Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement

This paper presents an implementation of the hybrid Cuckoo search and Grey wolf (CS-GWO) optimization algorithm for solving the problem of distribution network reconfiguration (DNR) and optimal location and sizing of distributed generations (DGs) simultaneously in radial distribution systems (RDSs). This algorithm is being used significantly to minimize the system power loss, voltage deviation at load buses and improve the voltage profile. When solving the high-dimensional datasets optimization problem using the GWO algorithm, it simply falls into an optimum local region. To enhance and strengthen the GWO algorithm searchability, CS algorithm is integrated to update the best three candidate solutions. This hybrid CS-GWO algorithm has a more substantial search capability to simultaneously find optimal candidate solutions for problem. Furthermore, to validate the effectiveness and performances of the proposed hybrid CS-GWO algorithm is being tested and evaluated for standard IEEE 33-bus and 69-bus RDSs by considering different scenarios

Stability Enhancement of DFIG Wind Farm Using SSSC With FOPID Controller

The wind power generation has become more important nowadays to meet the increase in power demand. DFIG based wind power generation is the recent and used in many countries due to its better power controllability. The controllers like Proportional Integral (PI) are used for the stabilization of the waveforms of the supply system. The change in controllers produces better oscillation damping in recent days. The effect of varying the wind input to generate power using the wind turbine resulting in instability in the power system because of the control is done on a grid supply. This paper aims to proposes an optimum FOPID controller for damping power system instability using a Static Synchronous Series Compensator (SSSC) system that takes into account the dynamics of wind energy conversion systems (WECS) connected to a infinite grid. The WECS model, which includes variations in wind supply to the wind turbine, has been developed to test the durability of the optimized controller that was developed to damping power system oscillations. The controller used to take the power system dynamics into account. A new controller is being designed to include a corrective measure for the damping the oscillations to adjust the instability caused by wind supply variations. The controller helps to tune the controller settings that lead to the achievement of the power oscillation damping objectives. These results are compared with conventional PMSM based wind turbine system

Optimal design, prefeasibility techno-economic and sensitivity analysis of off-grid hybrid renewable energy system

This work aims to find an optimal hybrid renewable system design using solar, wind energy, battery storage, thermal loads, thermal load controller (TLC), boiler, and a diesel generator (DG) for the considered site. The prefeasibility techno-economic analysis has been carried out using HOMER software to meet the load demand requirement of the village. For identifying winning system architecture, minimum net present cost (NPC), lowest cost of energy (COE), and the highest renewable fraction (RF) are used as the criteria. The obtained results show that the least cost-optimal hybrid system consists of 614kW-PV,850kW-WT,800kW-DG, 1212 no. of batteries and 591 kW converter along with TLC-2000kW, having minimum NPC: $5.48M, least COE:$0.272/kWh and highest RF:91.6% can provide 92% reliable power supply to onsite load demand of 4502.95kWh/day with 70% renewable sources in the considered site. This paper also presents a sensitivity analysis of the hybrid system with variations in load demand, diesel fuel price, project lifetime, and interest rate

Grey wolf optimisation algorithm for solving distribution network reconfiguration considering distributed generators simultaneously

This article represents an application of the grey wolf optimisation (GWO) algorithm to solve the most optimistic combinatorial problems for optimal distribution network reconfiguration (DNR) and allocation of distributed generators (DGs) in a system. In this work, a metaheuristics algorithm is utilised to minimise the active power losses (APL) and enhance the voltage profile. Various scenarios were considered in this context to compare the performance of the proposed algorithm under voltage and current capacity constraints. Furthermore, a detailed validation via comparison of the results is being carried out with other methods from the exhaustive literature. The proposed algorithm reduces the APL by 63.13%, 56.19%, and 34.27% with DNR in IEEE 33, 69 and 118-bus systems. Similarly, APL reduction by 69.61%, 82.09%, and 36.08% with DNR considering DGs simultaneously. The results show that the proposed algorithm is an effective and promising method to solve problems similar to this work