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Short-term Hydropower Planning With Uncertain Wind Power Production
KTH, School of Electrical Engineering (EES), Electric Power Systems. (Electricity market research group)
KTH, School of Electrical Engineering (EES), Electric Power Systems.ORCID iD: 0000-0001-6000-9363
KTH, School of Electrical Engineering (EES), Electric Power Systems.
2013 (English)In: Power and Energy Society General Meeting (PES), 2013 IEEE, IEEE conference proceedings, 2013, 6672693- p.Conference paper, Published paper (Refereed)
Abstract [en]

The main purpose of this paper is to summarize the findings from simulating two stochastic short-term planning models for a price-taker hydropower producer. The first model is a two-stage stochastic linear programming problem. Profound sensitivity analysis is provided in terms of volatility in spot market prices and water inflow level. The results show that for the short-term hydropower planning problems the effect of considering price uncertainty in the stochastic model is higher compared to considering inflow level uncertainty. The second model is a two- stage stochastic linear programming problem. The model generates optimal bids to spot market considering real-time market price uncertainties. While simultaneously bidding to both markets, the results are not realistic. To make the bidding strategies more flexible and robust different approaches are modeled and assessed. Finally one of the approaches is suggested as the most applicable one.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 6672693- p.
Series
IEEE Power and Energy Society General Meeting PESGM, ISSN 1944-9925
Keyword [en]
Hydropower planning, Price takers, Short term planning, Wind power production
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-134309DOI: 10.1109/PESMG.2013.6672693ISI: 000331874302094Scopus ID: 2-s2.0-84893159354ISBN: 978-1-4799-1303-9 (print)OAI: oai:DiVA.org:kth-134309DiVA: diva2:665818
Conference
2013 IEEE Power and Energy Society General Meeting, PES 2013; Vancouver, BC; Canada; 21 July 2013 through 25 July 2013
Note

QC 20131217

Available from: 2013-11-20 Created: 2013-11-20 Last updated: 2016-09-22Bibliographically approved
In thesis
1. Optimal bidding of a hydropower producer insequential power markets with riskassessment: Stochastic programming approach
Open this publication in new window or tab >>Optimal bidding of a hydropower producer insequential power markets with riskassessment: Stochastic programming approach
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Short-term hydropower planning and bidding under uncertainty is a complicated task. The problem became more challenging with the liberalized market environment within the last two decades. Apart from this new reform taking place in the electricity market, the electricity market participants including hydropower producers experienced the second change in the form of intermittent wind power integration into power systems. Thus, previous decision support tools are not capable of fulfilling market participants’ expectations in the new competitive and highly uncertain environment. Intermittent power sources, namely wind power, increase the imbalances in the power system, which in turn increases the need of the regulating power sources. Being a flexible energy source, hydropower can provide regulating power. For this purpose, new hydropower planning and bidding models must be developed, capable of addressing uncertainties and the dynamics existing within market places.

In this dissertation, a set of new short-term hydropower planning and bidding models are developed for sequential electricity markets under price uncertainties. Developed stochastic coordinated hydropower planning and bidding tools can be classified into two classes, as models with exogenousand endogenous prices.

In the first class, developed coordinated bidding tools address the price uncertainties using scenario trees, which are built based on the distribution function of the unknown variables. Thus, the proposed coordinated bidding and planning tools consider all possible future prices and market outcomes together with the likelihood of these market outcomes. To reflect the continuously clearing nature of intra-day and real-time markets rolling planning is applied. In addition, models apply risk measures as another way to hedge against uncertain prices.

In the second class, hydropower stochastic strategic bidding models are developed using stochastic bi-level optimization methodology. Here market prices are calculated internally as dual variables of the load balance constraints in the lower level ED problems. To be able to solve the stochastic bilevel optimization problem, KKT optimality conditions are applied. By this transformation the problem is converted to a single-level stochastic program, which is simplified further using a corresponding discretization technique.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2016
Series
TRITA-EE, ISSN 1653-5146 ; 2016:039
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-192628 (URN)978-91-7595-890-3 (ISBN)
Public defence
2016-10-14, K1, Teknikringen 56, Stockholm, 11:00 (English)
Opponent
Supervisors
Note

QC 20160922

Available from: 2016-09-22 Created: 2016-09-16 Last updated: 2016-09-22Bibliographically approved

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Amelin, Mikael

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