An Optimal power flow algorithm to reduce power loss by placement of DG in distribution system

Abstract

Distributed generation is a small-scale and renewable-based energy source (ex: solar/ wind/ biomass) near to loads in distribution networks. It is becoming more prominent in the present world due to incremental demands for electricity. The integration of DGs in the distribution system issprofitable, loss reduction and voltage-profile improvement if it is optimally sized and optimally placed. Research work included in this thesis focuses on using aneoptimization methodology for identifying the most appropriate locationaand size ofaDG. Initially, detailed study of optimal DG planning was carried regarding objective functions, constraints, load and design variables, and mathematical approaches. In this dissertation, a novel combined methodology for optimal DG planning is presented by Newton Raphson’s (NR) power-flow solution andeoptimization algorithm named ParticleeSwarm Optimization(PSO). A multi-objective function has been modified by considering real and reactive power loss minimization and cost minimization to attainethe optimal size and optimal location of DGs. Moreover, voltage-profile improvement and power systemestability improvements are obtained. The performance of theeproposed methodology is testedron the IEEE-30 busesystem and program is developed and simulated from MATLAB software. Two types of DGs are evaluated using the proposed model which is called a single DG source delivering only realpower and a single DG source delivering both realeand reactiveapower. The methoddis executed on the same 30-test bus systemefor different weighting factors. Resultsain theatest bus systemashow the effectiveness of the developed mathematical model with higher power loss reduction and cost reduction percentages. Furthermore, the proposed methodology is applied to select two distribution feeders in Sri Lanka with time-varying loads to allocate solar PV and biomass as DGs. In order to have a techno-economic solution for optimal size of DG and best location, the proposed algorithm can be used on any MV distribution feeder providing relevant line and load details.