Abstract
The liberalization of the power markets gained a remarkable momentum in the context of trading electricity as a commodity. With the upsurge in restructuring of the power markets, electricity price plays a dominant role in the current deregulated market scenario which is majorly influenced by the economics being governed. Electricity price has got great affect on the market and is used as a basic information device to evaluate the future markets. However, highly volatile nature of the electricity price makes it even more difficult to forecast. In order to achieve better forecast from any model, the volatility of the electricity price need to be considered. This paper proposes a price forecasting approach combining wavelet, SARIMA and GJR-GARCH models. The input price series is transformed using wavelet transform and the obtained approximate and detail components are predicted separately using SARIMA and GJR-GARCH model respectively. The case study of New South Wales electricity market is considered to check the performance of the proposed model.
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Kumar, V., Singh, N., Singh, D.K., Mohanty, S.R. (2018). Short-Term Electricity Price Forecasting Using Hybrid SARIMA and GJR-GARCH Model. In: Perez, G., Mishra, K., Tiwari, S., Trivedi, M. (eds) Networking Communication and Data Knowledge Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 3. Springer, Singapore. https://doi.org/10.1007/978-981-10-4585-1_25
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DOI: https://doi.org/10.1007/978-981-10-4585-1_25
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