Multi-agent based metalearner using genetic algorithm for decision support in electricity markets

Author(s):  
Tiago Pinto ◽  
Joao Barreto ◽  
Isabel Praca ◽  
Gabriel Santos ◽  
Zita Vale ◽  
...  
Author(s):  
Tiago Pinto ◽  
Zita Vale

This paper presents the Adaptive Decision Support for Electricity Markets Negotiations (AiD-EM) system. AiD-EM is a multi-agent system that provides decision support to market players by incorporating multiple sub-(agent-based) systems, directed to the decision support of specific problems. These sub-systems make use of different artificial intelligence methodologies, such as machine learning and evolutionary computing, to enable players adaptation in the planning phase and in actual negotiations in auction-based markets and bilateral negotiations. AiD-EM demonstration is enabled by its connection to MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).


2011 ◽  
Vol 20 (02) ◽  
pp. 271-295 ◽  
Author(s):  
VÍCTOR SÁNCHEZ-ANGUIX ◽  
SOLEDAD VALERO ◽  
ANA GARCÍA-FORNES

An agent-based Virtual Organization is a complex entity where dynamic collections of agents agree to share resources in order to accomplish a global goal or offer a complex service. An important problem for the performance of the Virtual Organization is the distribution of the agents across the computational resources. The final distribution should provide a good load balancing for the organization. In this article, a genetic algorithm is applied to calculate a proper distribution across hosts in an agent-based Virtual Organization. Additionally, an abstract multi-agent system architecture which provides infrastructure for Virtual Organization distribution is introduced. The developed genetic solution employs an elitist crossover operator where one of the children inherits the most promising genetic material from the parents with higher probability. In order to validate the genetic proposal, the designed genetic algorithm has been successfully compared to several heuristics in different scenarios.


2019 ◽  
Vol 22 (6) ◽  
pp. 1467-1485 ◽  
Author(s):  
Juan Du ◽  
Hengqing Jing ◽  
Kim-Kwang Raymond Choo ◽  
Vijayan Sugumaran ◽  
Daniel Castro-Lacouture

2012 ◽  
Vol 241-244 ◽  
pp. 1745-1750
Author(s):  
Nan Nan Yan ◽  
Di Zheng

This paper mainly concentrated on the method of improving the dispatching trucks working at a container terminal and built the multi-agent model for the dispatching job. The contract net protocol was taken as the communication ones among agents, and the analytic hierarchy process was also applied for the decision support for container trucks dispatching.


Smart Cities ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 1437-1453
Author(s):  
Hugo Algarvio

Over the last few decades, the electricity sector has experienced several changes, resulting in different electricity markets (EMs) models and paradigms. In particular, liberalization has led to the establishment of a wholesale market for electricity generation and a retail market for electricity retailing. In competitive EMs, customers can do the following: freely choose their electricity suppliers; invest in variable renewable energy such as solar photovoltaic; become prosumers; or form local alliances such as Citizen Energy Communities (CECs). Trading of electricity can be done in spot and derivatives markets, or by bilateral contracts. This article focuses on CECs. Specifically, it presents how agent-based local consumers can form alliances as CECs, manage their resources, and trade on EMs. It also presents a review of how agent-based systems can model and support the formation and interaction of alliances in the electricity sector. The CEC can trade electricity directly with sellers through private bilateral agreements. During the negotiation of private bilateral contracts, the CEC receives the prices and volumes of their members and according to its negotiation strategy, tries to satisfy the electricity demands of all members and reduce their costs for electricity.


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