Analysis Of Electricity Price Volatility Based On TGARCH Model

The role of electricity price in the electricity market is self-evident.It is both fundamental and important,and is the key to ensuring the stable operation of the electricity market.With the deepening of China's power system reform,China's marketization has gradually deepened.Studying electricity price issues and understanding the volatility of electricity price are of great significance to China's market participants and system operators,and are more conducive to ensuring the stable operation of the electricity market and the country's rational optimization of resource allocation.The successful operation experience of the Nordic power market has a profound impact on the power reform worldwide.Therefore,it is very important to study the electricity price forecast of the typical Nordic electricity market and analyze the influence of different exogenous variables on electricity price forecast and electricity price volatility.In this paper,the electricity price fluctuation curve is drawn by selecting different electricity price time series in the two electricity markets,Denmark dominated by wind power generation and Sweden dominated by hydropower generation.The analysis found that the electricity price fluctuations in different power markets all have the characteristics of volatility clustering,multi-period,and mean reversion,as well as other phenomena such as extreme value jumps and leverage effect Therefore,the research in this paper has significance of general applicability in different power markets.Considering the difficulty of electricity price prediction and the fluctuation characteristics of electricity prices,the research methods proposed by scholars at home and abroad mainly include time series method,neural network method and combined model prediction method.With reference to the method of studying financial time series in economics,this paper decided to use the time series method to establish a model for electricity price prediction and analysis of electricity price volatility.In this paper,based on the characteristics of the electricity price series of different electricity markets,an autoregressive moving average(ARMA)model,a multivariate generalized autoregressive conditional heteroscedasticity(GARCH)model,and a thresholded multivariate generalization Autoregressive conditional heteroscedasticity(TGARCH)model,are established for the actual electricity price data in Denmark and Sweden.In addition,when performing model estimation,it is assumed that the residual sequence obtained follows a normal distribution,and the prediction accuracy of different models is analyzed using multiple model prediction error evaluation indicators.The calculation shows that the TGARCH model has better prediction accuracy for both power markets.There are many factors that affect prediction and fluctuation of electricity price.In this paper,three exogenous variables including demand load,renewable energy generation and penetration of renewable energy generation are added to the preferred TGARCH electricity price prediction model to study the influence of different explanatory variables on electricity price and price fluctuation.The study found that in both power markets,the renewable energy generation and penetration of renewable energy generation both reduced the price of electricity and the fluctuation of electricity price;while the demand load increased electricity prices as expected,but reduced the fluctuation of the electric price.The study also found that although these three exogenous variables have the same effect on the electricity price and electricity price fluctuations in the two electricity markets in Denmark and Sweden,the degree of impact is different,and the overall impact on Denmark electricity market is greater than that on Swedish.The analysis shows that the TGARCH model considering renewable energy power generation is more valuable for electricity price prediction and volatility analysis.Studying the impact of renewable energy generation on electricity prices and electricity price volatility is also of great significance to the development and supervision of China's electricity market.