To date, a variety of studies have been published on the topic of long term energy system transition. Most studies on future energy systems, however, have a shorter time frame or adopt a supranational focus (e.g. the Energy Roadmap, 2011 or the World Energy Outlook, 2015). It then constitutes a sincere challenge to perform a national energy system transition study with as time horizon 2050 and covering a far-reaching transformation of the energy system.

VITO, together with the FPB (Federal Planning Bureau) and ICEDD, performed a study to scrutinise the transition of the Belgian national energy system towards a future mix entirely based on renewable energy sources. The focus on renewable energy sources and on building a national energy system completely running on renewable energy can be traced back to three main concerns:

  •   – Climate change: Renewable energy sources (RES) are a major instrument in the fight against climate change as RES do not release (net) greenhouse gas emissions.
  • – Security of supply: Most renewable energy sources make use of technologies that ultimately derive energy from natural phenomena like wind, wave, tidal, sun, water, etc. Renewable electricity can be generated from wind power, wave, solar photovoltaics (PV), hydro, geothermal and biomass. Since most RES are then cultivated or naturally available within a nation's territory, RES can help to reduce Belgium's (and Europe's) growing dependence on imported fossil fuels. As a 100% RES based system is independent of imported fossil fuels, it goes without saying that security of energy supply should benefit from a transition to a 100% RES based system.
  • – Economy/competitiveness: creating or expanding a renewable market with a considerable number of direct and indirect jobs can seem appealing. Moreover, an energy system entirely based on renewable energy presupposes considerable efforts in the field of energy savings to drastically diminish the amount of energy needed, which in its turn instigates the activity of a.o. the building sector (through e.g. Insulation, heat pumps, airco systems, etc.). Not only job creation can prompt economic growth, also cost cutting does. As to costs, (most) RES, once in operation, have no fuel costs and less maintenance is needed to keep them functioning (IEA, 2005). However, it is also worth noting that most RES today need subsidies to compete with other technologies. These subsidies should nonetheless decrease steadily over time because of the “learning by doing” process and economies of scale so as to reach a level playing field with the “old” fossil fuels whose prices, due to scarcity issues, will likely not stop increasing in the coming decades if no global action is taken.
The methodology to calculate the pathways/scenarios towards a fully renewable energy mix is based on the TIMES techno-economic modelling framework, developed by the IEA (International Energy Agency, ETSAP implementing agreement). TIMES (an acronym for

The Integrated MARKAL-EFOM System) is an economic model generator for energy systems, which provides a technology-rich basis for estimating energy dynamics over a long-term, multi-period time horizon. Reference case estimates of end-use energy service demands (e.g. car travel; residential lighting and heating/cooling; steam heat requirements in industrial sectors; etc.) are provided by the user. In addition, the user provides estimates of the existing stock of energy related equipment in all sectors and the characteristics of available future technologies, as well as present and future sources of primary energy supply and their potentials.

Using these as inputs, the TIMES model aims at supplying energy services at minimum global cost (at minimum loss of surplus) by simultaneously making equipment investment and operating decisions. For example, an increased demand for electrical appliances in the residential sector due to population growth leads to a number of reactions.

First, it involves a choice of appliances as the market provides different types corresponding to different energy efficiency levels (energy labelling) at different costs. Second, the increased demand for electricity has to be met and either existing generation equipment is used more intensively or new – possibly more efficient – equipment must be installed. The choice of the model of the generation equipment (type and fuel) is based on the analysis of the characteristics of alternative generation technologies, on the economics of the energy supply, and on environmental criteria.

The cost minimisation approach covers the full time horizon, which involves comparing different costs at different points in time. For this purpose all costs are discounted to the base year, using a uniform (social) discount rate.

The TIMES model is less suited as a projection tool. The main purpose of TIMES is the analysis of alternative scenarios, i.e. the impacts of measures are evaluated by comparing two scenarios which have been constructed in a transparent and consistent manner. The approach is more normative from the point of view of the public authorities (prescribing what optimally should happen). Transparency is guaranteed by the explicitness.

Challenges of intermittent energy

When dealing with high penetrations of intermittent renewable energy sources like wind and solar, fluctuations in supply occur and prevail over demand fluctuations. In the case of solar energy, the decomposition of the yearly production profile comprises 3 components: first, day/night fluctuations, second, a long wave starting at close to zero levels in January, peaking in the summer months and ending at similar close to zero levels by the end of the year, and third, a pattern that looks purely random. For wind we observe many cycles, defining periods with low availability extending from a couple of days to a couple of weeks. Dealing in a correct way with the intermittent nature of wind and solar energy is a major challenge for developing renewable energy scenarios and the high share of renewable energies required several model improvements for which we defined specific model adjustments that are also applicable for TIMES models for other countries. Different approaches for dealing with intermittent energy can be thought of: a better integration of the Belgian network in a European network, installing back-up installations, implementing smart grids, using storage technologies, adapting demand to supply.

Storage options are included in order to represent different alternatives in dealing with the volatility of energy supply. So far, the only mass storage available in Belgium is the pumped water storage facility in Coo, representing a capacity of 5 GWh, allowing producing electricity at a power rate of 1.2 GW. Additional storage facilities are included in the model: day/night and seasonal storage options for electricity, electricity to hydrogen and hydrogen to electricity options (electrolysis and fuel cells) and hydrogen storage options.

Standard TIMES models consider 12 sub-periods in one year, representing 4 seasons and 3 daily levels: night, day and peak. Usually this distribution in twelve time slices is chosen to represent the variability in demand and one peak demand slice simulates a peak close to historical levels. Empirically it has been found that this level of detail is sufficient for dealing with fluctuations in demand when supply is steerable. However, when dealing with high penetrations of intermittent renewable energy sources like wind and solar, fluctuations in supply occur and prevail over demand fluctuations. In order to represent this in the model the number of time periods within one year has been extended to 78 periods, equivalent to 26 two-week periods and 3 daily levels. The main goal of this study is to examine the feasibility and the impact of a 100% renewable energy target on the future Belgian energy system 63. Although the realisation of such a transformation within a 40-year perspective may at first seem highly ambitious in a nation rather poorly endowed with natural resources and possessing both a highly energy-intensive industry and an energy-greedy residential sector, it appears to be technically feasible.

1. Extensive electrification and almost 100% renewable electricity by 2030

Moving to a 100% renewable energy system implies a radical transformation of nearly all sectors of the economy. The model shows that the strongest growth of renewable technologies is concentrated in the period 2030–2050. Nevertheless, some sectors experience thorough impacts earlier on through high growth rates of renewable energy technologies. This is particularly the case in the electricity production sector, which has to be transformed almost completely into a renewable based sector by 2030, since investments in the power generation sector appear to be the least expensive. Furthermore, the results of the model indicate that a 100% renewable energy system needs extensive electrification, causing a doubling or even tripling of the current electricity production by 2050.

2. Energy imports strongly diminish, but remain important

Transforming the energy system into a 100% renewable system will require considerable investments in demand-side management technologies, storage capacities and energy production installations. On the other hand, a higher share of renewable energy or lower energy consumption implies less fossil fuel purchases, which may reduce the national external fuel bill. Indeed, it is evident that solar, wind, hydroelectric or geothermal energy production installations do not need fuel input to produce useful energy for final consumers. The only exceptions to this rule are biomass and electricity imports which will tilt the balance of payments. Even so, the share of total imported energy tumbles from 83% in the reference scenario to a range between 15% and 42% in the renewable scenarios.

3. Additional energy system costs are rather stable over the different scenarios

The energy system cost is the sum of all energy expenses in an energy system. It consists of variable, fixed and investment costs. We calculated that the increase of the energy system cost amounts to approximately 20% in 2050, or 2% of Belgian GDP in 2050 (GDP2050). The necessary power sector investments vary between 1.0% (scenario focusing on demand decrease) and 1.7% (PV and WIND) of GDP2050. In conclusion, we can say that from today up to 2050, 300 to 400 billion € of investments are needed to transform our current energy system into a 100% renewable energy system.

4. Creation of additional employment

Although total system costs may appear considerable, one has to bear in mind that orienting our energy future towards renewable energy sources also entails benefits. One of those positive effects is further analyzed in the course of this study: the creation of additional employment through the renewable value chains. It was estimated that, by the end of 2030, this effect would create 20 000 to 60 000 additional full-time equivalent jobs compared to the reference scenario. At any point in time, the renewable scenarios create more full-time equivalent jobs than the reference scenario. The high end of the interval is taken in by the PV scenario, given that it necessitates many discrete panel installations combined with a large installation component in PV employment.

5. A new paradigm on energy perception

A new paradigm is arising in the way we think about energy. In a world without excess overcapacity of intermittent renewable energy sources and only limited access to biomass and geothermal energy, long-term (seasonal) storage is becoming extremely expensive. This leads us to believe that, in a cost-optimal modelling approach, a transformation of the energy system towards abandoning strict equilibria and replacing it by installing overcapacity in intermittent renewable energy sources is to be preferred. In other words, it may be more cost-efficient for the Belgian society to adapt in a certain way to the variability of the solar energy flow instead of trying to store enough energy in order to keep our current socio-economic paradigm unchanged. This in turn can impact the current industrial organisation towards more seasonal production oriented sectors, using necessary energy commodities such as electricity only during the cheapest periods of the year when e.g. sunlight is abundantly available and closing down during the darker winter months. This flexibility within the industry can then be perceived as having the same effect as a giant battery in which electricity can be stored in the aggregation state of e.g. steel.


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