Sudeesha Warunasinghe Arachchige

Outputs

Stochastic Modelling and Simulation of Wind Power, Electricity Load and Natural Gas Prices for Texas Energy Market

The simulation of wind power, electricity load and natural gas prices will allow commodity traders to see the future movement of prices in a more probabilistic manner. The ability to observe possible paths for each process enables traders to get valuable insights for placing their trades on electricity prices. Since these processes have a high seasonality factor, the seasonality component was modelled using a truncated Fourier series and the random component using stochastic differential equations. It is evident from the literature that all the above processes are mean-reverting processes, thus three mean-reverting OU processes were considered as the model for each process. The industry experts believe there is a correlation between wind power, electricity load and natural gas prices. For example, when wind power is higher, and the electricity load is lower, the natural gas prices are relatively low. Thus, to account for this correlation structure in the simulation, we utilised a Vine Copula and integrated it into the simulation. The study is conducted for the Texas energy market and uses daily time scales for the simulations.