The set-up for a new electrical system for variable renewable energy resources (RERs) will bring additional capital costs and therefore upgradation of the existing systems is by far the best option to ensure little to no greenhouse gases (GHGs) or harmful pollutants. This paper reports advanced power electronic converter-based devices (PECs) which play a crucial role in conversion and control activities in connecting RERs to power grids they cannot only bypass the associated challenges but can also be an efficient and potential equipment in power and energy sector. The interfacing of PECs with RERs is explored in this work is powered by an advanced framework in which smart inverters (SIs) are also utilized to maintain the regulated output voltage in line with the grid requirement and the effectiveness of the developed system is verified on MATLAB environment. The capabilities of SIs are emphasized which ranges from enhanced coordination between the devices, better efficiency and seamless integration of renewables with the utility grid to ensure holistic operation. A detailed analysis is performed and the outcomes reveal the suitability and applicability of the proposed work and in particular, interfacing PECs with the utility grid not only improves the performance of the system but also increases efficiency and limits the challenges associated with the integration of renewables in the mainstream grid to a considerable extent. The peak voltage of 300 V is produced by employing SIs from solar PV system which corresponds to an RMS voltage of 212.13 V within the permissible frequency range.

In this paper, an Adaptive Quantum-inspired Evolutionary Algorithm (AQiEA) has been applied for minimizing the power losses in the distribution network by suitable placement, sizing and subsequent allocation of load on Distributed Generators (DG) for a varying load with a time horizon of twentyfour hours. Many efforts have been reported in the literature to minimize power losses. However, they have mostly used a fixed load, i.e., nonvarying load, whereas it is well known that load in distribution network varies during the day. An investigation was undertaken to find the reduction in power losses on a timevarying load. It has been found that the average power losses for dynamic load allocation on DGs for every hour have a maximum reduction in power loss as compared with other well-known cases in the literature. Optimal location and size of DG is a difficult nonlinear, non-differentiable combinatorial optimization problem. AQiEA is used to find the appropriate location and capacity of DG for a varying load with a time horizon of twenty-four hours to minimize the power losses. AQiEA doesn?t require additional operators like local search and mutation to improve the convergence rate and avoid the premature convergence. A Quantum Rotation inspired Adaptive Crossover operator is used as a variation operator, which is parameter free. The effectiveness of AQiEA is demonstrated on two test bus systems viz., 33 bus system and 69 bus system, which are used as benchmark problems for validating the proposed methodology as well as for comparative testing amongst existing techniques. Wilcoxon signed rank test is also used to demonstrate the effectiveness of AQiEA. The experimental results show that AQiEA has better performance as compared to some existing ?state of art? techniques.