
Robust coalitional game theoretic optimisation for cooperative energy hubs with correlated wind power
Author(s) -
Cong Hao,
Wang Xu,
Jiang Chuanwen
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2018.6232
Subject(s) - wind power , game theory , computer science , mathematical optimization , power (physics) , mathematical economics , mathematics , engineering , electrical engineering , physics , quantum mechanics
As the development of the energy industry, the integration and complementary of various energy resources will be trends of future multiple energy systems. Energy hub (EH) plays an important role in allocating energy resources efficiently. This study proposes a robust coalitional game theoretic optimisation model to execute the cooperative operation of multiple EHs with correlated wind power. First, an EH model with wind power generation is established. It considers both uncertainties and correlations of wind power. Then, coalitional game theory is introduced to solve the cooperation problem of multiple EHs. Distributed coalition formation algorithm called merge–split rule is developed to form coalitions of EHs. Furthermore, the robust optimisation method is presented to cope with the uncertainties of wind power. Scenarios of correlated historical data are covered by minimum volume enclosing ellipsoid and solved by Khachiyan's first‐order algorithm. Numerical results are given to verify the feasibility and efficiency of our proposed models and methods.