Risk-based distributed generation placement

TLDR

The study proposes a strategy for placing distributed generation units in distribution networks under uncertainty. The approach models uncertainties with fuzzy numbers, formulates a multi‑objective optimization minimizing cost, technical and economic risks, and identifies Pareto‑optimal solutions via a genetic algorithm followed by a max‑min selection. A case study demonstrates the effectiveness of the proposed methodology.

Abstract

A strategy is presented for the placement of distributed generation (DG) units in the distribution networks in an uncertain environment. Uncertainties in the system are modelled using fuzzy numbers. The proposed approach is based on a multi-objective model in which the objectives are defined as minimisation of monetary cost index (including investment, operation cost of DG units and cost of losses), technical risks (including risks of voltage and loading constraints violation because of load uncertainty) and economic risk due to electricity market price uncertainty. The true Pareto-optimal solutions are found with a multi-objective genetic algorithm and the final solution is found using a max–min approach. An example is presented to demonstrate the effectiveness of the proposed methodology.