The need for energy has significantly increased in the world in recent years. Various research works were presented to develop Renewable Energy Sources (RESs) as green energy Distributed Generations (DGs) to satisfy this demand. In addition, alleviating environmental problems caused by utilizing conventional power plants is diminished by these renewable sources. The optimal location and size of the DG-RESs significantly affect the performance of Radial Distribution Systems (RDSs) through the fine bus voltage profile, senior power quality, low power losses, and high efficiency. This paper investigates the use of PV (photovoltaic) and (Wind Turbine) WT systems as a DG source in RDSs. This investigation is presented via the optimal location and size of the PV and WT systems, which are the most used DG sources. This optimization problem aims to maximize system efficiency by minimizing power losses and improving both voltage profile and power quality using White Shark Optimization (WSO). This algorithm emulates the attitude of great white sharks when foraging using their senses of hearing and smell. It confirms the balance between exploration and exploitation to discover optimization that is considered as the main advantage of this approach in attaining the global minimum. To assess the suggested approach, three common RDSs are utilized, namely, IEEE 33, 69, and 85 node systems. The results prove that the applied WSO approach can find the best location and size of the RESs to reduce power loss, ameliorate the voltage profile, and outlast other recent strategies. Adding more units provides a high percentage of reducing losses by at least 93.52% in case of WTs, rather than 52.267% in the case of PVs. Additionally, the annual saving increased to USD 74,371.97, USD 82,127.257, and USD 86,731.16 with PV penetration, while it reached USD 104,872.96, USD 116,136.57, and USD 155,184.893 with WT penetration for the 33, 69, and 85 nodes, respectively. In addition, a considerable enhancement in the voltage profiles with the growth of PV and WT units was confirmed. The ability of the suggested WSO for feasible implementation was validated and inspected by preserving the restrictions and working constraints.

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Power flow is the backbone for power system operation and control. Power system balancing, where supply of energy has to equal demand all time, is a very important operation constraint for electric power systems. In recent years, penetration of Distributed Energy Resources (DERs) especially Renewable Energy Sources (RESs) into the distribution system has increased. RESs are known by their intermittent behavior in nature. Hence, as the number of these RESs increases, the sudden frequent change in power flow increases. Therefore, new obstacles to the operation and control of power systems arise. Power distribution system is also sparse and large system. Moreover, most traditional power flow solutions are based on iterative techniques which obviously take time. Therefore, computation time is a real problem when finding power flow solutions at distribution system especially with the unpredictability of RESs. To overcome these problems, a real-time linearized three-phase AC Power Flow (ACPF) model at distribution system is proposed. In this paper the linearized ACPF at distribution system is molded as follows. First Quasi linearized ACPF equations are developed for short period of time based on Newton’s Raphson (NR) method. Second sparse reordering algorithm techniques are used to reorder the node numbering of the power distribution system to reduce computational time. Then, simulation on IEEE 4 bus power system and IEEE 37 bus power distribution system are presented to validate the proposed model. Furthermore, Monte Carlo simulation is used to test the robustness of the proposed model.