Summary
Within the context of power grids, inertia is observed to be approximately constant over time, thereby contributing to the stability of the grid. However, as the share of renewable energy sources in the grid increases, the inertia associated with synchronous generators decreases, which has been shown to pose a threat to overall stability. In the context of modern power grids, the increasing share of renewable energy sources reduces system inertia, threatening overall stability and necessitating robust restoration strategies. This paper proposes a novel optimal restoration scheme utilizing a Multi-Objective Genetic Algorithm (MOGA) to address partial or complete blackouts. The study focuses on establishing an optimal schedule for Black Start
Read more Read less(BS) units to energize Non-Black Start (NBS) units and prioritizing critical loads through optimal transmission path selection. The primary objective is to minimize total restoration time and unserved load while restricting the number of switching actions. The proposed allocation model rigorously incorporates grid constraints, including active power balance, reactive power support, and voltage limits. Validated on the New England 10-unit 39-bus system, the algorithm considers node topological importance and line weights to optimize the backbone network.
Simulation results confirm that the proposed strategy generates a feasible, reliable, and expeditious restoration plan suitable for integration into real-time transmission system operation tools.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | C2_11686_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | Turkiye |
| Study committees | |
| File size | 838 KB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
CARLAK Hamza Feza - Akdeniz University; KAYAR Ergin - Turkish Electricity Transmission Corporation
Keywords
Black Start (BS), Genetic Algorithm (GA), Blackout, System Restoration Plan
