The Human Aspect of Electric Grid Operation

Control room of grid operator ISO New England, Holyoke, Massachusetts Photo: © ISO New England

Control room of grid operator ISO New England, Holyoke, Massachusetts
Photo: © ISO New England

Extreme weather events, technical and human failure, or sabotage (e.g., with weapons of mass destruction), can disrupt human infrastructure and impact the electrical grid, provoking cascading failures or blackouts that can affect millions of people. In power grid simulation, the human failure probability has been mostly ignored. In a recently published paper, researchers from Fraunhofer CSE and MIT focus on what human intervention can accomplish to influence the recovery and the extension of blackouts. Read the paper abstract.

Simulating the electric grid

What policies should be enacted to ensure the stability of the grid in a crisis, such as a storm, or a malicious attack? And what kind of human intervention can help to stabilize the grid in such an event? In a recent study, the U.S. Department of Defense (Defense Thread Reduction Agency), the University of New Mexico (UNM), and scientists at Fraunhofer CSE researched which factors affect the stability of electric grids. As part of the study, the UNM simulated the physical grid, and Fraunhofer CSE provided data and an assessment as to how grid operator stress and incomplete and inaccurate information can affect grid stability. The results were integrated into the grid model developed by UNM.

What affects human performance in the grid operating room?

Dr. Joana Abreu, behavioral scientist at Fraunhofer CSE, and her team, applied a methodology, which was originally used to calculate the probability of human error in nuclear power plants. The SPAR-H methodology quantifies error probability by considering factors that influence the perception, processing and response to events, such as those in a grid operating room. The factors are: the amount of time that the operator has available to respond, fatigue, stress, stressors, level of complexity of the situation, level of experience and training, procedures, alarms, and work processes. The methodology incorporates variables that describe the cognitive status of the operator and variables describing the situation.

Studying actual grid incidents

In order to assess the circumstances of actual incidents in electric grid operation, Abreu interviewed operators and asked them to illustrate a timeline, identify key decisions they made, and consequences. To document the effects of distinct weather zones in outage reports, Abreu interviewed operators from two climate zones: New England and New Mexico. Each operator described one or more incidents that took place during a shift, including, for example, a power loss on an island, which is difficult to serve. In a next step, multipliers for each performance shaping condition, such as time available, level of complexity, level of experience, were assigned to the actions taken and/or decisions made by the operator. These multipliers reflect the error probability in performing an action or making a decision.

Calculating human error probability in crises

The researchers classified each narrated scenario according to a phase in a blackout – precursor, escalation, and cascading – and calculated the frequency of occurrence that is associated with factors like fatigue (fitness for duty), complexity, experience, along with their level of severity (e.g., unfit, moderate complexity, high experience) and created a probability distribution for the probable occurrence of those levels of severity for each factor. The resulting probability distribution was integrated into a dynamical model to simulate the stochastic progression of failures, which was developed in parallel by UNM. The introduction of the human error probability in this domain is innovative and complemented the UNM model for grid stability by including human factors into the model.

Previous research indicates that calculated human error probabilities significantly correlated with actual values with an average precision of 72%. Yet, as the researchers point out, more data is needed to more accurately represent error probability. They also point out that methods aiming at assessing human reliability rely on the subjective interpretation of experts about situations they did not directly observe, as well as on operators’ ability to narrate a past event objectively. In addition, the SPAR-H methodology could still be improved by considering the dependency between performance shaping factors, such as time available and stress.


The project is funded by a basic research grant of the Defense Threat Reduction Agency.

About author
Anne Williams is Fraunhofer CSE's Associate Marketing Manager. She works with the Center’s staff to foster CSE’s business relations and make its activities known to the public.
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