Computational Intelligence in Smart Grids: Case Studies

2014 ◽  
pp. 265-292 ◽  
Author(s):  
Mohamed A. Abido ◽  
El-Sayed M. El-Alfy ◽  
Muhammad Sheraz
Keyword(s):  
Case Studies ◽  
Computational Intelligence ◽  
Smart Grids

Computational intelligence approaches and linear models in case studies of forecasting exchange rates

2007 ◽  
Vol 33 (4) ◽  
pp. 816-823 ◽  
Author(s):  
André Alves Portela Santos ◽  
Newton Carneiro Affonso da Costa ◽  
Leandro dos Santos Coelho
Keyword(s):  
Exchange Rates ◽  
Case Studies ◽  
Computational Intelligence ◽  
Linear Models

scholarly journals A case study research on interoperability improvement in Smart Grids: state-of-the-art and further opportunities

2021 ◽  
Vol 1 ◽  
pp. 33
Author(s):  
Johann Schütz ◽  
Mathias Uslar ◽  
Jürgen Meister
Keyword(s):  
Case Studies ◽  
Smart Grids ◽  
Large Scale ◽  
Critical Infrastructure ◽  
State Of The Art ◽  
Case Study Research ◽  
Efficient Integration ◽  
Cost Efficient ◽  
Theoretical Foundations

With the topic of Smart Grids taking up momentum, challenges to integrate systems from various vendors’ at large scale in a critical infrastructure have arisen. This issue is usually tackled utilizing standards and, therefore, agreements between the various parties. However, the aspect of the interoperability between systems is not only defined by physical connections, but has a multi-faceted dimension which needs to be dealt with at all layers in order for a semantic and cost-efficient integration. Within this contribution, we motivate the need for a procedural way to deal with interoperability in Smart Grids, show the theoretical foundations and the approach taken and present case studies that cover the problem in scope. Based on these case studies, results are critically reflected and conclusions are drawn.

Load Flow Analysis in Smart Grids

2019 ◽  
pp. 187-199
Author(s):  
Osman Hasan ◽  
Awais Mahmood ◽  
Syed Rafay Hasan
Keyword(s):  
Computational Intelligence ◽  
Smart Grids ◽  
Flow Analysis ◽  
Vital Role ◽  
Load Flow ◽  
Power Grids ◽  
Safety Critical ◽  
Load Flow Analysis ◽  
Comprehensive Survey ◽  
The Given

Load flow analysis is widely used to estimate the flow of various electrical parameters such as the voltage, current, and power in power grids. These estimates allow us to effectively and reliably manage the given grid under random and uncertain conditions. Given the enormous amount of randomness and uncertainties in the factors that affect the smart grids, compared to traditional power grids, a complete and rigorous load flow analysis holds a vital role in ensuring the reliability of this safety-critical domain. In this chapter, the authors describe smart grids in terms of their basic components and then categorize the factors that affect the loads in smart grids. This is followed by a comprehensive survey of various existing load flow analysis techniques (i.e., numerical, computational intelligence, and probabilistic).

Opening Address

2017 ◽  
Vol 21 (1) ◽  
pp. 8-8
Author(s):  
Editor: Prof. Yasufumi Takama ◽  
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Computational Intelligence ◽  
Smart Grids ◽  
Fuzzy Inference ◽  
Peer Review Process ◽  
Web Intelligence ◽  
The Past ◽  
Research Areas ◽  
Institute Of Technology

The JACIII was first published in 1997, and 2017 marks its 20th anniversary. During the last two decades, the research fields in computational intelligence have rapidly evolved owing to the spread of the Internet, performance improvement of computers, and accumulation of scientific knowledge. To celebrate this 20th anniversary, we have selected 6 important research areas from the JACIII scope, and invited outstanding researchers from each of these areas to contribute papers about the progress and major topics in those areas during the past 20 years. Submitted paper went through a peer-review process by distinguished professors to further improve the quality. The research areas selected were computational intelligence, fuzzy intelligence, intelligent robots, artificial intelligence and web intelligence, data mining, and smart grids. Each of those paper covers broad topics appeared in the research areas, from which readers could grasp what happened during the past 20 years. We also hope readers could find some hints about future directions of their own researches towards the next 20 years. <strong>Invited Paper 1: Computational Intelligence: Retrospection and Future</strong> Author: Witold Pedrycz (University of Alberta, Canada) <strong>Invited Paper 2: Fuzzy Inference: Its Past and Prospects</strong> Authors: Kiyohiko Uehara (Ibaraki University, Japan) and Kaoru Hirota (Beijing Institute of Technology, China) <strong>Invited Paper 3: Relationship Between Human and Robot in Nonverbal Communication</strong> Authors: Yukiko Nakagawa and Noriaki Nakagawa (RT Corporation, Japan) <strong>Invited Paper 4: Web Intelligence and Artificial Intelligence</strong> Author: Yasufumi Takama (Tokyo Metropolitan University, Japan) <strong>Invited Paper 5: A Review of Data Mining Techniques and Applications</strong> Authors: Ratchakoon Pruengkarn, Kok Wai Wong, and Chun Che Fung (Murdoch University, Australia) <strong>Invited Paper 6: Development and Current State of Smart Grids: A Review</strong> Author: Ken Nagasaka (Tokyo University of Agriculture and Technology, Japan)

scholarly journals Standards for Cyber-Physical Energy Systems—Two Case Studies from Sensor Technology

2019 ◽  
Vol 9 (3) ◽  
pp. 435 ◽  
Author(s):  
Michael Krutwig ◽  
Bernhard Kölmel ◽  
Adrian Tantau ◽  
Kejo Starosta
Keyword(s):  
Case Studies ◽  
Smart Grids ◽  
Manufacturing Industry ◽  
Energy Systems ◽  
Sensor Technology ◽  
Area Network ◽  
Wide Area Network ◽  
Physical Energy ◽  
Wide Range ◽  
Operational Energy

Cyber-physical energy systems (CPES) describe a specialization of the cyber-physical system concept, in which energy systems are transformed into intelligent energy networks. These systems provide the basis for the realization of smart microgrids and smart grids. In the last decade, numerous research projects have intensively explored the fundamentals and modeling of CPES and validated them in pilot projects. In the meantime, more and more CPES solutions have been appearing on the market and the battle for the most suitable standards has begun. This paper gives an overview of the currently available standards for CPES sensor technologies and assesses the suitability for implementation. In two case studies in the application area of operational energy management in German companies, a sensor retrofitting is described—once with proprietary technology and once using the standards Long Range (LoRa) Wide Area Network and OPC Unified Architecture (OPC UA). As a result, the shortcomings of the standards for their use in CPES are shown and discussed. OPC UA, which was originally developed for the manufacturing industry, turns out to be to be a suitable standard for a wide range of CPES implementations.

scholarly journals Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-32 ◽  
Author(s):  
João Soares ◽  
Tiago Pinto ◽  
Fernando Lezama ◽  
Hugo Morais
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Electric Vehicles ◽  
Computational Intelligence ◽  
Smart Grids ◽  
Energy Resource ◽  
Management Problem ◽  
Renewable Generation ◽  
Complex Problems ◽  
Optimization And Simulation

This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

High-Performance Computing and Geography: Developments, Issues, and Case Studies

1998 ◽  
Vol 30 (10) ◽  
pp. 1839-1856 ◽  
Author(s):  
I Turton ◽  
S Openshaw
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Geographic Information Systems ◽  
High Performance Computing ◽  
Case Studies ◽  
Computational Intelligence ◽  
High Performance ◽  
Recent Developments ◽  
Parallel Supercomputer ◽  
Performance Computing

In this paper we outline some of the results that were obtained by the application of a Cray T3D parallel supercomputer to human geography problems. We emphasise the fundamental importance of high-performance computing (HPC) as a future relevant paradigm for doing geography. We offer an introduction to recent developments and illustrate how new computational intelligence technologies can start to be used to make use of opportunities created by data riches from geographic information systems, artificial intelligence tools, and HPC in geography.

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