By 2050, the European Union aims to reduce greenhouse gases by more than 80%. The EU member states have therefore declared to strongly increase the share of renewable energy sources (RES-E) in the next decades.

The vast majority of renewable energy is expected to come from wind and photovoltaics (PV). These sources, however, depend on local weather conditions, leading to an increase in stochastic electricity generation. Given a large deployment of wind and PV capacities, weather uncertainty results in two major impacts on electricity systems:

First, the capacity mix must be flexible enough to cope with the volatile RES-E generation, i.e., ramp up supply or ramp down demand on short notice.

Second, sufficient back-up capacities are needed to provide secure supply during times with low feed-in from wind and solar capacities. Otherwise, sharp decreases or increases in renewable production may lead to price spikes on the wholesale market and, if supply and demand do not meet, to potential black-outs.

Renewable Power Capacities
Renewable Power Capacities

The provision of back-up capacity has been intensely discussed in the literature in recent years (for instance Cramton and Stoft, 2008; Joskow, 2008). Concerning flexibility, the discussion is rather new and previous literature is scarce. Lamadrid et al. (2011), an exception, argue that as volatility increases, additional incentives to invest in flexible resources should be implemented in market design. Meanwhile, the Californian system operator (CAISO) has already started to implement ramping products in market design to ensure flexibility.

Flexibility in electricity systems

In electricity systems electricity demand and supply have to be balanced at any time. Flexibility on the supply side was in previous decades mainly necessary, because inelastic demand was subject to fluctuation, following daily, weekly and seasonal patterns. One can – depending on the considered time period – distinguish two kinds of flexibility.

On the one hand, variability relates to longer time frames (larger than 1 h) and especially to the need of thermal power plants to adapt to changing residual load (i.e., demand minus generation by renewable energies such as wind and solar). Renewables do not cause variable generation costs and are thus usually dispatched prior to thermal plants (and depending on market regulations even required to do so). With the increasing share of fluctuating electricity generation from renewables, the demand served by thermal plants is thus subject to a higher variation.

Phases of power plant flexibility
Phases of power plant flexibility

On the other hand, in the shorter time span up to about 1 h, the need for flexibility options mainly arises from the deviation between forecast renewable generation and actual outcome (forecast errors of demand are of minor magnitude). As this deviation occurs on short notice, the electricity system has limited options to adapt, as for instance older power plants need more time to adapt their electricity output, especially if they have to start up first.

Impacts of an increasing share of renewable power

Due to the negligible variable costs of RES-E, they can be integrated on the left-hand side of the merit order. This means they are usually dispatched before other supply technologies. The impact of an increasing share of renewables can thereby best be discussed by analyzing the residual load to be covered by other technologies. The impact is two-fold; on the one hand the (residual) load duration curve is affected and the achievable full load hours for other technologies reduced. On the other hand, the hourly changes of residual load possibly impose additional flexibility of the other supply technologies.

Furthermore the provision of balancing power becomes more relevant due to possibly increasing absolute forecast errors. Based on simulation assumptions, the RES-E share on gross electricity demand in Europe increases from 34% in 2020 to 54% in 2030, and to 75% in 2050. In the short term (until 2020), hydro-power (39% of RES-E generation) and onshore wind (26% of RES-E generation) are the most deployed renewable energy sources. Due to the assumed large deployment of on and offshore wind turbines, more than 50% of the renewable energy is provided by wind power in 2050. Solar technologies – mainly deployed in southern Europe – generate about 22% of the renewable energy.

Renewable generation in Germany and the need for more flexibility
Renewable generation in Germany and the need for more flexibility

Bertsch, Growitsch and Nagl (2014) illustrate the effects of such a high share of renewables with the examples of Germany and the UK. While Germany is well-connected to its neighbouring countries, the UK only has few interconnections and is closer to an insular system. For Germany, the renewable technologies, i.e., wind and photovoltaics, are by assumption diversified, whereas the renewable capacities in the UK consist mostly of on and off-shore wind capacities, which lead to greater challenges due to the fluctuating nature of wind. In 2050, they suggest, Germany has a renewable generation share of 61% of gross electricity consumption, of which about 64% is wind and 20% pv. The UK has a renewable share of about 76% with over 90% wind.

More wind, more solar, more flexibility

Electricity systems with a high share of renewables are confronted with an increasing requirement for flexibility. If the market does not provide sufficient flexibility and requires additional incentives, market design may be affected.

Most recent research has analyzed this issue using a linear investment and dispatch models to simulate the development of electricity markets in Europe up to 2050. The models are extended by including constraints for the provision of balancing power provision depending on renewable feed-in, demand-side reactions, start-up processes of conventional power plants and flexible CCS power plants with a detachable CCS unit.

The results of the integrated analysis show that achievable full load hours of conventional capacities are reduced as renewable generation increases. Depending on the fluctuating renewable share, the volatility of the residual load increases and significantly impacts the electricity system. In 2050, when, e.g., for Germany and the UK with 50% and 70% of fluctuating renewables respectively, the spread of hourly changes increase by 50% in Germany and doubles in the UK.

Power plant flexibility v. operating cost
Power plant flexibility v. operating cost

Extreme values of hourly changes occur more often and reach up to 40,000MW in the UK due to the high wind penetration. In other countries with a more balanced renewable portfolio, values around 20,000MW still occur. Provision of balancing power for forecast errors increases and, given a 10% provision of renewable feed-in, reaches over 10,000MW in some hours. The system adapts to the reduced achievable full load hours by adding more peak-load capacities, i.e., gas-fired power plants.

Due to the relatively low investment costs, they serve as cost-efficient backup technologies. With higher CO2 prices, the general case does not change: only more conventional capacity is equipped with CCS. Due to different storage investments energy storage seem a to be mainly built to prevent renewable curtailment, rather than to provide flexibility. It’s posited therefore, that at every point in time, excess capacity is able to ramp up within 15 min, allowing the electricity system to deal with any flexibility requirement.

Pulling it all together

The main trigger for investing in flexible resources is the achievable full load hours and the need for backup capacity. In a competitive market, the cost-efficient technologies that are most likely to be installed, i.e., gas-fired powerplants or flexible CCS plants, provide flexibility as a by-product. Under the condition of system adequacy, flexibility never poses a challenge in a cost-minimal capacity mix. Therefore, any market design incentivising investments in efficient generation thus provides flexibility as an inevitable complement.

Disruptive innovations and changes in national energy policies might alter the future demand of flexibility. However, rather unlikely that such changes will increase the demand for flexibility beyond the level assumed in latest analysis.

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  1. Wonderful article from one of the best energy writers on the web! Really enjoyed this.

    “Extreme values of hourly changes occur more often and reach up to 40,000MW in the UK due to the high wind penetration.” – is my understanding correct that the UK grid has to deal with an hourly change of 40 GW – ie 40 GW of wind generation turning off during a 1 hour period?

    I would comment that the rise of distributed intermittent generation at a distribution level is making forecasting of demand more challenging as well 🙂

    • Thanks Adam! Much appreciated and that was the most extreme result they indicated and, allow me a very small amount of sensationalism once in a while! You’re quite right to highlight the impact – often greater – that the distribution level events are having. Personally, I think that’s were a lot of the interest is going to be over the coming few decades; local generation, electric vehicles, domestic storage etc. Certainly, if we compare that the larger assets, it’s relatively easy to map out their likely evolution.

I'd love to hear what your thoughts are...please feel free to leave a reply

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