Power quality (PQ) is a matter of importance and concern in today's world. It has become paramount with the appearance in recent years of electronic consumer devices that distortions in the power grid be minimized. The use of electronic power equipment has increased fast, which is leading to various problems of PQ. The voltage swells and sags are the major (PQ) problems affecting industrial consumers. The best method to overcome these problems is through the use of custom power devices. The solution to this problem may be implemented using force devices, one example of which is known as a Dynamic Voltage Restorer (DVR), a device that is generally useful and efficient for power devices in electrical distribution grids. They have a fast, dynamic response for any disturbance and they are smaller size and lower in cost. In this paper, DVR modeling and analysis has been carried out using the MATLAB simulation program, a Proportional-Integrator (PI) controller with application of Pulse Width Modulation (PWM).

The stability of global economies relies heavily on power systems (PS) that have sufficient operating reserves. When these reserves are insufficient, power systems become vulnerable to issues such as load shedding or complete blackouts. Maintaining grid stability becomes even more challenging with a high penetration of renewable energy sources (RES). However, RES, connected through power electronic devices, offer significant potential as ancillary service (AS) sources. Renewable energy-based microgrids (MG), which aggregate various RES resources and have substantial load control potential, further enhance the capability of AS provision from RES. The presence of diverse AS resources raises the question of how to dispatch ancillary service signals optimally to all resources. Most of the previous research work related to AS allocation relied on single-bus MG models. This paper proposes a detailed MG model for the optimal dispatching of ASs among the resources using Virtual Load, along with an optimization procedure to achieve the best results. The model incorporates voltage profiles and power losses for AS dispatching, and a comparative analysis is conducted to quantify the significance of grid modeling. The model and proposed procedure are tested using the CIGRE microgrid benchmark model. The results indicate that detailed modeling of MG can impact the results by 11%, compared to single-bus modeling, which qualifies detailed MG modeling for all future research work and shows the impact that modeling can have on technical and economic indicators of MG operation.