Toward a Resilient Smart Grid for a Smart City - Defensive Scheme of Network Failure by Extreme Weather Events

Ms. Liping Huang, Dr. Hao-Tian Zhang and Dr. Chun Sing Lai


Enhancing the resilience of power grids to high-impact, low-probability events, such as extreme weather event due climate change, is of great important for constructing a smart grid and a smart city. Compared with expensive and high-cost power infrastructures hardening strategies, the economic smart control and operation strategies are easier to implement and welcome by power producers and consumers. This letter introduced a smart grid techniques-based defensive scheme of network failure by natural disaster, which have three layers, including information collection layer, component fault probability assessment layer and coordinating and decision system. As a result of information technology advancement and its deep integration with the electric power industry, smart grid techniques play an essential role in power system resilience enhancement. A resilient and smart grid forms a solid foundation to build a smart city.


Due to climate change and global warming, extreme weather events, such as hurricanes, ice storms, floods, droughts, and so on, have become more intense in recent decades and their degree and strength are growing. As a result, electrical power systems increasingly suffer more severe “attacks” from these extreme weather events, leading to major power outages, such as blackout   [1] . Between 2003 and 2012, about 679 power outages, each affecting at least 50000 customers, occurred in the U.S. due to weather events [2] . Current existing power grids have been traditionally designed to have high reliability to deal with known and credible threats but not strong and smart enough to withstand extreme weather events due to the low frequency of extreme weather events in the past and expensive construction cost. However, it is becoming more and more apparent that further considerations beyond the classical reliability-oriented view are needed to keep the lights on  [3] . A smart grid which not only can maintain high levels of performance under the most common disturbances but also is resilient to much less frequent disasters is needed to support the realization of a smart city. The resilience of a power grid with respect to extreme events is considered one of the key features of the smart grid by U.S. Department of Energy (DOE).

Resilience was first defined by C. S. Holling [4]  as a measure of “the persistence of an ecological system and of its ability to absorb change and disturbance and still maintain the same relationships between populations or state variables.” Based on this foundation definition, the concept of resilience has evolved in several different disciplines, such as safety management, social psychology, power systems and so on. Despite the minor difference between their detail definitions, the concept of resilience in any discipline can be generally approached as the ability of a system to anticipate and withstand external shocks, bounce back to its pre-shock state as quickly as possible and adapt to be better prepared to future catastrophic events [3]. A resilient smart grid, in detail, should be able to avoid severe damages to the critical power infrastructure caused by extreme events and to restore as much load as possible in a short time after major outage, and, in addition, to adopt lessons for adapting its operation and structure for preventing or mitigating the impact of similar events in the future  [5] .

How to build a resilient smart grid?

Approaches to resilient smart power grids mainly fall into two categories, i.e. critical power infrastructures hardening/reinforcement measures and smart control/operation measures.

Critical power infrastructure hardening measures are actions that make the power system less vulnerable to extreme events and improve the ability of power infrastructures to ride through high-intensity winds, heavy ice storms, and other extreme weather events. Some examples of network and component hardening strategies are given below [3] 

  • Replacing overhead transmission and distribution lines with underground cables;
  • Upgrading poles and tower with stronger, more robust materials;
  • Elevating substations;
  • Relocating facilities to areas less prone to extreme weather;
  • Rerouting transmission lines to areas less affected by weather;
  • Redundant transmission routes;
  • Vegetation management;

These measures can make the grid stronger enough to defend against the natural disaster to a great extent, however, due to the high construction cost and extra land expropriation problems, many power utilities are reluctant to take infrastructure hardening measures.

In contrast, compared with construction programs, smart control/operation measures are easier to implement and welcome by power producers and consumers. Smart control/operation measures refer to the actions that to provide the power systems with control capacity and solutions/regulations that can direct staffs of power utility or power consumers consciously prevent attacks of the power system from extreme weather events. A defensive scheme against network failure by extreme weather events would be an effective approach.

A general system defensive method currently used by many power utilities usually consists of three steps, i.e. obtaining the anticipated failure rate of the facility, processing security, and stability analysis and providing control solutions to decision makers. However, because the anticipated failure rate of the power facility is generated by historical data, the failure rate is often fixed and has no relation to the external variation natural disaster. As a result, the facility failure rate may not be accurate enough, leading to a false response solutions.

To address the above issues, smart grid techniques based defensive scheme of network failure by natural disaster is proposed. The scheme has three layers. The first one is the information collection layer. Static information, such as network parameters and basic application data, and dynamic information, such as load flow data and weather information, are read in the first layer. The second layer is fault probability assessment, including failure rate assessment of individual natural disaster and multiple disasters and fault probability assessment of electricity component, for example, fault probability assessment of distribution feeders. The third layer is a coordinated defense system, which is in response to risk assessment and providing control method to those affecting security and stability failures.  

The proposed defensive scheme to improve power system resilience can be achieved on the premise of the development of smart grid techniques. Smart grid techniques play an essential role in a resilient grid. Smart grid infrastructures include advanced metering infrastructure (AMI), remote-controlled switches /transformers / voltage regulators, telecommunications, data management, and distribution/outage management system (DMS/OMS). These facilities enable real-time monitoring and remote control and enhance visibility and controllability of power systems. Smart grid applications, such as fault location, isolation, and service restoration (FLISR), enable online analysis and intelligent decision making for distribution systems. FLISR can locate and isolate the faulted zone and implement service restoration schemes as a decision support tool for distribution system operators [1]. Making use of DERs to serve critical loads during extreme events is also considered as a smart grid technique that contributes to resiliency.


A resilient and smart grid that enables to provide sustainable, economic and efficient electricity supply is a fundamental support and needed for building a smart city. As a result of information technology advancement and its deep integration with the electric power industry, smart grid forms a solid foundation to build a smart city. Meanwhile, the construction of smart city will also greatly stimulate the enormous potential of the smart grid. Decision makers must be fully aware of the potential of the smart grid so that the smart urban construction can play an important role. It is expected that with the continuous advancement of technology, smart grid and smart city construction will mutually promote and facilitate each other.


[1]        Y. Xu, C. Liu, K. P. Schneider, and D. T. Ton, "Toward a resilient distribution system," 2015 IEEE Power & Energy Society General Meeting, Denver, CO, 2015, pp. 1-5.

[2]        Y. Wang, C. Chen, J. Wang, and R. Baldick, "Research on Resilience of Power Systems Under Natural Disasters—A Review," IEEE Transactions on Power Systems, vol. 31, no. 2, pp. 1604-1613, Mar. 2016.

[3]        M. Panteli and P. Mancarella, "The Grid: Stronger, Bigger, Smarter?: Presenting a Conceptual Framework of Power System Resilience," IEEE Power and Energy Magazine, vol. 13, no. 3, pp. 58-66, May-June 2015.

[4]        C.S. Holling, “Resilience and Stability of Ecological Systems,” Annual Review of Ecology & Systematics, vol.4, no. 4, pp. 1-23, 1973.


[5]        Y. Wang, L. Huang, M. Shahidehpour, L. L. Lai, H. Yuan, and F. Y. Xu, "Resilience-Constrained Hourly Unit Commitment in Electricity Grids," IEEE Transactions on Power Systems, vol. 33, no. 5, pp. 5604-5614, Sept. 2018.  


 Ms Liping Huang, IEEE Member, is working towards her PhD at Guangdong University of Technology. Her research interests are in energy models, power system operation and control. 

 Dr Hao-Tian Zhang, IEEE Member, is now a project manager with State Grid Electric Power Research Institute (NARI Group). He graduated from the University of London, City and received his Ph.D. degrees in power system in 2014. His research interests are in the field of smart grid implementation and applications, renewable energy grid integration, big data processing and decision support systems.

Dr Chun Sing Lai (S’11, M’19) received the B.Eng. (1st Hons.) in electrical and electronic engineering from Brunel University London, U.K. and D.Phil. in engineering science from University of Oxford, U.K. in 2013 and 2019 respectively. He is currently an EPSRC Research Fellow with the School of Civil Engineering, University of Leeds and also a Visiting Research Fellow with the School of Automation, Guangdong University of Technology, China. He is Secretary of the IEEE Smart Cities Publications Committee. He organized the IEEE SMC Workshop on Smart Grid and Smart City, SMC 2017 in Canada. His current interests are in data analytics and energy economics for renewable energy and storage systems.


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