Abstract
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Distributed generation (DG) systems are considered
an integral part in future distribution system planning. The active
and reactive power injections from DG units, typically installed
close to the load centers, are seen as a cost-effective solution for
distribution system voltage support, energy saving, and reliability
improvement. This paper proposes a novel distribution system expansion
planning strategy encompassing renewable DG systems
with schedulable and intermittent power generation patterns. The
reactive capability limits of different renewable DG systems covering
wind, solar photovoltaic, and biomass-based generation units
are included in the planning model and the system uncertainties
such as load demand, wind speed, and solar radiation are also accounted
using probabilistic models. The problem of distribution
system planning with renewable DG is formulated as constrained
mixed integer nonlinear programming, wherein the total cost will
be minimized with optimal allocation of various renewable DG systems.
A solution algorithm integrating TRIBE particle swarm optimization
(TRIBE PSO) and ordinal optimization (OO) is developed
to effectively obtain optimal and near-optimal solutions for
system planners. TRIBE PSO, OO, and the proposed algorithm
are applied to a practical test system and results are compared and
presented.