The Distributed Generator types have different combinations of real and reactive power characteristics, which can affect the total power loss and the voltage support/control of the radial distribution networks (RDNs) in different ways. This paper investigates the impact of DG’s penetration level (PL) on the power loss and voltage profile of RDNs based on different DG types. The DG types are modeled depending on the real and reactive power they inject. The voltage profiles obtained under various circumstances were fairly compared using the voltage profile index (VPI), which assigns a single value to describe how well the voltages match the ideal voltage. Two novel effective power voltage stability indices were developed to select the most sensitive candidate buses for DG penetration. To assess the influence of the DG PL on the power loss and voltage profile, the sizes of the DG types were gradually raised on these candidate buses by 1% of the total load demand of the RDN. The method was applied to the IEEE 33-bus and 69-bus RDNs. A PL of 45–76% is achieved on the IEEE 33-bus and 48–55% penetration on the IEEE 69-bus without an increase in power loss. The VPI was improved with increasing PL of DG compared to the base case scenario.

The significance of Distributed Generators (DGs) in the technical and economic operations of electric power distribution systems cannot be overemphasized in recent times. This is essential as a result of the incessant increase in electrical energy demand, which is becoming considerably difficult to meet with the conventional means of energy supply. Thus, DGs offer better alternatives for providing a quality supply of energy near the site of consumption. This type of energy supply is cleaner and cheaper most of the time due to the lessened transmission losses, which consequently reduced the cost of operation at the transmission and distribution levels of the power system. In this work, an approach for placement and sizing of solar PV DGs into radial distribution networks (RDN) based on the solar PV capacity factor of the site was analyzed using particle swarm optimization. The aim of this study is to analyze the effect of the approach on the real and reactive power losses within the network as well as the bus voltage profile. Constraints on credible system operation parameters, which includes bus voltage limits, power balance, and power flow limits, are considered in the formulation of the optimization problem. In order to verify the viability of the deployed approach, steady-state performance analyses were executed on IEEE 33-bus RDN; and the results obtained were compared with the results from other approaches reported in the literature.

The optimal penetration of a Shunt Capacitor (SC) is one of the most economical means to enhance the efficiency of radial distribution networks (RDNs). This enhancement includes reducing power loss, and operating costs, improving voltage profiles, and enhancing stability. This paper introduces a constriction-factor Particle Swarm Optimization (Cf-PSO) for SC allocation problem. It leverages the equivalent reactive power voltage stability index (EQVSI) to narrow the search space of the initial Cf-PSO population. The proposed approach analyzes the optimal SC allocation for various scenarios: the base case before SC integration, one SC, two SCs, three SCs, and four SCs. The Cf-PSO technique was tested on the standard IEEE 33- and 69-bus RDNs. For these networks, allocating four SCs resulted in the most significant percentage reduction in power loss: 35.15 % for the IEEE 33-bus and 35.85 % for the IEEE 69-bus, compared to their respective base scenarios. The simulation results also demonstrate that as more SCs are optimally installed, the percentage reduction in power loss and the financial cost-benefit improve. However, beyond two SCs, the rate of improvement significantly diminishes, reaching a point where adding more SCs is no longer economically advantageous compared to the previous number. The power loss results obtained using this approach were validated by comparing them to established techniques found in the open literature, confirming their effectiveness in most cases.