The optimum sizing ratio (Rs) between PV array and inverter were found equal to 0.928, 0.904, and 0.871 for 1 MW, 1.5 MW, and more than 2 MW, respectively, whereas the total power losses reached 8
Downloadable (with restrictions)! As the integration of solar photovoltaic (PV) power plants into distribution networks grows, quantifying the amount of PV power that distribution networks can
This study presents a multi-objective planning approach to optimally place open unified power quality conditioner (UPQC-O) by simultaneously optimising the photovoltaic (PV) hosting capacity (PVHC) and
The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for
In this review, the global status of the PV market, classification of the PV system, configurations of the grid-connected PV inverter, classification of various inverter types, and
The proposed methodology aims at searching for the optimal allocation of PVDGs with Volt/Var control based on AVR where hourly loading variations are considered. Therefore, the control variables are represented by
power of PV systems and therefore, keep the voltage level within the standard. In addition, this control can also be used to mitigate thermal capacity problems by adopting conservative set
A large number of photovoltaics (PVs) integration, without proper size and allocation throughout the distribution network (DN) The PVs are installed at the load bus in the given area. Note that in this study, PV
Optimal solar photovoltaic system locations and sizes in electrical distribution networks are derived using a novel Archimedes optimization algorithm in order to minimize network dependence and pollutant emissions to the greatest extent possible.
This paper proposes to resolve optimal solar photovoltaic (SPV) system locations and sizes in electrical distribution networks using a novel Archimedes optimization algorithm (AOA) inspired by physical principles in order to minimize network dependence and greenhouse gas (GHG) emissions to the greatest extent possible.
The grid dependency for actual power is 11.58%, which is lower than the grid dependency for uncompensated power, according to the optimal allocation of SPV systems with a total installed capacity of 715.39 kW. Table 3, which also includes results from the AOA research, has results from different heuristic search algorithms (HSAs).
Single-line diagram of particle 28-bus agriculture feeder. The optimal allocation of SPV systems can be solved for Scenario 1, which is the minimizing of only losses (i.e. F 1) at the 100% SPV IC level; and Scenario 2, which is the minimization of both losses and AVD at the 100% SPV IC level (i.e. F 2).
The appropriate allocation of SPV systems, it can be argued, resulted in a significant improvement in the voltage profile as a result of the optimization. Furthermore, the voltage profile of the network has become flatter, which is crucial for long-term stability.
The effective loading of the system is (75.564 kW + j 576.893 kVAr) as a result of the real power adjustment, and the grid dependency of the system for real power is ~12.27% lower than in the base scenario, as indicated in Fig. 7.
