This study aims to investigate the dynamic relationship between electricity consumption (EC), peak load (PL) and gross domestic product (GDP) in the Kingdom of Saudi Arabia by employing a vector auto-regression (VAR) analysis using time series data from 1990-2015. We also employ Granger causality testing, the impulse response function and forecast error variance decompositions. The forecasts for the total EC, PL and GDP using the VAR model with a ten-year horizon show positive growth rates of around 7.21%, 6.87% and 14.14%, respectively. We find bidirectional Granger causal relationships between the PL and the EC and GDP. The results also show that 29% of the PL is explained by its own innovative shocks. The contributions of the EC and GDP to the PL are 10% and 34%, respectively. This study demonstrates PL to be a significant variable that relates to growth.

This paper examines the impact of solar and wind prices on the Australian electricity spot and options markets for the period January 2006-March 2018. Using a vector autoregression analysis, we examine both the direction of influence and influence absorption through Granger causality testing, the impulse response function, and forecast error variance decompositions. We identify a unidirectional Granger causal relationship between the solar and wind electricity prices and the spot prices in New South Wales, Queensland, Victoria, and South Australia. The forecast results suggest that the solar and wind electricity prices reduce the spot and options electricity market prices. These results are important for energy policymakers and government organizations that support renewables, as their use not only decreases the wholesale spot prices, but also encourages initiatives to explore and switch to alternative energy sources, which tend to be more cost effective and environmentally friendly.

This study aims to develop autoregressive integrated moving average (ARIMA) models to predict the solar, wind, spot and options pricing over the next 2 years, with historical data being used in a univariate manner to understand market behaviour in terms of trends. The assessment is made in the context of the Australian National Electricity Market (ANEM). The ARIMA models predict the future values of the monthly solar, wind, spot and options prices for various Australian states using time-series data from January 2006 to March 2018. The results show increases from 30.46% to 40.42% for the spot electricity prices and from 14.80% to 15.13% for the options electricity prices in the ANEM with a 2-year horizon. The results further show that wind prices are expected to increase by an average of 5.43%. However, the results also show that the average solar electricity prices will decrease by 67.7%.

Following the liberalisation of the global electricity markets, spot and options markets have been established in many countries. Electricity pricing issues, coupled with increased concern regarding global warming and the greenhouse effect, represent the driving factors behind electricity price movements. Australia, Germany, the United States (US) and other countries worldwide have increasingly shifted their focus away from fossil fuels and towards energy generated from renewable sources, including solar and wind power. This paper examines the behaviour of the Australian, German and US electricity markets in terms of the impact of solar and wind pricing on the electricity spot and options markets for the period January 2006 to March 2018. Using a vector autoregression analysis, we examine both the direction of influence and the influence absorption through Granger causality testing, the impulse response function and forecast error variance decompositions. Our findings indicate that the electricity markets in Australia, Germany and the US are interdependent and related with regards to solar and wind price changes, meaning that the investigated electricity markets are influenced by movements in other electricity markets. The findings of this study are important for investors, energy analysts, government organisations and policymakers.