Abstract
All over the world, the operators of the power distribution networks (DNs) are still looking for improving the efficiency of their networks. The performance of DNs and lifetime of its component have been significantly affected by its capability of varying their topologies with accurate load gathering via smart grid functions. This paper investigates making use of the smart DNs features and proposes a model of handling the capability of re-allocating the capacitors integrating with configuring the DNs topology. Using the developed formulation, the efficiency of DNs can be improved not only by minimizing the operational costs related to the network losses but also by optimizing the investment costs associated with capacitor re-allocations. Also, various load patterns are employed in the developed formulation to imitate the daily load variations over a year. The improved sunflower optimization algorithm (ISFOA) is proposed in this paper to get the optimal solution of the presented problem. The standard IEEE 33-node feeder and practical 84-node system of Taiwan Power Company (TPC) are the considered test systems. Besides, the uncertainties due to a distributed generation of wind power are investigated via Monte Carlo simulation involved with the proposed ISFOA. Furthermore, to verify the ability of ISFOA to obtain better solutions compared with different recent optimizers, a statistical comparison is carried out based on a large scale 118-node distribution systems. The simulation results reveal that significant technical and economic benefits are obtained by applying the proposed algorithm with higher superiority and effectiveness.
Highlights
Automation of distribution networks (DNs) is one of the most effective frameworks for improving their efficiency and enhancing the reliability of the power service as well [1]
This analysis is based on two exemplary load patterns which were taken from a practical Brazilian distribution utility [65]
All the distribution nodes are possible for locating the capacitors, so the capacitor sites are integers chosen from node 1 to Nb
Summary
Automation of distribution networks (DNs) is one of the most effective frameworks for improving their efficiency and enhancing the reliability of the power service as well [1]. A hybrid approach that combines network reconfiguration and capacitor placement using Harmony Search Algorithm (HSA) is proposed to minimize power loss reduction and improve voltage profile was proposed in [45]. In [46], an improved binary particle swarm optimization method was proposed for optimal network reconfiguration and capacitor placement to reduce power loss. This paper introduces a practical and economic solution methodology for performance enhancement of smart DNs with optimal integrated capacitors re-allocations, distribution reconfiguration and daily load variations. It represents several load patterns with daily load variations over a year horizon, which makes the proposed improvement more realistic and closer to reality.
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