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Erschienen in:
Overview of Wholesale Electricity Markets Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

3. Electricity Markets and Intelligent Agents Part II: Agent Architectures and Capabilities

verfasst von : Fernando Lopes, Helder Coelho

Erschienen in: Electricity Markets with Increasing Levels of Renewable Generation: Structure, Operation, Agent-based Simulation, and Emerging Designs

Verlag: Springer International Publishing

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Abstract

Agent technology is a relatively new and rapidly expanding area of research and development. The major motivations for the increasing interest in intelligent agents and multi-agent systems include the ability to provide solutions to problems that can naturally be regarded as a society of autonomous interacting components, to solve problems that are too large for a centralized agent to solve, and to provide solutions in situations where expertise is distributed. Electricity markets (EMs) are complex distributed systems, typically involving a variety of transactive techniques (e.g., centralized and bilateral market clearing). The agent-based approach is an ideal fit to the naturally distributed domain of EMs. Accordingly, a number of agent-based models and systems for EMs have been proposed in the technical literature. These models and systems exhibit fairly different features and make use of a diverse range of concepts. At present, there seems to be no agreed framework to analyze and compare disparate research efforts. Chapter 2 and this companion chapter claim that such a framework can be very important and instructive, helping to understand the interrelationships of disparate research efforts. Accordingly, Chap. 2 (Part I) and this chapter (Part II) introduce a generic framework for agent-based simulation of EMs. The complete framework includes three groups (or categories) of dimensions: market architecture, market structure and software agents. The first two groups were the subject of Chap. 2. This chapter discusses in considerable detail the last group of dimensions, labeled “software agents”, and composed by two distinct yet interrelated dimensions: agent architectures and agent capabilities.

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Vorheriges Kapitel Electricity Markets and Intelligent Agents Part I: Market Architecture and Structure
Nächstes Kapitel Market Prices in a Power Market with More Than 50% Wind Power
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Fußnoten
1
Although it is conceptually useful to distinguish between the two broad dimensions of “agent architectures” and “agent capabilities”, the distinction is not absolute (and may at times be somewhat arbitrary). Accordingly, the reader may find some overlap between these dimensions.
 
2
The architectures discussed in the first part of this section are based on the five basic types of agents presented in [25, Chap. 2]. The present section, however, is not intended as a summary of the authors’ views on agent architectures, and also presents a top-level view of a software agent.
 
3
For convenience, throughout this section we use the term “environment” to denote a generic agent environment. For software agents that represent market entities operating in a competitive energy market, the term should denote, naturally, this particular market environment.
 
4
Formally speaking, several conceptions of limited rationality for software agents have been proposed in the literature, notably bounded optimality—the capacity to generate maximally successful behavior given the available information and computational resources. Bounded optimal agents behave as well as possible, given their computational resources (see, e.g., [26, 27] for details).
 
5
Figure 3.1 gives an abstract view of an agent. Specific details about each component module and the control flow among modules need further architectural refinement (e.g., details about the decision-making mechanism). See [32, Chap. 2] and [33] for representative surveys of concrete agent architectures up to 1998, and [2, Chaps. 3–5] for a description of subsequent work.
 
6
The agent commonly operates in an environment populated by other agents and interacts with them to meet its design objectives. In Fig. 3.1, we have not included components that explicitly support such interaction (but see the next subsection).
 
7
For the sake of simplicity, we consider fairly direct representations of the agent’s beliefs and internal state. However, the internal state may be seen as a subset of the beliefs, namely beliefs about the environment where the agent operates.
 
8
Plans-as-recipes are often stored in an internal data structure called plan library (see, e.g., [34]). Also, researchers working in the area of agent architectures use different terms to denote structures similar in function to plans-as-recipes (e.g., knowledge areas [35], or plan templates or schemata [36]).
 
9
Software agents that can combine both reactive and deliberative reasoning are commonly refereed to as hybrid agents.
 
10
At this stage, a natural question to ask is: “Which of the architectures described in the previous subsection should be considered by agent designers?” The answer is: “All of them” [25, Chap. 27].
 
11
Although the three agent properties discussed earlier—autonomy, reactivity and pro-activeness—are mainly related to the micro aspects of agent technology (the agent level), social ability is closely related to the macro aspects of agent technology (the social level). In other words, we now move from the micro level of individual agents to the macro level of multi-agent systems.
 
13
Chapter 8 is entirely devoted to the agent-based system and presents a detailed description of its main features. The reader is therefore referred to it for details.
 
14
As noted earlier, a market to match the imbalances caused by the variability and uncertainty present in power systems is currently being developed.
 
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Metadaten
Titel
Electricity Markets and Intelligent Agents Part II: Agent Architectures and Capabilities
verfasst von
Fernando Lopes
Helder Coelho
Copyright-Jahr
2018
Buch
Electricity Markets with Increasing Levels of Renewable Generation: Structure, Operation, Agent-based Simulation, and Emerging Designs

Print ISBN: 978-3-319-74261-8

Electronic ISBN: 978-3-319-74263-2

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-74263-2_3