A novel methodology for medıum and long-term electricity market modeling

Download

12625977.pdf

Date

2020-11-15

Author

İlseven, Engin

Metadata

Show full item record

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

Item Usage Stats

397
views

221
downloads

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 and long-term horizon. The proposed methodology consists of electricity demand, supply, and price modeling parts for the medium-term horizon and reveals the possible range of electricity prices considering the uncertainties in demand and supply. This methodology is upgraded with two new features for the utilization in the long-term horizon in the changing market environment. The first one of these features is a generator maintenance scheduling model which enables more realistic electricity supply modeling. The second one is a realistic electricity generation expansion planning model which determines the future electricity generation fleet. Based on these modifications and the previously established electricity price model used for the medium-term horizon, this methodology can reveal how electricity market conditions can evolve for a selected year in the long-term horizon. Thanks to its dynamic structure and ability to yield results on hourly basis, the central planner can benefit from this modeling methodology in policy making.

Subject Keywords

Generator Maintenance Scheduling, Electricity Demand Forecasting, Generation Expansion Planning, Electricity Price Forecasting, Electricity Market Model

URI

https://hdl.handle.net/11511/89595

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...
The Relationship Between Energy Commodity Prices and Electricity and Market Index Performances: Evidence from an Emerging Market Ordu, Beyza Mina; Soytaş, Uğur (2016-01-01) We investigate the effect of energy commodity price movements on market and electricity index returns in Turkey for the periods before, during, and after the year 2008. Although the Turkish economy is highly reliant on oil, we find that oil price does not lead either electricity or market indexes. This might be attributable to sluggish integration of financial markets in Turkey compared to developed markets. Natural gas price leads electricity index in the pre-2008 period. Its significance is reduced follow...
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...
Application of bagging in day-ahead electricity price forecasting and factor augmentation Özen, Kadir; Yıldırım Kasap, Dilem (2021-11-01) The electricity price forecasting (EPF) is a challenging task not only because of the uncommon characteristics of electricity but also because of the existence of many potential predictors with changing predictive abilities over time. In such an environment, how to account for all available factors and extract as much information as possible is the key to the production of accurate forecasts. To address this long-standing issue in a way that balances complexity and forecasting accuracy while facilitating th...
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...

Citation Formats

E. İlseven, “A novel methodology for medıum and long-term electricity market modeling,” Ph.D. - Doctoral Program, Middle East Technical University, 2020.