A Novel Modified Reptile Search Algorithm for Optimal Planning of a Real
Algerian Distribution Grid with Renewable Energy Resources Considering
Uncertainties of System
Abstract
The increasing demand for energy, coupled with concerns about the
environment and finite resources, has made the use of renewable energy
sources (RESs) crucial. Although wind and solar energy are one of the
most promising sources of renewable energy, their random and uncertain
nature poses a challenge for energy management systems. The integration
of RESs into distribution networks (DNs) is a challenging task that
requires optimizing DN planning. This involves incorporating distributed
generation (DG) systems such as wind turbines (WTs) and photovoltaics
(PVs) into the distribution networks, which can be optimized to reduce
costs, additionally, the resulting configuration can noticeably improve
stability by enhancing the voltage stability index and reducing voltage
deviation. In this paper, a novel Modified Reptile Search Algorithm
(MRSA) is proposed for the optimal planning problem (OPP) of the DN
under uncertainties such as solar irradiance, wind speed, load,
temperature, and energy prices. The proposed MRSA is based on two
strategies, including the fitness-distance balance method and the Levy
flight motion, to boost the searching ability of the standard RSA and
avoid local optima. The suggested MRSA algorithm has been evaluated on
typical benchmark functions and a real 112-bus Algerian distribution
network.