Hydro-Optimization-Based Medium-Term Price Forecasting Considering Demand and Supply Uncertainty

Date

2018-07-01

Author

İLSEVEN, Engin
Göl, Murat

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

272
views

0
downloads

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 based on the intersection of demand curve and merit order curve that has dynamic behavior for dam-type hydrogeneration, import coal, and natural gas power plants. The paper aims to determine the range of possible electricity prices rather than a single price forecast by creating multiple scenarios based on the uncertainties in main variables affecting the electricity prices. Meanwhile, electricity generation portfolio with respect to market participants and primary energy resources as well as price forecasts can be obtained simultaneously. Ultimately, the model can identify how effective a variable of the market on the electricity price is. The developed method is validated via real data.

Subject Keywords

Electricity market modeling, Electricity price forecasting, Optimization

URI

https://hdl.handle.net/11511/47430

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS

DOI

https://doi.org/10.1109/tpwrs.2017.2771618

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

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...
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...
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...
Extensions for Benders cuts and new valid inequalities for solving the European day-ahead electricity market clearing problem efficiently Ceyhan, Gökhan; Köksalan, Mustafa Murat; Lokman, Banu (2022-07-16) © 2021 Elsevier B.V.We study the day-ahead electricity market clearing problem under the prevailing market design in the European electricity markets. We revisit the Benders decomposition algorithm that has been used to solve this problem. We develop new valid inequalities that substantially improve the performance of the algorithm. We generate instances that mimic the characteristics of past bids of the Turkish day-ahead electricity market and conduct experiments. We use two leading mixed-integer programmi...
Application of a Hybrid Machine Learning model on short term electricty demand prediction Assar, Ahmed Khaled Ahmed Farouk; Fahrioğlu, Murat; Sustainable Environment and Energy Systems (2022-2) Electricity demand forecasting is an important procedure in the electricity market and plays a great role in assuring a sustainable and efficient operation chain. By accurately forecasting the demand, one can see a considerable reduction in production costs as well as saving energy resources. Therefore, optimizing the demand forecasting techniques became an inseparable goal of power economics, leading to the introduction of machine learning to this sector that proved to be superior to other pre-defined alte...

Citation Formats

E. İLSEVEN and M. Göl, “Hydro-Optimization-Based Medium-Term Price Forecasting Considering Demand and Supply Uncertainty,” IEEE TRANSACTIONS ON POWER SYSTEMS, pp. 4074–4083, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47430.