Enabling Computing Techniques for Wide-Area Power System Applications
Creators: 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
Publisher: name: IEEE
Year: 2022

Power systems are undergoing unprecedented changes. The replacement of<br />large conventional power plants with dispersed renewable power<br />generators connected to both transmission and distribution grids,<br />changes in the consumption of energy, the expectation of improved system<br />security and resiliency and increasing reliance on automated systems all<br />have a considerable impact on the day-to-day operation of the electrical<br />grid.<br /><br />Increasing uncertainty levels are one of the most tangible consequences<br />of these changes: the randomness of renewable energy sources, the<br />complex electricity market price dynamics and the uncertain load<br />behaviour represent some of the most challenging issues to be addressed<br />by system operators. These complex and correlated uncertainties directly<br />affect real-time grid operation, which, due to the reduction of power<br />system inertia caused by the replacement of large rotating generators<br />with distributed inverter-based renewable power generators, is becoming<br />more vulnerable to dynamic perturbations.<br /><br />Moreover, the data streaming acquired by the distributed grid sensors<br />cannot provide power system operators, who must perform intensive<br />numerical computations aimed at enhancing situational awareness, with<br />the necessary measures and alerts to adjust the system to, e.g., prevent<br />severe grid perturbations or mitigate the impacts of multiple<br />contingencies.<br /><br />To overcome these limitations, researchers and designers of<br />high-performance power system computing systems are revisiting numerous<br />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<br />will analyze the most promising enabling technologies, which include<br />pervasive communication systems based on resilient and self-healing<br />architectures, wide-area monitoring systems based on synchronized<br />measurement devices, data mining-based techniques for knowledge<br />discovery from sensors data-streams and computational intelligence-based<br />tools for real-time decision making. The advances in these technologies<br />for the development of enhanced power system operations tools include<br />Wide Area Monitoring Protection and Control Systems (WAMPACs), which<br />enable system-wide data processing for the purpose of improving<br />situational awareness, mitigating the impacts of large disturbances and<br />reducing the probability of catastrophic events.