Is congestion pricing the way forward for Europe?



Author: ABB European Advisors

Unprecedented levels of intermittent, “must run” generation are entering the system – reaching almost 40% of total load over the next decade in most Northwest European countries. In Germany by 2017 installed renewable capacity exceeds peak demand, and by 2030 may represent more than 50% of total demand, with unknown impacts on the market.

Increasing amounts of “uncontrollable” plant makes life much harder for System Operators to maintain grid stability, and will also increase constraint costs, reserve costs and losses as the provision of generation to serve load becomes harder to optimize. It is likely that regulatory intervention will be required at some point, to protect the stability of the grid, and potentially to control costs. The most obvious intervention is to ensure that all generation forms are incentivized to at least some extent to generate only when needed; the traditional way to do this is to expose them in some way to market prices.

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Source: ABB, inc.

The US power market is already set up to reflect the costs of grid stability and transmission congestion in their electricity market prices: most US markets have a nodal pricing system, where prices are set at the marginal price at each pre-defined node or location, taking into account (to some extent) physical transportation limitations. In Europe, prices are zonal; a single price for the whole country (or region), which do not reflect the cost of congestion within that zone in any way. However, physical reality does come into play in the end: curtailment of wind generation is already a real issue: surplus wind and PV generation is already being turned down during times of system stress across Northwest Europe, and this is only going to increase in frequency.

As zonal prices do not naturally reflect transmission congestion, the principles of remuneration for curtailed plant in Europe are less than certain, and, for some individual renewable plant, this could be a major factor for future income. These plant may be asked, at very short notice, to stop producing, and if they are not adequately compensated, then there is a “double whammy” on income. Income is affected not only by lower production volumes, but also by missing out on the higher priced periods. This is particularly important for renewable generators as it is impossible for them to shift their generation to other periods to make up the volume loss – they have no control over when it is windy or sunny. Of course, it is also possible that the windfarm owner may benefit from being over-compensated, for example, being turned down during low priced periods and being repaid at average market price. The problem here is in planning – without knowledge of when congestion and curtailment is more likely to happen, and what prices are likely to outturn, it is impossible to predict income.

Moreover, constraints in the transmission and distribution systems tend to be localised and systematic. In other words, if you are unlucky enough to have sited your windfarm behind a local constraint, you may well be asked to turn down time and time again, potentially during the highest priced periods when the transportation system is under particular stress – until the owner of the wires invests in upgrading their capacity.

If the market price included some element of congestion pricing, then that windfarm owner would have been able to avoid the local constraint, and favour more locations with greater transmission capacity. Not only would this help the plant owner, but also would minimise the stresses and investment costs for the wires owner.

Nodal pricing is not without its problems: higher priced nodes may attract new investment, but as soon as their power station comes on line they may alleviate the congestion problem and prices fall.

Transparency, availability and interpretation of data is also a hurdle to effective congestion analysis and pricing. The biggest challenge is getting the right models to handle the massive volumes of data, and the translation of very short term locational signals into longer term trends. Savvy investors are already doing some locational analysis. The European transmission system operators, individually and under the umbrella of ENTSOE, and alongside the REMIT EU directives for information transparency, are also moving in the right direction here. For the first time, transmission data is starting to be published, and joined up across regions. Instead of transmission operators focusing just on the short term within their own transmission area, they are starting to look at pan-European, longer term congestion issues: where the stresses are, and, in particular, how cheap renewable generation can be sited and transported to best meet load.

It is unclear whether European power markets will introduce explicit pricing of congestion into their markets. It is, so far, not envisaged as part of the Electricity Target Model, and to our knowledge only the Polish market is, as yet seriously considering it. Even if European markets choose not to follow the US into full nodal pricing, they should learn from the US markets, which have been learning to forecast, analyse and interpret congestion, and associated pricing and locational signals for many years now.