NDLI: Electricity Markets Portfolio Optimization Using a Particle Swarm Approach

Content Provider	IEEE Xplore Digital Library
Author	Guedes, N. Pinto, T. Vale, Z. Sousa, T.M. Sousa, T.
Copyright Year	2013
Description	Author affiliation: GECAD - Knowledge Eng. & Decision Support Res. Center, Polytech. of Porto, Porto, Portugal (Guedes, N.; Pinto, T.; Vale, Z.; Sousa, T.M.; Sousa, T.)
Abstract	Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors' research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player's portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and off-peak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator - OMIE.
Starting Page	199
Ending Page	203
File Size	253307
Page Count	5
File Format	PDF
ISBN	9780769550701
ISSN	15294188
e-ISBN	9781479921386
DOI	10.1109/DEXA.2013.49
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electricity supply industry Context Optimization Databases Portfolios Particle swarm optimization Multi-agent systems Portfolio Optimization Adaptive Learning Artificial Neural Network Electricity Markets Multi-Agent Simulation Particle Swarm Optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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