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This paper proposed a novel method to find the Optimal Feeder Reconfiguration (OFR) of radial distribution
network along with optimal site and size of Distributed Generation (DG) with an objective of power loss
reduction. OFR and DG allocation problems are highly non-linear and complex optimization problems,
complexity of problem is further increased with the addition of distribution operation constraints. In the last
two decades, Evolutionary Algorithms (EAs) have been implemented successfully to find the OFR and DG
allocation considering different objective functions. However, search space adopted by EAs are unconstrained,
therefore numerous methodologies are adapted to discard infeasible solutions. The penalty approach is most
widely used in the literature, it requires appropriate selection of penalty parameters using a tedious trial and
error method. In this paper, a new EA Constrained Composite Differential Evolution (C2oDE) is proposed find
optimal capacity and site of DG along with reconfiguration problem. In the proposed algorithms three trial
vectors are generated to strike balance among exploration and exploitation. Furthermore, to find the feasible
solutions in the decision space two most widely used constraint handling techniques that include feasibility rule
and ɛ-constrained method are added to select the trail vector and individuals respectively for the next
generation. Proposed C2oDE method has been validated by considering IEEE 33-bus, 69-bus and 119-bus
distribution networks at five different cases. Simulation results obtained shows better performance of proposed
method against the most recent literature to find both OFR and DG allocation.
Aamir Ali, Noor Hussain Mugheri, Muhammad Usman Keerio, Muhammad Usman Keerio. (2020) Constrained Composite Differential Evolution Search for Optimal Site and Size of Distributed Generation Along with Reconfiguration in Radial Distribution Network , Mehran University Research Journal of Engineering & Technology, Volume 39, Issue 4.
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