Open AccessInterval optimization‐based scheduling of interlinked power, gas, heat, and hydrogen systems
Author(s) -
Nasiri Nima,
Sadeghi Yazdankhah Ahmad,
Mirzaei Mohammad Amin,
Loni Abdolah,
MohammadiIvatloo Behnam,
Zare Kazem,
Marzband Mousa
Publication year - 2021
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/rpg2.12101
Subject(s) - wind power , scheduling (production processes) , integer programming , solver , power to gas , computer science , power system simulation , cogeneration , natural gas , electric power system , flexibility (engineering) , operating cost , electricity , energy storage , mathematical optimization , electricity generation , engineering , power (physics) , electrical engineering , waste management , mathematics , algorithm , chemistry , physics , electrolysis , statistics , electrode , quantum mechanics , electrolyte
The combined heat and power (CHP) plant is one of the emerging technologies of gas‐fired units, which plays an important role in reducing environmental pollutants and delivering high energy efficiency. Moreover, the hydrogen energy storage (HES) system with extra power storage from wind turbine via power to hydrogen technology allows the injection of stored energy into the power grid by reverse hydrogen to power services, offsetting in this way the uncertainty of wind power. Consequently, simultaneous usage of CHP and HES units not only makes the maximum use of wind power distribution but also increases flexibility and reduces the operating costs of the entire network. Therefore, this paper proposes an interval optimization technique for managing the uncertainty of wind power generation in the integrated electricity and natural gas (NG) networks considering CHP–HES. Moreover, to enhance the flexibility of the NG network, a linearized Taylor series‐based model is proposed for modelling linepack of gas pipelines in the proposed scheduling framework that is formulated mixed‐integer linear programming and solved using the Cplex solver. The obtained results indicate that the simultaneous use of CHP–HES in the day‐ahead scheduling reduces the operating cost and increases the flexibility of the whole network.