Innovative smart grid control technologies

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

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Application of advanced communication and control technologies for smart grid : a comprehensive review

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.13704 ◽

2018 ◽

Vol 7 (3) ◽

pp. 1514

Author(s):

S Surender Reddy

Keyword(s):

Smart Grid ◽

Real Time ◽

Frequency Control ◽

Security Measures ◽

Contingency Analysis ◽

Measuring Device ◽

Comprehensive Review ◽

Communication Techniques ◽

Control Command ◽

Control Technologies

This paper presents a comprehensive review of advanced control and communication technologies of smart grid (SG). Various func-tions/features of SG include real-time pricing, voltage/VAr control, frequency control, power quality, demand response management, distri-bution system restoration, and reconfiguration, distributed generation dispatch and storage. There is a strong requirement to control these functions, as well as to communicate within themselves. Suppose, if two-way communication is not possible then it cannot be considered as a function of SG. When trying to track or monitor a function, one must be able to control, command, and communicate with it. In order to control observation ability and measure of some type of numerical quantity that is obtained from a real time measuring device being moni-tored is necessary. Some of these measurable quantities are: overvoltage limits, security measures and contingency analysis. This paper addresses various challenges of control and communication techniques of SG.

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Multi-agent systems’ asset for smart grid applications

Computer Science and Information Systems ◽

10.2298/csis130224072r ◽

2013 ◽

Vol 10 (4) ◽

pp. 1799-1822 ◽

Cited By ~ 15

Author(s):

Gregor Rohbogner ◽

Ulf Hahnel ◽

Pascal Benoit ◽

Simon Fey

Keyword(s):

Smart Grid ◽

Smart Grids ◽

Distributed Networks ◽

Multi Agent Systems ◽

Agent Systems ◽

Grid Environments ◽

Control Concept ◽

Multi Agent ◽

Grid Applications ◽

Control Technologies

Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term ?agent? exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning systems, and agents. Further, we review most recent smart grid projects, and contrast their interpretations with our understanding of agents and multi-agent systems. We point out that multi-agent systems applied in the smart grid can add value when they are understood as fully distributed networks of control entities embedded in dynamic grid environments; able to operate in a cooperative manner and to automatically (re-)configure themselves.

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