Electricity price forecasting using hybrid time series models

Download

index.pdf

Date

2018

Author

Taş, Büşra

Metadata

Show full item record

Item Usage Stats

368
views

140
downloads

Accurate forecasting of hourly electricity price is very important in a competitive market. Decision makers highly benefit from accurate forecasting. Because electricity cannot be stored, shocks to demand or supply affect the electricity prices. As a result, electricity prices show high volatility. Additionally, it may have multiple levels of seasonality. Therefore, forecasting with conventional methods is very difficult. In this study, hybrid models are constructed with Seasonal Autoregressive Integrated Moving Average (SARIMA), TBATS and Neural Network models for the analysis of hourly electricity prices in Turkey. Time series can contain both linear and nonlinear patterns. Thus, using a hybrid model can give better results in forecasting. Both linear and nonlinear parts of the time series can be modeled by this approach. While SARIMA model and TBATS model are used to capture the linear behavior of the electricity price series. Neural Network is used to model the nonlinearity in the series. Electricity demand is used as exogenous variable. Different combinations of hybrid models and individual models are compared in terms of forecasting performance. The results indicate that mostly hybrid models outperform the individual models in one-week ahead and one-day ahead forecasting.

Subject Keywords

Electricity, Electricity

URI

http://etd.lib.metu.edu.tr/upload/12622456/index.pdf
https://hdl.handle.net/11511/27475

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Hydro-Optimization-Based Medium-Term Price Forecasting Considering Demand and Supply Uncertainty İLSEVEN, Engin; Göl, Murat (2018-07-01) This paper proposes an electricity market model of Turkish electricity market for monthly and yearly electricity price forecasting in medium-term by means of supply and demand dynamics formed via a theoretical approach. The electricity market model created within this scope consists of three main components related to electricity demand, supply, and price segments along with hydro optimization submodel, which takes into account the nonlinear relation between supply and price. Electricity price is determined...
Electricity Price Modelling for Turkey Yildirim, Miray Hanim; Ozmen, Ayse; TÜRKER BAYRAK, ÖZLEM; Weber, Gerhard Wilhelm (2011-09-02) This paper presents customized models to predict next-day's electricity price in short-term periods for Turkey's electricity market. Turkey's electricity market is evolving from a centralized approach to a competitive market. Fluctuations in the electricity consumption show that there are three periods; day, peak, and night. The approach proposed here is based on robust and continuous optimization techniques, which ensures achieving the optimum electricity price to minimize error in periodic price predictio...
Hydro Inflow Forecasting and Virtual Power Plant Pricing in the Turkish Electricity market Çabuk, Sezer; Kestel, Sevtap Ayşe; Kalaycı, Erkan (2019-05-23) Hydro inflow forecasting with most accurate quantitative models is a very crucial subject for effective hydro optimization, virtual power plant pricing, volume risk management and weather derivatives pricing in the Turkish electricity market. Predicting increase or decrease in hydro inflow, seasonal characteristics of hydrological years such as wet, dry or normal, allow the decision-makers to economically use water for optimal periods, quantify of volume risk and determine effective portfolio management str...
A novel methodology for medıum and long-term electricity market modeling İlseven, Engin; Göl, Murat; Department of Electrical and Electronics Engineering (2020-11-15) In the electricity market, there is a considerable degree of uncertainty in electricity demand, supply, and price due to the uncertainty in parameters such as economic growth, weather conditions, fuel prices, and timing of new investments, etc. These factors in return affect the predictability of the electricity market. This thesis aims to increase the predictability and observability of the electricity market by means of a suitable and validated electricity market modeling methodology designed for medium a...
Short-term electricity load forecasting with special days: an analysis on parametric and non-parametric methods Erisen, Esra; İyigün, Cem; Tanrisever, Fehmi (Springer, 2019-01-01) Accurately forecasting electricity demand is a key business competency for firms in deregulated electricity markets. Market participants can reap significant financial benefits by improving their electricity load forecasts. Electricity load exhibits a complex time-series structure with nonlinear relationships among the variables. Hence, models with higher capabilities to capture such nonlinear relationships need to be developed and tested. In this paper, we present a parametric and a nonparametric method fo...

Citation Formats

B. Taş, “Electricity price forecasting using hybrid time series models,” M.S. - Master of Science, Middle East Technical University, 2018.