2023-04-23 21:59:24
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Partly due to the gradual integration of the European electricity system and market, it is increasingly important that weather forecasts are available for larger geographical areas. The fact that the European electricity supply is partly dependent on natural gas-fired power plants also points in this direction. Parallel to the decline in pipeline gas imports, energy carriers regasified from liquefied natural gas (LNG) transported by ship from other continents are playing an increasingly important role in meeting fuel needs.
The destinations of LNG tankers are also extremely varied geographically, which may not even be finalized when the ships depart. The LNG market has thus essentially globalized the gas market, which is significantly affected by weather-related correlations. Local weather phenomena thus acquire global significance, directly influencing local supply and demand, and indirectly shaping market conditions in distant parts of the world.
As a result of all this, monitoring the current and expected weather of the entire world is increasingly essential for efficient and effective electricity trading. MVM Partner’s dealers regularly receive information on the expected development of the weather, shorter a day and three times a week longer, and once a week they are also informed regarding the expected meteorological conditions in the United States and China for the next 45 days and the likely level of energy consumption.
Twenty years ago, the problem would not have arisen
Overall, therefore, the role of the weather in terms of energy trade has become more significant, but due to climate change, it has also become more unpredictable, especially in the longer term. In the short term of one week, there is no decrease in the accuracy or quality of forecasts, but for several months in advance, for example, the answer to the question regarding the prospects for summer nuclear or hydropower production is clearly much more uncertain nowadays than even just two decades ago, when it was not really the mentioned problem existed.
All of this has serious effects on energy trading activities as well. The rise of renewables and the increase in their production fundamentally increases the volatility of market prices. In the past, until the role of renewables was significant, prices were basically determined by the price at which conventional power plants might purchase fuel and the efficiency with which they were able to produce electricity. Nowadays, when production is largely provided by renewables in certain periods, extremely low or even negative prices can develop on the wholesale electricity market, since weather-dependent renewable power plants produce without fuel and with low variable costs. Also due to their weather-dependent nature, even though it may also happen that the production of renewable energy drops suddenly and dramatically (the Germans call this the dunkelflaute effect, when neither the sun shines nor the wind blows), thereby also the market supply, which is an immediate significant boost affects prices.
The general trend is related to the expansion of the renewable capacity, according to which the shorter the forecast, the more accurate the result, therefore trading is getting closer to the time of production. Thus, it is expected that the intraday and next-day markets, i.e. the relatively well-predictable periods of renewable production, will play an increasingly important role in trading as a whole. If the production differs from the forecast, the surplus or deficit must be sold by the market participant, due to which the reduction in trading periods is associated with an increase in market liquidity.
Can the weather transform the market concept?
Another electricity market challenge is partly related to the weather and the expansion of renewable capacities. In its current form, electricity trading (day and intraday) usually takes place at the regional level in Europe, with the exception of a few countries, which, due to their geographical conditions, trade on their markets, which are divided into several zones and have different price levels. For example, in Italy, consumption is higher in the northern region, while renewable production is concentrated in the southern areas, which can cause bottlenecks in the network during periods of significant wind energy production.
Therefore, according to certain opinions, motivated by technical considerations, it would be advisable to transform country-by-country trading into a market structure in which the so-called offer zones would be formed in accordance with the circumstances. If this concept were to gain ground, it might even mean that in the future, Hungarian electricity production and demand will not necessarily be traded in Hungary, but, for example, in a regional market called the East-Central European zone.
Such a concept would rather divide larger markets, for example in the case of Germany, which has similar problems with Italy in terms of wind energy, into northern and southern parts. The problem that can now be called chronic in Germany and especially in the neighboring countries is that the surging wind energy production in northern Germany often physically reaches southern Germany in such a way that it makes a big detour and uses and burdens the Polish, Czech or even Hungarian grids. . Experts are trying to solve this situation with various measures and market mechanisms, but problems of this kind are expected to come more and more to the fore with the expansion of renewable capacity.
Artificial intelligence helps
The processes taking place in the energy sector and climatic conditions make the role of meteorology and weather forecasts and the further development of weather models increasingly important. All of this requires meteorologists participating in the work to take energy aspects into account, while energy traders must acquire some meteorologist’s perspective.
Nowadays, artificial intelligence is also used at MVM Partner to prepare and clarify weather forecasts used for the purposes of energy trading, so artificial intelligence can also contribute to the short-term scheduling of renewable electricity production.
Although we are still relatively at the beginning of the development and application of artificial intelligence and machine learning, they cannot be replaced by human labor even today, since technology offers a much faster and more efficient solution in the given work process. In the longer term, technology can reduce the uncertainty factor of forecasts, even if it will not be able to eliminate it completely, not even considering the possible shortcomings, inaccuracies, and errors of the initial data.
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