Author:
Jesan Rodriges,Hassan Zahir
Abstract
Ensuring the provision of high-quality and dependable power supply to customers stands as a paramount responsibility within the realm of power systems. The concept of restructuring the power system emerges as an efficient approach to deliver economically viable and uninterrupted power supply. The assessment of power system reliability hinges on various factors, with the reliability index serving as a pivotal metric, dependent on both system security and adequacy. To enhance the reliability index, strategically locating FACTS devices becomes essential, a task facilitated through power flow analysis with specified constraints, pinpointing the weakest points through Genetic Algorithm-driven fast-acting device placement. The correlation between DG establishment and the reliability index was meticulously calculated, further bolstered by the introduction of a Derated Forced Outage Rate for enhanced performance assessment. In the pursuit of heightened power system reliability, sequential simulations prove invaluable, particularly in minimizing Expected Energy Not Supplied (EENS) and improving overall system reliability. The results obtained through sequential simulations underscore the effectiveness of this approach within bulk electrical systems. The installation of multiple FACTS devices in the system's weakest areas facilitated EENS computation, coupled with the assessment of related reliability indices such as system frequency and system duration. This approach not only enhances system reliability but also promotes the economic operation of both transmission and distribution.The simulation results substantiate the alignment of power system reliability objectives in deregulated power systems with the required standards, advocating for the restructuring of power networks. The reliability assessments, driven by the optimal placement of DGs and FACTS devices, reveal substantial improvements in system reliability, underscoring the pivotal role of these technologies in enhancing overall power system dependability.