Category Power Electronics for Renewable and Distributed Energy Systems

Future Developments

Although they are very promising, MAS are still an emerging technology in the

field of power systems. Topics to explore in the future include:

• Making agents smarter. Most agents used in MAS for power systems tend to be closer to reactive agents than to cognitive agents. Making them smarter would enable a greater autonomy and more complex decision-making processes with additional parameters taken into account. The learning capability of agents could for example have many applications, from forecasting to scheduling, and could partially pre-solve some problems. Similarly, the planning capacity of agent is rarely used.

• Fully distributing and automating the decision-making process. Decision­making processes are usually partially centralized, i. e., not fully distributed...

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Protection Fault Analysis and Management

Davidson et al. [81] propose a fault diagnosis and management called PEDA, for protection engineering diagnosis agents (PEDA). PEDA has been used since 2004 by a British utility. Its objective is to automate the analysis and management of faults recorded by SCADAs and digital fault recorders (DFR). As thousands of faults can be recorded during an event such as a storm, engineers need to be supported by a system capable of extracting the most important information from the mass of collected data.

In this case, MAS technology was used as a medium for system integration. The hardware and software used to achieve fault analysis and management can indeed change rather frequently over time, and the system has to be able to accommodate such evolutions...

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One of the earliest applications of MAS in power systems is for restoration, as described in Nagata and Sasaki [76]. Restoration is needed after a partial or global blackout has occurred. Operators usually employ an OMS to automatically restore power, by sequentially re-energizing all the buses in the grid so as to serve the loads. At the end of the process, the grid is back to its normal operation mode, as before the event. The objective is to serve the maximum of loads connected to the buses. Several constraints have to be respected: the balance between supply and demand, the capacity of each source, and the voltage limits on each bus and branch.

In the proposed approach, two types of agents are used (Fig. 15.27): bus agents (BAG, one for each bus), and a facilitator agent (FAG)...

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Market-Based Coordination of Distributed Generation

Coordinating distributed energy sources in modernized power markets is another field where MAS-based cooperation can be employed. PowerMatcher, a concept developed by ECN in the Netherlands [51, 68, 69], is an example. The objective is
to coordinate agents so as to balance supply and demand in an economically efficient way. To solve this problem, agents have the capability to competitively trade energy on a common market. These market-based negotiations provide a decision-making framework based on microeconomics.

The negotiation process relies on dynamic pricing schemes, in which prices can vary throughout the day depending on the balance between supply and demand: the higher the demand, the higher the prices, and vice versa...

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Applications of MAS to Power Systems

For all the reasons listed in the previous sections, MAS have been applied to solve several problems in power systems. The following four examples were published in the last decade. Based on the explanations from the previous sections, the reader is encouraged to analyze what choices the designers of the presented MAS have conducted. Other existing applications [4] also constitute interesting concepts.

15.5.1 Coordinated DC Bus Voltage Control

Lagorse et al. proposed a MAS-based coordinated DC bus voltage control scheme, described in [67]...

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Development Platforms

Although it is possible to develop a MAS from scratch, using a dedicated devel­opment platform (middleware) is, in most cases, a much simpler solution. Many different toolkits were created over the years, as shown in [62]. These platforms include tools and functionalities that facilitate the development of MAS. Some of them comply with FIPA standards, especially for messaging and agent manage­ment. A list of such platforms is available in [63].

In the field of MAS for power system applications, the Java agent development framework (JADE [64]) is the most popular. It has extensive documentation, third – party plug-ins (e. g., for mobile devices, for BDI agents [65], etc.) and full FIPA compatibility...

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Multi-Agent Planning

In order to attain their goals, agents are sometimes required to coordinate them­selves to cooperate or compete with each other, and dispatch tasks using inter­action protocols. In some cases, agents may be required to plan their actions before executing them. Actions can include rounds of interactions that must happen in a given order, for example if their outcomes are interdependent. As shown in Fig. 15.21, planning enables advanced agent cooperation, whereas negotiations are used for managing competing agents.

Similarly to interactions, planning involves action selection, sequencing, and resources handling. The established plans can be action sequences or action trees resulting from policies and strategies defined by the designer or by other agents. Figure 15.7 provides a simple examp...

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Inter-Agent Interaction

The described topologies define the interaction of an agent with another one, or entity, but it is still needed to define how they interact. Interactions are paramount notions for defining MAS [2]. An interaction between agents can only take place if they can act or communicate and if there are situations where they can get toge­ther, such as the need to fulfill a common objective. Interactions may be conducted under the form of discussions between at least two agents and can occur in numerous situations: the rescue of an agent by others, a conversation between two agents, the implicit agreement when two agents have to decide which one goes first, the cooperation of several agents to fulfill a common task, and so on.

Interactions are usually required when agents have to satisfy a common o...

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