Enabling Computing Techniques for Wide-Area Power System Applications (TR94)

11 Feb 2022
Amedeo Andreotti, University of Naples Federico II, Italy Guido Coletta, Ricerca Sistemi Energetici RSE, Italy Adam J. Collin, University of Campania, Italy Fabrizio De Caro, University of Sannio, Italy Mohammad Dolatabadi, Valie Asr University, Iran Aristides Kiprakis, University of Edinburgh, United Kingdom Loi Lei Lai, Guangdong University of Technology, China Massimo Panella, University of Rome La Sapienza, Italy, Khmaies Ouahada, University of Johannesburg, South Africa, Marjan Popov, TU Delft, Netherlands, Pierluigi Siano, University of Salerno, Italy , Chun Sing Lai, Brunel University London, United Kingdom, Sr?an Skok, University North, Croatia, Vladimir Terzija, Skolkovo Institute of Science and Technology, Russia, Stefania Tomasiello, University of Tartu, Estonia, Luigi Troiano, University of Salerno, Italy, Domenico Villacci, University of Sannio, Italy, Ahmed F. Zobaa, Brunel University London, United Kingdom
Primary Committee:
Power System Operation, Planning and Economics Committee (PSOPE)
Sponsored by:
Technologies and Innovation Subcommittee
Chair: Alfredo Vaccaro, University of Sannio, Italy, Vice Chair: Sasa Djokic, University of Edinburgh, United Kingdom, Secretary: Antonio Pepiciello, University of Sannio, Italy
Video Length / Slide Count:
Pages: 41
Power systems are undergoing unprecedented changes. The replacement of
large conventional power plants with dispersed renewable power
generators connected to both transmission and distribution grids,
changes in the consumption of energy, the expectation of improved system
security and resiliency and increasing reliance on automated systems all
have a considerable impact on the day-to-day operation of the electrical

Increasing uncertainty levels are one of the most tangible consequences
of these changes: the randomness of renewable energy sources, the
complex electricity market price dynamics and the uncertain load
behaviour represent some of the most challenging issues to be addressed
by system operators. These complex and correlated uncertainties directly
affect real-time grid operation, which, due to the reduction of power
system inertia caused by the replacement of large rotating generators
with distributed inverter-based renewable power generators, is becoming
more vulnerable to dynamic perturbations.

Moreover, the data streaming acquired by the distributed grid sensors
cannot provide power system operators, who must perform intensive
numerical computations aimed at enhancing situational awareness, with
the necessary measures and alerts to adjust the system to, e.g., prevent
severe grid perturbations or mitigate the impacts of multiple

To overcome these limitations, researchers and designers of
high-performance power system computing systems are revisiting numerous
design issues and assumptions pertaining to scale, reliability, heterogeneity and manageability of real-time power system monitoring, protection and control systems. In this context, this technical report
will analyze the most promising enabling technologies, which include
pervasive communication systems based on resilient and self-healing
architectures, wide-area monitoring systems based on synchronized
measurement devices, data mining-based techniques for knowledge
discovery from sensors data-streams and computational intelligence-based
tools for real-time decision making. The advances in these technologies
for the development of enhanced power system operations tools include
Wide Area Monitoring Protection and Control Systems (WAMPACs), which
enable system-wide data processing for the purpose of improving
situational awareness, mitigating the impacts of large disturbances and
reducing the probability of catastrophic events.

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