Open AccessRisk‐based optimal operation of coordinated natural gas and reconfigurable electrical networks with integrated energy hubs
Author(s) -
Hemmati Mohammad,
Abapour Mehdi,
MohammadiIvatloo Behnam,
AnvariMoghaddam Amjad
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/rpg2.12189
Subject(s) - control reconfiguration , natural gas , electric power system , scheduling (production processes) , computer science , electricity , flexibility (engineering) , cogeneration , distributed generation , electricity generation , reliability engineering , engineering , mathematical optimization , power (physics) , renewable energy , electrical engineering , embedded system , operations management , physics , statistics , mathematics , quantum mechanics , waste management
This paper elaborates on optimal scheduling of coordinated power and natural gas (NG) networks in the presence of interconnected energy hubs considering reconfiguration as a flexibility source. With regard to the energy hub system consisting of several generation units, storage and conversion technologies, as well as natural gas‐fired units, the high interdependency between gas and electricity carriers should be captured. The hourly reconfiguration capability is developed for the first time in a multi‐energy system to enhance the optimal power dispatch and gas consumption pattern. The realistic interdependency of electrical and NG grids is investigated by employing the steady‐state Weymouth equation and AC‐power flow model for power and gas networks, respectively. Furthermore, to handle the risk associated with strong uncertainty of wind power, load, and real‐time power price, the conditional value at risk approach is employed. The proposed model is implemented on the integrated test system and simulation results are presented for different cases. The impact of the risk aversion level on operating cost and optimal scheduling of controllable units is examined. Numerical results demonstrate that reconfigurable capability reduces the operational cost up to 7.82%.