In a world increasingly reliant on electricity, power outages can bring daily life to a grinding halt. However, an innovative research by Chaudhry Talha Hassan and Dr Tariq Mahmood Jadoon from the Department of Electrical Engineering significantly accelerated the restoration of electric power after a major blackout by improving the resilience of smart grids. These grids integrate many distributed energy resources (DERs) such as solar panels, wind turbines and energy storage systems.
Shortly, after the study's publication in IEEE Xplore in August 2023, Sir Ganga Ram Hospital in Lahore experienced a power outage due to alleged mismanagement, forcing doctors to use torchlight to complete their procedures. A similar incident had occurred at Services Hospital Lahore less than a month earlier, impeding patient care. More recently, during the Sindh flash floods, the preservation of the Guddu power station played a crucial role in preventing a blackout that could have impacted 25% of Pakistan's population.  These recurrent incidents underscore the timeliness of this research, where critical loads in a distribution feeder can be restored by harnessing power from neighboring DERs considering the power network as a cyber-physical power system.   
When an entire city or neighborhood experiences an abrupt power loss, the urgency to restore electricity to critical facilities such as hospitals and emergency services is paramount. Bulk power distribution networks typically have a limited number of switchable lines and loads. This limitation can make it challenging to restore power, particularly in situations where many inductive loads are switched on simultaneously. 
This is where the innovative concept of "microgrids" comes into play. The researchers have proposed the creation of these smaller, self-sustaining power networks that can swiftly bring power back to affected areas. Unlike the conventional top-to-bottom approach, the research emphasizes harnessing smart grids, using communication tech, reconfiguring networks, and integrating DERs. This ensures the rapid restoration of power to critical loads while addressing challenges like frequency control and practical factors such as switch types and communication constraints.
Inverter-dominated smart grids face unique challenges related to dynamic stability and lower inertia. The research introduces a multi-layered framework that integrates cyber-networks into the restoration process. It also emphasises the importance of monitoring the health of energy storage systems, ensuring safe charging and discharging strategies, and imposing constraints on frequency and voltage to maintain grid stability.
Moreover, the act of restoring power can sometimes introduce problems like system overload. To mitigate these potential issues, the study incorporates dynamic stability constraints into the restoration process, ensuring that the system remains stable even during the reconnection of numerous power sources.
To validate their concepts, the researchers employed computer simulations. These simulations create a virtual representation of the power system, allowing the team to experiment with different strategies without affecting the actual electricity supply.

The research sheds light on the crucial role of synchronous generators as black-start distributed generators (DGs) for service restoration. Unlike renewable energy sources, high-inertia diesel generators can provide reliable power during emergencies. By including backup generators (BUGs) as dispatchable DGs in microgrids, the research demonstrates an innovative approach to harnessing power from non-dispatchable sources, enhancing microgrid stability, and expanding coverage.
Talha's research promises a more efficient and resilient future for power restoration. By harnessing the power of microgrids and cyber-physical systems, this approach promises to revolutionise how we think about restoring electricity in the face of adversity. As our world increasingly relies on electricity, innovations like these are essential for ensuring that the lights stay on even when the grid faces its darkest hours.