A Singular Spectrum Analysis based Approach to Price Forecasting for a Day Ahead Electricity Market

Deregulation across various electricity markets created a need for an operational framework that has capability to run similar to the dynamics of real world commodity markets possessing the competitiveness to ensure long run stability, providing opportunity to every participant and maintaining the price level of commodity within the reach of consumer. The electricity framework takes into account the power system balancing constraints required to ensure its reliability and security. This complex structure with its aim of competitiveness motivated the participating entities to run the generating capacities at the optimum level, forced the operators to minimize the transmission losses and created an environment for the consumers to take the benefit of variable pricing conditions. Specially, these effects are reflected via short term electricity price forecasting (STPF) in a significant amount. The STPF created the required decision base for the entities to bid in market with an effective strategy of risk management to hedge against the highly volatile pricing events to ensure the required amount of liquidity and making better economic conditions while in case of large consumers, it helps to either curtail or schedule the loads to minimize the cost of energy. It also helps them to prepare an alternative strategy to make available the required energy via small private generating units during peak price hours. To account for different requirements of various entities, accurate price forecasting is a crucial task. The complexity of the price dynamics also involves the variations attributed to spatial effects in different operating regions such as calamities and extreme conditions. In this paper, Singular Spectrum Analysis based model is used to forecast the price. The simulations results show the accuracy of proposed model.