One Man's Journey to the Self-Healing Grid
- Written by Massoud Amin
While developing mathematical models for keeping aloft individual aircraft, whole squadrons, or end-to-end systems for the U.S. DoD logistics networks after suffering damage, Massoud Amin, chairman of the IEEE Smart Grid Newsletter, discovered how power systems and interdependent coupled networks for fuel supply, energy and power, communication and energy markets could be retrofitted or designed to automatically stabilize and correct themselves. He carried those ideas first to the Electric Power Research Institute (EPRI) and then to the University of Minnesota, where he holds the Honeywell/H.W. Sweatt Chair in Technological Leadership.
Smart Grid Newsletter: What is the history behind the development and application of the self-healing concept?
Before moving to EPRI in January 1998, I worked for 14 years on several projects with NASA-Ames and McDonnell Douglas on control and stabilization of combat systems including a damaged F-15 aircraft. Even before receiving a doctorate in systems science and mathematics at Washington University in St. Louis, I worked on projects with the U.S. Department of Defense on a stabilization project for a Sikorsky helicopter, developing fast and accurate state estimators combined with robust adaptive controls. I also worked on developing intelligent navigation for low-observables in semi-autonomous or autonomous aircraft, which allows the aircraft to dynamically adjust itself to maintain zero/minimum detection paths to avoid enemy radar sites, carry out missions with high probability, to predict and counter enemy maneuvers if detected and safely return to home base. This work combined mathematical foundations of nonlinear dynamical complex systems, differential game theory, stochastic optimization, dynamic risk assessment and artificial intelligence combined with overlaid networks of sensing, secure communications and controls to achieve the desired objective.
In that early period, was there anything in particular that drew your attention to this subject?
Well, there was this rather dramatic incident in 1983 where an F-15 fighter flying over a friendly country lost over 90 percent of its right wing, which resulted not only in a loss of the aircraft’s control surfaces but also its symmetry. Nevertheless, by judiciously using the remaining control surfaces in combination with engine thrust and afterburners, the pilot was able to land the plane safely. In the aftermath, the very same aircraft was put through extensive wind tunnel tests at McDonnell Douglas (now Boeing) in St. Louis. But since childhood I had been fascinated with how resilient people conducted themselves during instabilities and stressors, achieving healthy survival, often with greater strength and success. The pilot’s fast effective response and resilience impressed me. My colleagues and I wondered if we could help save other pilots when their aircraft is damaged.
What were you doing at that time?
When I was at Washington University during the mid-late 1980s and 1990s, I worked on projects with McDonnell Douglas (now called Boeing Phantom Works), NASA-Ames Research Center and NASA Dryden Flight Research Center to develop a damage-adaptive Intelligent Flight Control System (IFCS). This work utilized on-line sensing, system estimation, communication and control technologies to predict the aircraft parameters and to continuously optimize the control system response. Our team designed the IFCS to provide consistent handling response to the pilot under normal conditions and during unforeseen damage or failure conditions to the aircraft. I also worked on projects for the U.S. Air Force to apply the same methods for the end-to-end large-scale military logistic systems.
So that work was not confined to the stabilization of individual aircraft?
No. As my work with R&D projects continued, I moved from studying the survival of single airplanes to the survival of squadrons and large-scale defense and civilian logistic networks for DoD’s Air Mobility Command and the U.S. Transportation Command. During this time I developed a full range of solutions—from theoretical foundations to real-world deployments—on how groups and networks can keep mission effectiveness when critical components like fueling or devices and crews go down.
While working on these projects I began to realize there’s an equally obvious need to strengthen and increase intelligence in the power grid. A grid operator is similar to a pilot flying an aircraft, monitoring how the system is being affected, how the “environment” is affecting it and having a solid sense of how to steer it in a stable fashion.
And so the power grid was increasingly the focus of your attention?
Yes. This work moved dramatically forward when I joined the Electric Power Research Institute (EPRI) in January 1998.
During the 1980s and 1990s, it provided the background for the creation, successful launch and management of research programs for the electric power industry, including the EPRI/DOD Complex Interactive Networks/Systems Initiative (CIN/SI), which involved six university research consortia, comprising 240 graduate students and 108 professors in 28 U.S. universities along with 52 utilities and ISOs and DoD. The goal of this project, which took place between 1998 and 2002, was to retrofit our nation’s interdependent critical infrastructures and to build integrated networks that were secure, robust and self-healing, by developing and deploying layers of secure sensing, high-confidence communications, and automation networks.
The vision was to transform the modernized end-to-end electric power system into a "smart grid" – an integrated, self-healing and electronically controlled secure and resilient power system.
Interdependent networks of fuel/water supply, end-to-end electric power systems, telecommunications and financial networked systems have a normal, undisturbed state and an alert model that senses precursors to an emergency state. When they are in an aggravated state they attempt to restore to a normal one. The key is to build systems that are simple and smart, that focus on security, reliability, robustness, efficiency and security. Security became even more important in the wake of 9/11, when the focus became on dynamic risk assessment, analyzing threats to these infrastructures.
The EPRI/DOD CIN/SI effort laid the foundation for several on-going initiatives in smart grids and self-healing infrastructures focusing on smart reconfigurable resilient networks. In the case of developing a self-healing power grid, the key components and tools included anticipation of disruptive events, look-ahead simulation capability, fast isolation and sectionalization; and adaptive islanding and self-healing restoration.
What is the architecture for the self-healing grid and how would it work?
By knowing how failures occur, assessing vulnerabilities and working out self-healing strategies, a holistic risk management, monitoring and control system can be designed and deployed. The resulting self-optimizing and self-healing system operates on three-tiered intelligence levels:
The bottom layer, closest to devices in the field, is distributed intelligence. It is akin to the reptilian brain, with simple responses to environmental stimuli. In the middle layer, validation of incoming data and coordination of various functions takes place in milliseconds; at a substation, for instance, an intelligent device monitors the health of the asset and communicates it to an automated control center. This layer is somewhat akin to a mammalian neo-cortex that can strategize, act and be upgraded through experience to higher functionality. The top layer contains the centralized command-and-control functions directed by human operators.
Because the system would be utilized by classes of users with differing needs and requirements—including top executives, business line leaders and operations managers—it would provide multiple levels of resolution: macro (the entire system), meso (for example, individual operation) and micro (such as, microgrids, subsystems, assets) to support full situational awareness and better decision making to reduce risks with actionable intelligence.
If organized in coordination with the internal structure existing in a complex infrastructure and with the physics specific to the components they control, these agents promise to provide effective local oversight and control without need of excessive communications, supervision, or initial programming. Indeed, they can be used even if a human’s understanding of the complex system in question is incomplete. These agents exist in every local subsystem and perform preprogrammed self-healing actions that require an immediate response. Such simple agents already are embedded in many systems today, such as circuit breakers and fuses as well as diagnostic routines. With this, we’ve observed we can account for precursors to low-probability and high-impact failures, how seemingly small and often appearing unrelated precursors to failure occur. With that capability we save the larger system from massive cascading failures while we automatically and rapidly localize, repair, restore and “self-heal” the system from micro- to macro-levels.
CIN/SI developed, among other things, a new vision for the integrated sensing, communications and control of the power grid. Some of the pertinent issues are why/how to develop controllers for centralized vs. decentralized control and issues involving adaptive operation and robustness to disturbances that include various types of failures. The technologies included, for example, the concept of self-healing electricity infrastructure, and the methodologies for fast look-ahead simulation and modeling, adaptive intelligent islanding and strategic power infrastructure protection systems are of special interest for improving grid security from all hazards, including equipment failures, human errors, terrorist attacks and natural disaster.
Given economic, societal and quality-of-life issues and the pivotal role of the electricity infrastructure, a self-healing grid is essential.