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On optimal hydropower bidding in systems with wind power: Modeling the impact of wind power on power markets
KTH, School of Electrical Engineering (EES), Electric Power Systems.
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The introduction of large amounts of wind power into power systems will increase the production uncertainties due to unforeseen wind power production variations. This will have a significant impact on the required balance management quantities. The most suitable power source to balance fast production or consumption variations is hydropower because of its flexibility and low operational costs.

This thesis addresses the problem of trading of electricity on the daily marketfrom a hydropower producer perspective in a system with large amounts of wind power. The overall aim is to present models that can be used in the trading decision process. This thesis describes models within three different areas:1. Modeling of the demand for balancing power by using deterministic andstochastic models. The stochastic models are based on stochastic differentialequations.2. Modeling of prices on the day-ahead and real-time markets using deterministic and stochastic models. The stochastic models are based on time series modeling.3. Short-term hydropower scheduling of trading decisions. These problems areformulated as stochastic optimization problems where the market prices arerandom variables.

The first two can be used to simulate the impact of wind power on various market prices, while the third simulates how the hydropower producer responds to market prices. Thereby, the thesis presents the necessary models for short-term scheduling of hydropower for a future system with significant amounts of wind power.

This thesis concludes that the proposed price models are sufficient to reflect the relevant price properties, and that the proposed short-term hydropower scheduling models can be used to simulate the actions taken by the hydropower producer in a system with significant amounts of wind power. This is also supported by the case studies in the appended publications.

Place, publisher, year, edition, pages
Stockholm: KTH , 2009. , xi, 76 p.
Series
Trita-EE, ISSN 1653-5146 ; 2009:021
Keyword [en]
Hydropower, wind power, stochastic modeling, optimization
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-10266ISBN: 978-91-7415-301-9 (print)OAI: oai:DiVA.org:kth-10266DiVA: diva2:213677
Public defence
2009-05-13, E1, Lindstedsvägen 3, KTH, Stockholm, Stockholm, 13:00 (English)
Opponent
Supervisors
Note
QC 20100804Available from: 2009-05-08 Created: 2009-04-28 Last updated: 2011-01-12Bibliographically approved
List of papers
1. Optimal regulating market bidding strategies inhydropower systems
Open this publication in new window or tab >>Optimal regulating market bidding strategies inhydropower systems
2005 (English)In: Proceedings of the 15th Power Systems ComputationConference (PSCC), 2005Conference paper, Published paper (Refereed)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-10261 (URN)
Note
QC 20100804Available from: 2009-04-28 Created: 2009-04-28 Last updated: 2010-08-04Bibliographically approved
2. Hydropower planning coordinated with wind power in areas with congestion problems for trading on the spot and the regulating market
Open this publication in new window or tab >>Hydropower planning coordinated with wind power in areas with congestion problems for trading on the spot and the regulating market
2009 (English)In: Electric power systems research, ISSN 0378-7796, Vol. 79, no 1, 39-48 p.Article in journal (Refereed) Published
Abstract [en]

In this paper a day-ahead planning algorithm for a multi-reservoir hydropower system coordinated with wind power is developed. Coordination applies to real situations, where wind power and hydropower are owned by different utilities, sharing the same transmission lines, though hydropower has priority for transmission capacity. Coordination is thus necessary to minimize wind energy curtailments during congestion situations. The planning algorithm accounts for the uncertainty of wind power forecasts and power market price uncertainty. Planning for the spot market and the regulating market is considered in the algorithm. The planning algorithm is applied to a case study and the results are summarized in the paper.

Keyword
Wind power production; Hydropower production; Stochastic optimization; OPERATION; SYSTEM; GENERATION; PRODUCER
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-6137 (URN)10.1016/j.epsr.2008.05.019 (DOI)000261306900005 ()2-s2.0-54049158045 (Scopus ID)
Note
QC 20100608Available from: 2006-09-20 Created: 2006-09-20 Last updated: 2011-03-22Bibliographically approved
3. Modeling real-time balancing power market prices using combined SARIMA and Markov processes
Open this publication in new window or tab >>Modeling real-time balancing power market prices using combined SARIMA and Markov processes
2008 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, Vol. 23, no 2, 443-450 p.Article in journal (Refereed) Published
Abstract [en]

This paper describes modeling of real-time balancingpower market prices by using combined seasonal auto regressiveintegrated moving average (SARIMA) and discrete Markovprocesses. The combination of such processes allows generationof price series with periods where no demand for balancingpower exists. The purpose of the model is simulation of prices toconstruct scenario trees representing possible realization of thestochastic prices. Such scenario trees can be used in planningmodels based on stochastic optimization to generate bid sequencesto the balancing market. The spread of the prices in the treeand the shape of the scenarios are of central importance. Modelparameter estimation methods reflecting the demands on scenariotrees have therefore been used. The proposed model is also appliedto data from the Nordic power market. The conclusion of thispaper is that the developed model is appropriate for modelingreal-time balancing power prices.

Keyword
Markov processes, power prices, SARIMA processes, scenario generation, time series analysis
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-10262 (URN)10.1109/TPWRS.2008.920046 (DOI)000258765900021 ()2-s2.0-43849104117 (Scopus ID)
Note

QC 20100804

Available from: 2009-04-28 Created: 2009-04-28 Last updated: 2012-09-17Bibliographically approved
4. Estimating real-time balancing prices in wind power systems
Open this publication in new window or tab >>Estimating real-time balancing prices in wind power systems
2009 (English)In: Proceedings of the 2009 Power Systems Conference and Exposition (PSCE), 2009, 229-237 p.Conference paper, Published paper (Refereed)
Abstract [en]

As the amounts of installed wind power increases in the power system, the required real-time balancing quantities increases because of the unpredictability of wind power production. Real-time balancing power is usually provided through various market solutions and thus, the prices on such markets will be affected by the increase in wind power production. Consequently, there exist a need for planning and simulation tools concerning the increased balancing demand. This paper therefore describes an estimation model for real-time balancing prices in systems where significant levels of wind power will be added. The model is divided into two steps: The first estimating the changes in required real-time balancing quantities, and the second calculating the corresponding price changes.

Keyword
Estimation models, Power systems, Price changes, Simulation tool, Time balancing, Wind power production, Wind power systems
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-10263 (URN)10.1109/PSCE.2009.4840069 (DOI)000271244500034 ()2-s2.0-70349177536 (Scopus ID)
Conference
IEEE/PES Power Systems Conference and Exposition Seattle, WA, MAR 15-18, 2009 IEEE; PES
Note
QC 20100804Available from: 2009-04-28 Created: 2009-04-28 Last updated: 2011-03-01Bibliographically approved
5. Modeling real-time balancing power demands in wind power systems using stochastic differential equations
Open this publication in new window or tab >>Modeling real-time balancing power demands in wind power systems using stochastic differential equations
2010 (English)In: Electric power systems research, ISSN 0378-7796, Vol. 80, no 8, 966-974 p.Article in journal (Refereed) Published
Abstract [en]

The inclusion of wind power into power systems has a significant impact on the demand for real-rime balancing power due to the stochastic nature of wind power production The overall aim of this paper is to present probabilistic models of the impact of large-scale integration of wind power on the continuous demand in MW for real-time balancing power This is important not only for system operators, but also for producers and consumers since they in most systems through various market solutions provide balancing power.

Since there can occur situations where the wind power variations cancel out other types of deviations in the system, models on an hourly basis are not sufficient Therefore the developed model is in continuous time and is based on stochastic differential equations (SDE) The model can be used within an analytical framework or in Monte Carlo simulations.

Keyword
Stochastic differential equations, Real-time balancing, Wind power
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-10264 (URN)10.1016/j.epsr.2010.01.004 (DOI)000278640200009 ()2-s2.0-80052124524 (Scopus ID)
Note
QC 20100804 Uppdaterad från manuskript till artikel (20110112). Tidigare titel: Modeling real-time balancing demands in systems with wind power using stochastic differential equationsAvailable from: 2009-04-28 Created: 2009-04-28 Last updated: 2011-01-12Bibliographically approved
6. Modeling power prices in wind power systems using non-constant mean and volatility models
Open this publication in new window or tab >>Modeling power prices in wind power systems using non-constant mean and volatility models
(English)Manuscript (Other academic)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-10265 (URN)
Note
QC 20100804Available from: 2009-04-28 Created: 2009-04-28 Last updated: 2010-08-04Bibliographically approved

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