Multiobjective Robust Power System Expansion Planning Considering Generation Units Retirement

Hani Mavalizadeh, Abdollah Ahmadi, Foad Heidari Gandoman, Pierluigi Siano, Heidar Ali Shayanfar

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)


This paper presents a mixed-integer linear robust
multiobjective model for the expansion planning of an electric
power system. An information-gap decision theory-based framework is proposed to take into account the uncertainties in electrical demand and new power system elements prices. The model is
intended to increase the power system resistance against the uncertainties caused by forecast errors. The normal boundary intersection method is used to obtain the Pareto front of the multiobjective
problem. Since the planning problem is a large-scale problem, the
model is kept linear using the Big M linearization technique that is
able to significantly decrease the computational burden. The fuel
transportation and availability constraints are taken into account.
The model also enables the system planner to build new fuel transportation routes whenever it is necessary. The generating units’
retirement is also incorporated into the model, and the simulation
results are showed to the advantages of incorporating units’ retirement in the power system expansion planning model instead
of considering it separately. The proposed multiobjective method
is applied to the Garver 6-bus, IEEE 24-bus, and IEEE 118-bus
test systems, and the results are compared with the well-known
epsilon-constraint method.
Original languageEnglish
Article number7879112
Pages (from-to)2664-2675
Number of pages12
JournalIEEE Systems Journal
Issue number3
Publication statusPublished - 25 Sep 2018


  • Generation expansion planning
  • Information-gap decision theory
  • Mixed-integer linear programming
  • Normal boundary intersection
  • Transmission expansion planning


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