Enhanced Power System Restoration Through MILP Black Start Allocation Optimization

Abstract

Restoring a power system following a blackout is a critical undertaking, necessitating the efficient allocation of Black Start (BS) resources—generators capable of initiating without external power. This research introduces an innovative approach to address a critical challenge in power system restoration—optimal black start allocation. Efficient allocation of resources when power systems face blackouts is crucial for rapid restoration. Leveraging the power of Mixed Integer Linear Programming (MILP), this study formulates and solves the black start allocation problem with the primary objective of minimizing allocation costs, all while satisfying many operational constraints. These constraints include ensuring power supply meets demand, adhering to generator output limits and ramping rates, and enforcing time-bound generator startup decisions. Furthermore, it maintains power flow equilibrium and network stability through branch flow and voltage magnitude constraints. This research offers a promising solution to enhance the resilience and reliability of power systems by optimizing the allocation of black start resources. This would reduce downtime ultimately and mitigate the far-reaching impacts of blackouts on society and the economy.