Wind farm portfolio optimization under network capacity constraints

DOI10.1016/j.ejor.2015.05.080zbMath1346.91182OpenAlexW2162680282MaRDI QIDQ320033

Anthony Papavasiliou, Yves Smeers, Hélène Le Cadre

Publication date: 6 October 2016

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2015.05.080

zbMATH Keywords

game theorymarket designMarkowitz frontierrenewable capacity investment

Mathematics Subject Classification ID

Applications of game theory (91A80) Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76) Portfolio theory (91G10)

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Capacity expansion of stochastic power generation under two-stage electricity markets ⋮ Deterministic electric power infrastructure planning: mixed-integer programming model and nested decomposition algorithm ⋮ An integrated planning model in centralized power systems ⋮ Designing coalition-based fair and stable pricing mechanisms under private information on consumers' reservation prices ⋮ A portfolio model for siting offshore wind farms with economic and environmental objectives ⋮ A game-theoretic analysis of transmission-distribution system operator coordination ⋮ Long-run wavelet-based correlation for financial time series ⋮ On the optimized design of next-generation wind farms ⋮ Mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems ⋮ On the efficiency of local electricity markets under decentralized and centralized designs: a multi-leader Stackelberg game analysis

Cites Work

• A generalized Nash equilibrium model of market coupling in the European power system
• The EU regulation on cross-border trade of electricity: a two-stage equilibrium model
• Electricity market clearing with improved scheduling of stochastic production
• Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network
• A Single-Settlement, Energy-Only Electric Power Market for Unpredictable and Intermittent Participants
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