Optimal Power Flow Scheduling of Distributed Microgrid Systems Considering Backup Generators

Abstract

Due to the great renewable integration capability of Microgrids (MG), reliability, resiliency and stability improvement, MGs play a crucial role in the next generation of electrical power networks. Besides, MGs provide significant potential economic and environmental benefits. However, the intermittent nature of renewable sources necessitates utilising energy storage devices, which would impose new challenges to the energy management of MGs. This paper proposes a centralised optimal power flow controller to minimise the operation cost of distributed microgrid systems while satisfying the technical constraints, considering the battery energy storage depreciation, transmission losses, and dispatchable units' characteristics. Due to the extensive computational time required to solve the nonlinear optimisation problem, the distributed microgrid system is formulated as a Mixed Integer Linear Problem. To investigate the performance and functionality of the proposed approach, it is applied to an actual case study at Griffith University, consisting of four MGs. The obtained results confirm the cost-effectiveness and applicability of the proposed model and control approach.

Reviewing the impact of AI on renewable energy efficiency and management

“…They facilitate the management of intermittent renewable sources by providing real-time monitoring, control, and protection systems for grid stability (Salehi et al, 2012). Smart grids also offer the capability to smooth out the fluctuation and intermittency properties of renewables, thereby enhancing the reliability and power quality of the grid (Garmabdari et al, 2019). Additionally, smart meter data analytics provide valuable insights for addressing the challenges associated with renewable energy integration, by offering application-oriented reviews and identifying future research challenges (Victor and Great, 2021;Wang et al, 2019).…”