Negative price spiral caused by renewables? Electricity price prediction on the German market for 2030

Logistic regression models were built and used to show the influence of energy sources, fuel, emission prices and time variables on low and negative price events. The models were tuned and validated with data from 2019 to 2021. The results show that volatile generation of wind and solar power raises the likelihood of low and negative electricity prices. Flexible power sources such as gas power plants, as well as high grid load and conventional generation, relate to higher, more stable market prices. Higher CO2 allowance prices also reduce the likelihood of negative prices, as flexible gas power plants with lower CO2 emissions compared to inflexible coal power plants are more flexible. The biggest influence of the Covid-19-pandemic was on the grid load in 2020 and 2021, which dropped heavily and lowered the electricity price on the market. The prediction analysis shows that in 2030 more low and negative price events will occur if the power supply does not become more flexible. Gas power plants, especially gas turbine peaker plants, help to reduce low prices in the future.

Is COVID-19 pandemic a “Black Swan” event? The impact of the pandemic on the Energy Market

The recent coronavirus disease (COVID-19) pandemic outbreak affected our society greatly, offering a chance to rebuild and rethink our way of living. Energy, as a driving factor of everyday life faced an unprecedented shock. How big was this shock for both the economic and political levels? No consolidated study exists where both aspects are considered. To rethink our way of living, we should reconsider the energy policies strategies for the upcoming years. To date, such an impact has not yet been quantified using price forecasting mathematical models. We have therefore developed a methodology, to quantify the impact of COVID-19 pandemic on European energy market. This paper is addressing the following question “Is the COVID-19 pandemic a Black Swan event?”Evidently COVID-19 had significant consequences on the European energy market. Stocks suffered historical minimum prices duringthis year, with a greater impact on coal technologies than renewable ones. Moreover, stock prices return is showing unexpected fluctuations, hence resulting in incorrectly predicted price forecasts. Despite the initial shock, the energy market is returning to pre-crisis levels, with the renewable technologies leading the comeback. Based on our findings and methods, we conclude that COVID-19 pandemic was not a Black Swan event. We foresee to extend our methodology beyond European energy market and the short-term effects of the pandemic with possible application on the impact of policy makers on energy models. © ECOS 2021 - 34th International Conference on Efficency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems.

Trend Prediction of Stock Index Based on Convolutional Neural Network

The emergence of the COVID-19 has a huge impact on the Chinese and American economies, including the fluctuations of stock price in the financial market. It's significantly valuable to search out the rules of index variability under this post-epidemic era. In this paper, we create an improved Convolutional Neural Network to search out the future trend of Shanghai Composite Index and Nasdaq composite index by using the daily data from January 1, 2011 to April 23, 2021, and find out the characteristics through nonlinear test and random lasso algorithm. The empirical results show that the prediction correction determination coefficients of Shanghai Composite Index and Nasdaq composite index reach 0.87 and 0.97 respectively, which shows that it is feasible and effective to use convolutional neural network to predict the stock index. © 2022 IEEE.