News Release

Looking into the past to find the solution for managing future demand

Parallel dispatch: A new paradigm of electrical power system dispatch

Peer-Reviewed Publication

Chinese Association of Automation

The wisdom and experience of human power grid operators can play a key role in managing growing demand, according to a design proposed in the January 10th issue of IEEE/CAA Journal of Automatica Sinica, a joint bimonthly publication of the IEEE and the Chinese Association of Automation.

The demand for electricity is expected to double by 2030, according to Jun Jason Zhang, an assistant professor of Electrical and Computer Engineering at the University of Denver and an author on this paper. "Electrical power grids are in the transition from traditional power grids to modern smart grids to accommodate the rapid development of human society. Expansion of power generation and renovation of transmission and distribution infrastructures, which cause tremendous consumption of public resources, cannot be the only solution to this social requirement."

Zhang and his team proposed that a top level design of an intelligent dispatch system could assist in this transition. By incorporating artificial systems to run computational experiments based on input from real-world systems, the algorithms could run scenarios and find the best way to dispatch power quickly and efficiently.

"Modern power systems are evolving into socio-technical systems with massive complexity, whose real-time operation and dispatch go beyond human capability," Zhang wrote, explaining that historical experience is still valuable. "An important mission of intelligent power system dispatch is to convert system operators' experience, including historical operation actions in successful and failed dispatch, historical dispatch records, and related dispatch data into intelligent technical models."

By incorporating the historical records into a learning network that can create feedback to a physical system, the dispatch system becomes an intelligent organization capable of decision-making and automating knowledge.

"We expect that a new dispatch paradigm, namely the parallel dispatch, can be established by incorporating various intelligent technologies, especially the parallel intelligent technology, to enable secure operation of complex power grids, extend system operators' capabilities, suggest optimal dispatch strategies, and to provide decision-making recommendations according to power system operational goals."

Other contributors on this project include researchers from the Chinese Association of Automation, State Grid Tianjin Power Dispatching and Control Center in China, the department of electrical and computer engineering at the university of Denver, School of Automation Science and Electrical Engineering at Beihang University in Beijing, China, and the National Renewable Energy Laboratory in Colorado.

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Fulltext of the paper is available: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8232602

IEEE/CAA Journal of Automatica Sinica (JAS) is a joint publication of the Institute of Electrical and Electronics Engineers (IEEE) and the Chinese Association of Automation. The objective of JAS is high quality and rapid publication of articles, with a strong focus on new trends, original theoretical and experimental research and developments, emerging technologies, and industrial standards in automation. The coverage of JAS includes but is not limited to: Automatic control,Artificial intelligence and intelligent control, Systems theory and engineering, Pattern recognition and intelligent systems, Automation engineering and applications, Information processing and information systems, Network based automation, Robotics, Computer-aided technologies for automation systems, Sensing and measurement, Navigation, guidance, and control. JAS is indexed by IEEE, ESCI, EI, Inspec, Scopus, SCImago, CSCD, CNKI. We are pleased to announce the new 2016 CiteScore (released by Elsevier) is 2.16, ranking 26% among 211 publications in Control and System Engineering category.

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