a significant impact on the direction of the energy transition. Nevertheless, it is important to stress that the high variability of most renewable energy technologies needs a more refined temporal resolution in order to capture their dispatch ability. The grid and dispatch case study sheds light on whether the suggested capacity expansion can be dispatched in certain South-Eastern European countries. Given the significant effect that such breakthroughs could have, the establishment of supporting mechanisms to expedite their occurrence could be a way for the transition to materialize sooner and at a lower cost.

Variations by pathway

It is clear that the consideration of breakthroughs in the modelling leads to a higher share in the final capacity mix which also determines the direction of the transition. In CL, where breakthrough is not considered for solar, the solar capacity in 2050 is less than three times compared to LS and PA pathways results. In general, the share in those pathways is almost similar which is indication that solar could play a major in a deep decarbonisation scenario. On the other hand, as the offshore wind breakthrough scenario is applied in CL and PA pathways, the higher deployment of this technology is observed in both of the pathways. The deployment is higher in the CL pathway compared to PA as this technology is applied as only breakthrough scenario. In the PA, both of the breakthroughs show their effects along with the higher reduction target.

Message 2: Power generation expected to rise

In all three pathways, the total capacity of the power system and the generation are expected to rise. This can be attributed to the fact that decarbonisation leads to higher demand for renewable electricity. The power generation capacity expansion will cause changes to the system. Those changes could be of either operational or economic nature. From an operational point of view, the higher share of renewables will make the system more susceptible to variability which needs addressing from an institutional point of view (e.g. integration of smart grids). For this reason, the model suggests that a certain capacity of natural gas will remain in the system even in 2050, to be used as a backup option, with much reduced full-load hours compared to today. From an economic point of view, this transition will cause the system to shift its cost from operational to capital. This requires a shift in the financing schemes and whether the consumer funds the investment directly or indirectly, depends on the level of system decentralisation. Figure 5 shows the energy mix in terms power generation for the three pathways.

Net electricity generation in the EU28 Figure 5. Net electricity generation in the EU28 (TWh).

Variations by pathway

In the LS pathway, the centralised technologies are limited to support the motivation of the pathway. This means that the nuclear power plant deployment, together with the CCS power plant options are not allowed except for the already planned capacities as there are some pilot projects scheduled in Netherlands, Germany, Spain and Poland. Therefore, the system is forced to move towards decentralised generation options, like Building Integrated Solar PV, which leads to higher power generation capacity compared to the CL pathway; although, these two pathways have the same reduction targets at the EU level overall. However, because of the full load hours of the decentralised technologies which means lower capacity factors compared to conventional technologies, lower electricity generation is observed in the LS compared to the CL pathway. In the PA pathway, the overall power generation is higher comparable to the other two pathways. This would probably mean that an ambitious decarbonisation target such as that proposed in the PA would require coordinated effort by different institutes as, for example, the electrification of industry could rely more on self-funding by the industries themselves rather than the government.

Message 3: Biomass appears to have a significant share in the energy generation – Implications must be examined

Biomass and the energy carriers based on biomass can be defined as mitigation options in different parts of the energy system. However, the exploitable potential of biomass depends on a plethora of local constraints which are not necessarily captured at a national level. One of these factors relates to the intensity of biomass use. Trade-offs with other sectors in which the use of biomass is imperative need be examined as part of energy planning. The REEEM case study on ecosystem services reveals such trade-offs and suggests different mix for the allocation of forestry resources.

Primary Energy Consumption Figure 6. Primary Energy Consumption [PJ].

Variations by pathway

The utilisation of biomass seems to be consistently cost-competitive across decarbonisation pathways. The balance of use across sectors varies according to the pathway narrative and the economically optimal allocation of bioenergy given its high system value. In the CL pathway, it is mainly utilised in the industry sector, as shown in Figure 7, while in LS the priority is given to the transport sector to meet the pathway’s sector-specific targets (Figure 8). On the other hand, in the PA pathway, priority is given to the electricity sector due to biomass CCS availability as a mitigation option. Biomass will be a limited resource and the specific targets will largely determine where it will be most valuable to use it.

The 80% share of renewables in the gross final energy consumption is achieved only in the PA pathway. With potential reduction in the amount of biomass that can be considered as exploitable (when trade-offs with other sectors are better examined), the achievement of the renewable energy target will become even more infeasible.

Final energy consumption by industry Figure 7. Final energy consumption by industry [PJ].

Final Energy Consumption by Transport Figure 8: Final Energy Consumption by Transport [PJ].

Message 4: Beyond 80% reduction such as 95% is feasible in the energy system

In PA pathway, the reduction target 95% is feasible by allowing the biomass CCS option which means that to produce negative emissions through a technology. In the other pathways, given targets are also fulfilled additional to the ETS and NON-ETS targets.

Variations by pathway

Due to different sectoral targets in the CL and LS pathways defined in the narrative of the pathways, decarbonisation is prioritised in industry in the CL pathway and in the residential and transport sector in the LS pathway. The other sectors which are not part of the specific targets have the opportunity to decarbonise less and thus, they benefit from additional reductions in those sectors which have the additional targets. For example, In LS agriculture does not need to decarbonise as much as in CL. As agriculture, residential, transport and commercial share the NON-ETS targets together, with the additional reduction in transport and residential it can reduce less in LS pathway. These benefits are visible in the sectoral CO2 emission levels.

As shown in Figure 9, the emissions by industry are quite similar in the CL and PA pathways, indicating that industry has maximised reductions in CL, as no further reductions emerge under PA. These graph shows the emissions before they captured. Therefore, PA numbers shows the values before they are captured biomass CCS. Conversely, the LS pathway sees less decarbonisation in industry due to the additional targets and therefore effort in the residential and transport sectors.

CO2 emissions in the EU28 Figure 9. CO2 emissions in the EU28 [Mton].

Message 5: The way the society responds to the transition will have an impact on the energy mix

In the CL and LS pathways, the push for the decarbonisation comes from the different actors in the energy system. The share of the electricity and emissions-free energy carriers across sectors differ.

Variations by pathway

Higher level of electrification is observed in the CL in industry compared to LS (Figure 7). On the other hand, electrification is higher in the residential and commercial sectors in LS compared to CL (Figure 10). Additionally, the highest electrification is observed in all the sectors in the PA pathway due to the need for more mitigation, as shown in Figure 11.

Final energy consumption in the residential sector Figure 10. Final energy consumption in the residential sector [PJ].

Total Final Energy Consumption Figure 11. Total Final Energy Consumption [PJ].

Additionally, environmental heat and especially solar thermal grow rapidly in the LS pathway to fulfil the decarbonisation targets in the residential segment. This proves that the aforementioned technologies could have an even higher contribution to the total energy generation according to given decarbonisation targets.