The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The books main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology

An Introduction to MultiAgent Systems.

https://recipp.ipp.pt/bitstream/10400.22/1585/7/ART_HMorais_2009_GECAD.pdf

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

This paper presents an electricity consumer characterization framework based on a knowledge discovery in databases (KDD) procedure, supported by data mining (DM) techniques, applied on the different stages of the process. The core of this framework is a data mining model based on a combination of unsupervised and supervised learning techniques. Two main modules compose this framework: the load profiling module and the classification module. The load profiling module creates a set of consumer classes using a clustering operation and the representative load profiles for each class. The classification module uses this knowledge to build a classification model able to assign different consumers to the existing classes. The quality of this framework is illustrated with a case study concerning a real database of LV consumers from the Portuguese distribution company.

/pdf/an-electric-energy-consumer-characterization-framework-based-31f3baap69.pdf

An electric energy consumer characterization framework based on data mining techniques

https://isiarticles.com/bundles/Article/pre/pdf/3047.pdf

A critical survey of agent-based wholesale electricity market models

Around the world, the electricity industry, which has long been dominated by vertically integrated utilities, is experiencing major changes in the structure of its markets and regulations. Owing to new regulations, it's evolving into a distributed industry in which market forces drive electricity's price. The industry is becoming competitive; a market environment is replacing the traditional centralized-operation approach. This transformation is often called the deregulation of the electricity market. MASCEM, a multiagent simulator system, is a valuable framework for evaluating new rules, new behavior, and new participants in the numerous electricity markets that are moving toward liberalization and competition.

MASCEM: a multiagent system that simulates competitive electricity markets

In this paper we propose a Multi-Agent system architecture to simulate and analyse Competitive Electricity Markets combining bilateral trading with power exchange mechanisms. This Multi-Agent environment includes several heterogeneous and autonomous intelligent agents representing the different independent entities in Electricity Markets. Agents are endowed with historical information about the market including past strategies of other players, and have strategic behaviour to face the market. This paper focuses on the different negotiation mechanisms supported by the simulator, and on agents' strategic behaviour to face them. A special emphasis is devoted to the structure of market players, Seller and Buyer agents, particularly in what concerns their decision analysis process to face the challenging market. A detailed description of an algorithm for Decision Support is presented. This is a promising algorithm to improve agents bidding process and counter-proposals definition.

Intelligent agents for negotiation and game-based decision support in electricity markets

As electric utility systems around the world continue to move towards open, competitive markets, the need for new modeling techniques will become more obvious. To study electricity markets behaviour and evolution we propose a multi-agent simulator where agents represent several entities that can be found in electricity markets, such as generators, consumers, market operators and network operators, but also entities that are emerging with the advent of liberalization, such as traders. The simulator probes the possible effects of market rules and conditions by simulating the strategic behaviour of participants. In this paper a special attention is devoted to the strategic decision processes of seller, buyer and trader agents, in order to gain advantage facing the new emerging competitive market.

/pdf/a-new-agent-based-framework-for-the-simulation-of-59yz26u680.pdf

A new agent-based framework for the simulation of electricity markets

This article presents work on applying multiagent simulation to analyze competitive electricity markets and to give decision support to the involved entities. A multiagent model is defined, where a...

Intelligent Agents for the Simulation of Competitive Electricity Markets

As electricity markets evolve, there is a need for new modelling approaches that simulate how electric power markets could evolve over time and how participants in these markets may act and react to the changing economic, financial and regulatory environment in which they operate. To study electricity markets behaviour and evolution we propose a multi-agent simulator where agents represent several entities that can be found in electricity markets, such as generators, consumers, market operators and network operators, but also entities that are emerging with the advent of liberalization, such as traders. The simulator probes the possible effects of market rules and conditions by simulating the strategic behaviour of participants. In this paper a special attention is devoted to the behaviour and characteristics of Seller, Buyer and Trader agents, highlighting their strategies and decision processes in order to gain advantage facing the new emerging competitive market.

An Agent-Based Simulator for Electricity Markets: Seller, Buyer, and Trader Players

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