A multistage framework for reliability-based distribution expansion planning considering distributed generations by a self-adaptive global-based harmony search algorithm

• A new multistage framework is presented for reliability-based DEP problem.
• In this paper, DGs are considered as an expansion option to increase the flexibility of the proposed model.
• In this paper, effective factors of DEP problem are incorporated as a multi-objective model.
• In this paper, three new algorithms HSA, IHSA and SGHSA are proposed.
• Results obtained by the proposed SGHSA algorithm are better than others.

In this paper, the authors present a new multistage framework for reliability-based Distribution Expansion Planning (DEP) in which expansion options are a reinforcement and/or installation of substations, feeders, and Distributed Generations (DGs). The proposed framework takes into account not only costs associated with investment, maintenance, and operation, but also expected customer interruption cost in the optimization as four problem objectives. At the same time, operational restrictions, Kirchhoff׳s laws, radial structure limitation, voltage limits, and capital expenditure budget restriction are considered as problem constraints. The proposed model is a non-convex optimization problem having a non-linear, mixed-integer nature. Hence, a hybrid Self-adaptive Global-based Harmony Search Algorithm (SGHSA) and Optimal Power Flow (OPF) were used and followed by a fuzzy satisfying method in order to obtain the final optimal solution. The SGHSA is a recently developed optimization algorithm which imitates the music improvisation process. In this process, the harmonists improvise their instrument pitches, searching for the perfect state of harmony. The planning methodology was demonstrated on the 27-node, 13.8-kV test system in order to demonstrate the feasibility and capability of the proposed model. Simulation results illustrated the sufficiency and profitableness of the newly developed framework, when compared with other methods.

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