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Multi-objective resilient-constrained generation and transmission expansion planning against natural disasters

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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en

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12

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International Journal of Electrical Power and Energy Systems, Volume 132

Abstract

In this paper, the resilient-constrained generation and transmission expansion planning (RCGTEP) considering natural disasters such as earthquake and flood is presented. The proposed model contains a two objective problem that the first objective function minimizes the construction and operation costs of resiliency sources (RSs) and, in the second objective function, the minimization of the expected energy not supplied (EENS) due to the outage of the system against the mentioned natural disasters is formulated. Also, the proposed model is constrained to linearized AC optimal power flow (AC-OPF) equations, the planning and operating of RSs constraints such as generation units, hardening transmission lines, parallel and series FACTS devices, resiliency constraints and power system angular stability against earthquakes and floods in the presence of critical and non-critical loads. In order to achieve the best compromise response, the RCGTEP single-objective problem is formulated based on the ε constraint-based Pareto optimization. In addition, this model has the uncertainty of RSs availability against natural disasters, so stochastic programming is used for RCGTEP. Then, the Benders decomposition (BD) method is used to solve the proposed problem and achieve the optimal solution in the shortest possible time. Finally, by implementing the proposed model on an IEEE standard transmission network, the numerical results confirm the capability of this method in improving the economic, operation, angular stability and resiliency indices of the power system simultaneously.

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Publisher Copyright: © 2021 The Author(s)

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Hamidpour, H, Pirouzi, S, Safaee, S, Norouzi, M & Lehtonen, M 2021, 'Multi-objective resilient-constrained generation and transmission expansion planning against natural disasters', International Journal of Electrical Power and Energy Systems, vol. 132, 107193. https://doi.org/10.1016/j.ijepes.2021.107193

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