Optimal sizing of photovoltaic and wind turbine distributed generation units in radial power distribution network using ant lion optimization algorithm

Abstract

The radial nature and large resistance to reactance ratio of a radial distribution power networks results in higher voltage drop and power loss than transmission power networks. Also, deviation of bus voltage beyond the allowable limit introduces a voltage instability problem in distribution power network. Therefore, power loss reduction, voltage profile improvement and voltage stability enhancement in radial distribution system (RDS) have become important now days. In recent times, distributed generation (DG) units are optimally allocated in RDS in order to achieve the aforementioned objectives. The capability of solar photovoltaic (PV) and wind turbine (WT) in providing electrical power with clean and environment-friendly makes it ideal to be used as distributed generation (DG) resource in RDS. In this work, single and multiple (two) PV and WT DG units are optimally allocated in RDS in order to reduces real power loss, to improves voltage profile and to enhances voltage stability. An integrated technique based loss sensitivity factor (LSF) and voltage sensitivity factor (VSF) is utilized to identify the optimal bus locations for DG units. The optimal size of single and multiple DG units is computed by applying a multi-objective based ant lion optimization (ALO) algorithm. The voltage profile improvement is achieved by minimizing the maximum voltage deviation index (IVD) of buses and voltage stability is enhanced by maximizing VSI of buses. ALO based optimal placement of single and multiple DG units is investigated on IEEE 33 bus and 69 bus RDSs. The obtained test results of ALO algorithm is compared with the test results of other algorithms presented in the literature to highlight the effectiveness of ALO algorithm. From the comparative analysis, it is found that ALO based optimal allocation of DG units have provided better power loss reduction and voltage profile enhancement than other algorithms. Additionally, it is found that test results of ALO algorithm for optimal placement of WT DG unit have contributed better power loss reduction, voltage profile improvement and voltage stability enhancement than optimal placement of PV DG unit. Furthermore, the performance of ALO algorithm is investigated on both test systems with variable power demand for optimal placement of single and multiple PV DG units. The test results clearly outlined that optimal allocation of DG in RDS having variable power demand through ALO algorithm can also effectively minimize the real power loss, improve voltage profile and enhance the voltage stabi newline