Holistic approach to resilient electrical energy distribution network planning

•This paper proposes a two-objective linearized resilient architecture model for distribution networks.•The proposed framework is based on planning of backup distributed generation, storage, hardening and tie lines.•A scenario-based stochastic programming approach is used to model the uncertainties....

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Bibliographic Details
Published in:International journal of electrical power & energy systems Vol. 132; p. 107212
Main Authors: Shahbazi, Amid, Aghaei, Jamshid, Pirouzi, Sasan, Niknam, Taher, Vahidinasab, Vahid, Shafie-khah, Miadreza, Catalão, João P.S.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.11.2021
Subjects:
Natural disasters
Network equipment planning
Optimal power flow
Resilient architecture
Resilient architecture
Network equipment planning
Optimal power flow
Natural disasters
ISSN:0142-0615
Online Access:Get full text
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Summary:•This paper proposes a two-objective linearized resilient architecture model for distribution networks.•The proposed framework is based on planning of backup distributed generation, storage, hardening and tie lines.•A scenario-based stochastic programming approach is used to model the uncertainties.•Numerical results confirm the capabilities of the proposed strategy in obtaining a resilient distribution network. This paper proposes a two-objective linearized resilient architecture (LRA) model for distribution networks to achieve a strictly resilient network during natural disasters like earthquakes and floods. To obtain this goal, the proposed LRA framework is based on the planning of the energy storage system (ESS), hardening and tie lines, and backup distributed generation (DG). Therefore, the proposed model minimizes the sum of planning and expected operation costs in the first objective function, and the total load shedding and repair costs originates from earthquakes and floods in the second objective function. Also, it constraints to the network planning model, linearized equations of the system operation, and system reconfiguration formulation. Moreover, stochastic programming models the uncertain availability of the network equipment during the natural disaster condition, the load and electricity price. In the next step, the ε-constraint-based Pareto optimization is used to achieve an equivalent single-objective LRA model and obtain the best compromise solution. Finally, the proposed strategy is applied to a standard test distribution network. Numerical simulation confirms the capability of the proposed method in obtaining a resilient distribution network during natural disasters.
ISSN:0142-0615
DOI:10.1016/j.ijepes.2021.107212