Scope of the Subcommittee

The Intelligent System Applications (ISA) Subcommittee investigates the development and applications of intelligent system methodologies and tools for problem-solving in power system engineering. These intelligent system techniques include expert systems, knowledge engineering, artificial neural networks, fuzzy logic, machine learning, evolutionary algorithms, and heuristic search methods.

The ISA Subcommittee organizes working groups and task forces that investigate innovative intelligent system methods and tools and their applications to power system engineering. This subcommittee sponsors technical sessions, tutorial courses, workshops, conferences, and other activities for the effective dissemination of state-of-the-art information within the technical area of the subcommittee. This subcommittee coordinates activities on intelligent system applications with other groups in IEEE Power Engineering Society and other technical organizations including CIGRE.

The Subcommittee’s intent is to focus on the following topics.

Core Focus

Intelligent methods
Algorithm development
System modeling and analysis
Data modeling
Design tools
Test systems

Call for participation: 2022-3 Competition on solar generation forecasting

Benchmarking of artificial intelligence methods for solar generation forecasting to address the increasing importance of energy resources forecasting in current and future power and energy systems.

NEW DEADLINE: 15th January 2023

I. Scope and Topics

Energy resource forecasting is increasingly important in current and future power and energy systems. Due to the high uncertainty of generation based on renewable energy sources, which results from their dependence on weather conditions, such as wind speed or solar intensity, the need to develop suitable solutions to deal with such variability increases considerably.

A relevant effort is being put into the development of energy consumption and generation forecasting methods, able to deal with different forecasting circumstances, e.g., the prediction time horizon, the available data, the frequency of data, or even the quality of data measurements. The main conclusion is that different methods are more suitable for different prediction circumstances, and it is not clear that a certain method can outperform all others in all situations.

This competition fosters the benchmarking of artificial intelligence methods for solar generation forecasting. Authors of methods that present the best results in this competition will be invited to present their work.

II. Submission Instructions

The deadline for the results submission has been postponed to 15th January 2023. The participants that already made their submissions are invited to improve their results until the new deadline.

Competition website:

Other competitions:


Luis Gomes, Polytechnic of Porto, Portugal (
Zita Vale, Polytechnic of Porto, Portugal (
Tiago Pinto, Polytechnic of Porto, Portugal (

Supported by the Working Group of Intelligent Data Mining and Analysis (IDMA) and IEEE PES Task Force on Open Data Set.

Supported by IEEE CIS Task Force on ‘Computational Intelligence in the Energy Domain’.

Consult, Use, Contribute, and Disseminate the Initiative of providing power system professionals with Public Data Sets

The IEEE Working Group (WG) on Intelligent Data Mining and Analysis makes power and energy-related data sets available whenever confidentiality and data property issues do not prevent their public use.
These data are intended to be used by researchers and other professionals working in power and energy-related areas requiring data for design, development, test, and validation purposes. These data should not be used for commercial purposes.

The public data sets are permanently available at

Dissemination of this initiative is taking place so that the number and diversity of the published data sets increase over time and can be used as a valuable public resource for R&D activities. Your contribution to this initiative can be very important. Please disseminate and contribute; use our contact points (; to have all the data that can be made public published on the website.

Please check our Call for Open Data Sets.


Sukumar Mishra, IIT Delhi
Hauz Khas, New Delhi 110 016, India


Hiroyuki Mori, Meiji University
Room 1203, 4-21-1 Nakano, Nakano-ku, Tokyo 164-8525, Japan



Past Chair

Zita A. Vale,, ISEP/IPP – Instituto Superior de Engenharia do Instituto Politécnico do Porto / Polytechnic of Porto
Rua Dr. António Bernardino de Almeida, 431; 4249-015 Porto – Portugal

Alexandre P. Alves Da Silva, General Electric, Fairfield · GE Global Research Center,
3135 Easton Turnpike, Fairfield, Connecticut 06828, USA

This subcommittee is a part of the Analytic Methods for Power Systems (AMPS) Technical Committee of the IEEE Power & Energy Society.