Assessing the Impact of Size and Site of Distributed Generations and Smart Meters in Active Distribution Networks for Energy Losses Cost

Many approaches have been applied to study the capacity of distributed generation (DG). One aspect missing from existing methods is the capability to efficiently adaptive power factor (APF) of DGs to power system problems. Hence, this paper proposes a methodology for simultaneous allocation of DGs and smart meters (SMs) in active distribution networks (ADNs) with adaptive power factor of DGs in order to minimize the cost of energy losses. Allocation of SMs in the promising (ADNs) would definitely affect the power system problems such as distributed generations (DGs) studies. SMs are taken into consideration for the sake of successful implementation of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. To overcome the minimum losses cost, the optimization procedure is tackled with genetic algorithm (GA) and tested thoroughly on IEEE 33-bus distribution test system. In this paper, a probabilistic load model is assumed instead of utilizing time-series based models. The results certify considerable effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting in the lowest value of energy losses as well.