International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-9 Issue-3, January 2020 1971 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: C9036019320/2020©BEIESP DOI: 10.35940/ijitee.C9036.019320 Abstract: In recent years, the demand for electric power is growing at a faster rate. This makes present time power system into a more composite one in structure and in terms of placing utility elements, operation, maintenance and control of power system to deliver the electric power to customers. To satisfy the demand for electricity is necessitate more generating units nearer to customer points and need of proper operational planning. The power loss is a major concern towards distribution system performance. Hence, minimization of losses in the system is a major consideration. The distributed generation plays significant role in satisfying the need for electricity demand and also helps in minimization of system losses by adopting intelligent algorithm technique. Among all its advantages, power losses, voltage enhancement and cost benefits are the prime areas of study in distributed generation units. So, placing and allocation of distributed generation acquire more attention towards distribution system. In this paper, an intelligent hybrid optimization technique is proposed for optimal distributed generating unit for minimizing the losses in radial distribution system. The proposed optimization technique is implemented for IEEE 33-bus system radial distribution system. The obtained simulated results provide the good applicability and enhancement in execution of the proposed hybrid method. Keywords : Binary particle swarm algorithm, cuckoo search algorithm, distributed generation, power loss reduction, voltage stability index. I. INTRODUCTION The distributed generation is emerging as very significant and easy solution for power demand. It provides generated power which is placing very close to the consumers and comprises the installation and operation of compact, smaller in size and clean generating units very close to load points. The word Dispersed Generation refers to typically smaller Revised Manuscript Received on January, 2020. * Correspondence Author Somashekar D.P*, Electrical & Electronics Engineering department, SDM Institute of Technology, Ujire, D.K, Karnataka, India, affiliated to Visvesvaraya Technological University, Belagavi, Karnataka. Email: somashekardp@yahoo.co.in Shekhappa G. Ankaliki, Electrical & Electronics Engineering department, SDMCET, Dharwad, India, affiliated to Visvesvaraya Technological University, Belagavi. Email: sgasdmee@rediffmail.com Ananthapadmanabha T, Electrical and Electronics Engineering department, NIEIT, Mysuru, India. Ramya N.S, Electrical & Electronics Engineering department, Research Scholar, VTU, Ujire, India. Email: ramyans90@gmail.com Santosh Kumar P.N, Electrical & Electronics Engineering department, SDM Institute of Technology, Ujire, D.K., India, affiliate to Visvesvaraya Technological University, Belagavi, Karnataka. scale of range 1kW-50kW power generation. And, these are connected to satisfy the consumer load demand in electric power distribution system. The proposed optimization technique is made to place DG unit suitably in reducing system power losses and to enhancing voltage magnitude. In this proposed work, DG placement is found by voltage sensitivity factor by meta-heuristic technique. From this, the priority is made for all busses and is arranged in descending form. The most sensitive locations are identified and chosen for locating DG in system. The results obtained from proposed optimization have enhanced the convergence rate and execution time. Zhu, et.al [1] considers two aspects for optimal insertion of DG for time varying loads i.e., to achieve higher reliability and to minimize losses. Willis [2] elucidated analytical methods and thumb rules method in evaluating the ODGP. The two methods “zero point analysis” and “2/3 rule are used. This method is employed for loss reduction, voltage effects and for uniform load services. Parizad et.al [3] described two outline of ODGP. The first outcome gives the reduction of system losses. Secondly, stability index is taken for optimal placement. Two line stability index is used to improve power transfer capability. It uses branch-current to bus-voltage (BCBV) and bus-injection to branch-current (BIBC) matrices. Caisheng Wang, M. Hashem Nehrir [4], describes the analytical approach for DG unit allocation to improve the performance. Rau and Wan [5] have described a technique for optimum allocation of DG in mesh network for enhancing the potential. Thereby, reducing network loss, reactive power requirement and line loadings. Payyala and Green [6] explain the method of merging techno-economic assessment of biomass-fuelled generators. It focuses on optimum size and placement based on technical and economic conditions. Khattam et.al [7] have analyzed Monte Carlo power flow algorithm which combines the stochastic and deterministic features of DG. The algorithm includes unreliability of both the location and on or off state of DG using Newton raphson method of load flow. Khanabadi, Doostizadeh et.al, [8] proposed optimum sitting and seizing of DG to eliminate clogging of power system using AC optimal power flow (ACOPF) along with binary variables and elucidated by mixed integer programming. Hybrid Optimization for Optimal Distributed Generation Unit Placement in Radial Distribution System Somashekar D.P, Shekhappa G Ankaliki, Ananthapadmanabha T, Ramya N.S, Santosh Kumar P.N