Stochastic programming approach for energy management in electric microgrids

DOI10.3934/naco.2014.4.241zbMath1304.90151OpenAlexW2324126123MaRDI QIDQ478949

Gabriela Martinez, Harald Held, Philipp Emanuel Stelzig

Publication date: 5 December 2014

Published in: Numerical Algebra, Control and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/naco.2014.4.241

zbMATH Keywords

stochastic optimizationsmart gridprogressive hedgingpower flow optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Mixed integer programming (90C11) Stochastic programming (90C15)

Uses Software

• Pyomo
• PySP
• OptiRisk

Cites Work

• Unnamed Item
• Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems
• Divide to conquer: decomposition methods for energy optimization
• Dual decomposition in stochastic integer programming
• Scenario reduction in stochastic programming
• Applying the minimum risk criterion in stochastic recourse programs
• Towards globally optimal operation of water supply networks
• PySP: modeling and solving stochastic programs in Python
• Linear Programming Under Uncertainty
• Introduction to Stochastic Programming
• Scenarios and Policy Aggregation in Optimization Under Uncertainty
• Lectures on Stochastic Programming
• Pyomo -- optimization modeling in Python

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