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Top1. Introduction
A capacitor can be defined as a two terminal passive electrical component which is used to store electrical charge. Electricity distribution is the final stage in the delivery of electricity to the end users. A distribution network carries electricity from the transmission system and delivers it to the consumers. It is the most visible part of the electricity supply chain. Presently, due to their simplicity the most of the distribution system are radial in nature. However, reactive power flows in a distribution network always causing high power losses. At heavy loads, the losses due to the reactive power flows can become even more significant. Moreover, these flows result in a high voltage drop at certain areas of distribution network. It is important for the distribution companies to optimize their operation by diminishing the losses and improving the voltages at different busses. To assure minimum loss and adequate levels of voltage at various points of the distribution network, the use of some devices that accomplish an effective voltage control, a reactive power control and a power factor control are essential. Since, the trend towards distribution automation is to improve their reliability, efficiency and service quality, the most efficient operating scenario for economic viability variations is required. Among many of their merits, line loss reduction, voltage profile improvement and reactive power compensation can be the salient specifications of capacitors. To achieve the benefits of loss reduction and voltage profile improvement to the utmost extent under various operating constraints, distribution engineers are required to determine the optimal location and size of the capacitors to be placed at different load levels.
Over the last few years a lot of research works have been carried out on capacitor placement problem in radial distribution system. Many researchers focused on analytical approach (Ng et al., 2000) to determine the optimum location and size of the capacitors in radial distribution system. Jabr (2008) proposed a conic and mixed integer linear programming approach (MILP) to optimize the capacitor to minimize the costs associated with capacitor banks, peak power, and energy losses. Jiang et al. (2008) developed an immune multi-objective algorithm for the purpose of finest allocation of capacitor in radial distribution network. Wu et al. (2010) proposed a loop analysis based analytical approach for the purpose of quasi minimum power loss in a distribution system. A bacterial foraging optimization based fuzzy logic has been reported by (Vahidi et al. 2011) to the optimum location of capacitors in order to reduce the power and energy losses. An analytical algorithm and fuzzy real coded GA was introduced by (Abul wafa et al. 2014) to optimize the capacitor to improve for improving voltage stability in radial distribution system. Besides the analytical approach many researchers developed classical based optimization technique for the purpose of placement of capacitor in radial distribution system. Todorovski et al. (2014) implemented a clustering-based optimization (CBO) to minimize the sum of costs for power/energy losses and capacitor costs in radial distribution system. But they are robust and repeatable method. The requirement to pre-specify locations is the major issue with this approach. It requires a pre-specified capacity or location. This method doesn’t scale well to higher dimensional problems. It is not vigorous with respect to noisy evaluation functions, and the handling of evaluation functions which do not yield a sensible result in given period of time is complicated. The optimal capacitor placement problem in a radial distribution system for variable load level is considered as a non-linear optimization problem with a non-differentiable objective function due to the fact that the costs of the capacitors vary in a discrete manner and the system load also varies continuously throughout the day. Therefore, the classical optimization techniques cannot perform satisfactorily, in solving optimal capacitor placement problems.