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Strategic Bidding of a Hydropower Producer under Uncertainty: Modified Benders Approach
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (Electricity Market Research Group (EMReG))ORCID iD: 0000-0002-6973-3726
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 1, p. 861-873Article in journal (Refereed) Published
Abstract [en]

This paper proposes a stochastic bilevel program for strategic bidding of a hydropower producer. The price, quantity and ramp-rate bids are considered. The uncertainty of wind power generation, variation of inflows for the hydropower producer, and demand variability are modeled through the moment-matching scenario generation technique. Using discretization the stochastic bilevel program is reformulated as a stochastic mixed-integer linear program (MILP) with disjunctive constraints. We propose a modified Benders decomposition algorithm (MBDA), which fully exploits the disjunctive structure of reformatted MILP model. More importantly, the MBDA does not require optimal tuning of disjunctive parameters and it can be efficiently parallelized. Through an illustrative 5-node example, we identify possible strategies (specific to a hydropower producer) for maximizing profit, which in turn leads to market insights. We also use the IEEE 24-node, 118-node, and 300-node case studies to show how our parallelized MBDA outperforms the standard benders decomposition algorithm. The parallelized MBDA is also compared to the state-of-the-art CPLEX solver.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 33, no 1, p. 861-873
Keyword [en]
Disjunctive constraint, modified benders decomposition algorithm, stochastic bilevel program
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-207089DOI: 10.1109/TPWRS.2017.2696058ISI: 000418776400076OAI: oai:DiVA.org:kth-207089DiVA: diva2:1095681
Note

QC 20170519

Available from: 2017-05-15 Created: 2017-05-15 Last updated: 2018-01-17Bibliographically approved
In thesis
1. Impact of High levels of Wind Penetration on the Exercise of Market Power in the Multi-Area Systems
Open this publication in new window or tab >>Impact of High levels of Wind Penetration on the Exercise of Market Power in the Multi-Area Systems
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

New European energy policies have set a goal of a high share of renewable energy in electricity markets. In the presence of high levels of renewable generation, and especially wind, there is more uncertainty in the supply. It is natural, that volatility in energy production induces the volatility in energy prices. This can create incentives for the generators to exercise market power by traditional means: withholding the output by conventional generators, bidding not the true marginal costs, or using locational market power. In addition, a new type of market power has been recently observed: exercise of market power on ramp rate. This dissertation focuses on modeling the exercise of market power in power systems with high penetration of wind power. The models consider a single, or multiple profit-maximizing generators. Flexibility is identified as one of the major issues in wind-integrated power systems. Therefore, part of the research studies the behavior of strategic hydropower producers as main providers of flexibility in systems, where hydropower is available.Developed models are formulated as mathematical and equilibrium problems with equilibrium constraints (MPECs and EPECs). The models are recast as mixed-integer linear programs (MILPs) using discretization. Resulting MILPs can be solved directly by commercially-available MILP solvers, or by applying decomposition. Proposed Modified Benders Decomposition Algorithm (MBDA) significantly improves the computational efficiency.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. p. 95
Series
TRITA 2017:047, ISSN 1653-5146
Keyword
wind integration, market power, game theory, mathematical programming
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-207090 (URN)978-91-7729-434-4 (ISBN)
Public defence
2017-06-13, Kollegiesalen, Brinellvägen 8, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20170516

Available from: 2017-05-16 Created: 2017-05-15 Last updated: 2017-06-13Bibliographically approved

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Moiseeva, EkaterinaHesamzadeh, Mohammad Reza

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