Open AccessCoordinated power system expansion planning considering the DSO's market operations
Author(s) -
KabiriRenani Yahya,
Ehsan Mehdi,
Shahidehpour Mohammad,
FotuhiFiruzabad Mahmud,
MohammadiIvatloo Behnam,
Wang Xu
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.0927
Subject(s) - solver , time horizon , upgrade , integer programming , mathematical optimization , distributed generation , linear programming , electric power system , computer science , renewable energy , ac power , engineering , power (physics) , electrical engineering , physics , mathematics , quantum mechanics , voltage , operating system
The main motivation of this study is to address the challenges due to high penetration of renewable distributed energy resources (DERs) and efficiently benefit from DERs in distribution system planning (DSP). This paper considers a decentralized enhanced platform for DSP which is coordinated with bulk power system planning (PSP) to keep the optimality and security of the whole power system. In the proposed coordinated approach, distribution system operators (DSOs) plan and operate DERs to upgrade their local distribution areas (LDAs), supply forecasting local load growth, and avoid or defer costly generation and transmission expansion planning at the bulk power system. The proposed DSP model consists of two main loops pertaining to the DSO's planning and operation in the first loop and the ISO's simulated operation in the second loop. The Benders decomposition (BD) is employed to iteratively solve the problems. The robust and stochastic programming are used for modelling uncertainties. The DSP problem is modelled as a mixed‐integer linear problem (MILP). The CPLEX solver in GAMS is applied to the modified 24‐bus IEEE RTS in a 10‐year horizon for numerical validation. The results show the performance of the proposed approach in reducing the total cost of supplying growing loads.