Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Hydro Inflow Forecasting and Virtual Power Plant Pricing in the Turkish Electricity market
Date
2019-05-23
Author
Çabuk, Sezer
Kestel, Sevtap Ayşe
Kalaycı, Erkan
Metadata
Show full item record
Item Usage Stats
328
views
0
downloads
Cite This
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 strategies. In this study, we focus on defining and pricing a hydroelectricity power plant as a Virtual Power Plant (VPP). For pricing of this non-standard option, we work on inflow and price scenarios and optimization model with the possible real world constraints. For the hydro inflow forecasting that will be used in optimization model, we apply Seasonal Autoregressive Integrated Moving Average model with Exogenous Variable (SARIMAX), whereas lagged indexed precipitation data, having the highest correlation with historical inflow data, is included as exogenous variable. In addition to point forecast of hydro inflow, we generate various inflow scenarios by using the distribution of model fit residuals as a stochastic processes for defined VPP. Moreover, we work on hydro optimization problem where objective function is maximizing the expected value of generation by tracing to generated inflow and price scenarios. Price scenarios are simulated by using the hourly shape of historical Day Ahead Market (DAM) prices. As a result, we could analyze the optimization outputs according to different price and inflow levels. For defined VPP, Volume at Risk measure is pressed to explain the meaning of risky volume for the valuation of VPP.
Subject Keywords
Hydro inflow forecasting
,
Hydro optimization
,
Virtual power plant pricing
,
Energy and commodity market
,
Valuation and decision in electricity market
,
Volume at risk
URI
http://www.centerforenergyandvalue.org/files/EV2019%20Book%20of%20Abstracts.pdf
https://hdl.handle.net/11511/75888
Conference Name
7th Multinational Energy and Value Conference, (23 - 25 May 2019)
Collections
Graduate School of Applied Mathematics, Conference / Seminar
Suggestions
OpenMETU
Core
Hydro inflow forecasting and virtual power plant pricing in the Turkish electricity market
Çabuk, Sezer; Kestel, Sevtap Ayşe; Danışoğlu, Seza; Department of Financial Mathematics (2016)
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 strat...
Forecasting the Hydro Inflow and Optimization of Virtual Power Plant Pricing
Çabuk, Sezer; Mert, Özenç Murat; Kestel, Sevtap Ayşe; Kalaycı, Erkan (Springer, 2021-01-01)
Hydro inflow forecasting is crucial for effective hydro optimization, virtual power plant pricing, volume risk management, and weather derivatives pricing in the electricity markets. Predicting hydro inflow allows the decision-makers to economically use water for optimal periods, quantify volume risk and determine effective portfolio management strategies. This study aims pricing a hydroelectricity power plant as a Virtual Power Plant based on Turkish energy markets. For pricing of such a non-standard optio...
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...
Volatility spillover from world oil spot markets to aggregate and electricity stock index returns in Turkey
Soytaş, Uğur; Oran, Adil (2011-01-01)
This study examines the inter-temporal links between world oil prices, ISE 100 and ISE electricity index returns unadjusted and adjusted for market effects. The traditional approaches could not detect a causal relationship running from oil returns to any of the stock returns. However, when we examine the causality using Cheung-Ng approach we discover that world oil prices Granger cause electricity index and adjusted electricity index returns in variance, but not the aggregate market index returns. Hence, ou...
Electricity price forecasting using hybrid time series models
Taş, Büşra; Yozgatlıgil, Ceylan; Department of Statistics (2018)
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 M...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
S. Çabuk, S. A. Kestel, and E. Kalaycı, “Hydro Inflow Forecasting and Virtual Power Plant Pricing in the Turkish Electricity market,” presented at the 7th Multinational Energy and Value Conference, (23 - 25 May 2019), Ankara, Türkiye, 2019, Accessed: 00, 2021. [Online]. Available: http://www.centerforenergyandvalue.org/files/EV2019%20Book%20of%20Abstracts.pdf.