Coalition formation in transmission expansion planning

The study of a decentralized coalition formation scheme in a specific power systems transmission expansion scenario is the purpose of this paper. We define first who are the agents in the expansion game and provide a decentralized coalition scheme based on Bilateral Shapley values. Finally, we allocate the total costs of expansion amongst the agents, based on the coalition history, and we compare our method with a centralized scheme.published_or_final_versio

A kernel-oriented algorithm for transmission expansion planning

With deregulation sweeping all over electrical systems around the world, transmission planning has undergone dramatic changes during this decade. Centralized cost allocation methods have become obsolete and new procedures are needed to deal with intelligent and self-sufficient players. In this paper we study the allocation of transmission costs in a decentralized manner. For this purpose we have developed a multi-agent system that is based on a well known cooperative game theory procedure, the kernel. Using our approach, the agents are able to form kernel-stable coalitions and the cost allocation procedure is performed at every step of the kernel- algorithm. A six bus example and an IEEE 24 bus case illustrate our model. © 2000 IEEE.published_or_final_versio

Multi-agent systems and birtual producers in electronic marketplaces

This paper presents an agent-based simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, considering user risk preferences. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions. In the simulated market agents interact in several different ways and may joint together to form coalitions. In this paper we address multi-agent coalitions to analyse Distributed Generation in Electricity Market

Multi-agent coalition formation in power transmission planning

Deregulation and restructuring have become unavoidable trends to the power industry recently in order to increase its efficiency, to reduce operation costs, or to provide customers better services. The once centralized system planning and management must be remodeled to reflect the changes in the market environment. We have proposed and developed a multi-agent based system to assist players, such as, owners of power generation stations, owners of transmission lines, and groups of consumers, in the same market to select partners to form coalitions. The system provides users with a cooperation plan and its associated cost allocation plan for the users to support their decision making process. Bilateral Shapley Value (BSV) was selected as the theoretical foundation to develop the system. The multi-agent system was developed by the combination of IDEAS and Tcl/Tk.published_or_final_versio

A multi-agent approach to the deregulation and restructuring of power industry

In recent years, the electric utility industry throughout the world has been facing pressure to deregulate or restructure in order to increase its efficiency, to reduce operational costs or to give consumers more alternatives. The once centralized system planning and operation management must be remodelled to adapt to the new market environment. Subject to unavoidable constraints such as the capacity of generation stations, physical limitations of the transmission lines, and demand on days-ahead scheduling, the current trading mechanism needs to be revised so that any party can be involved in this free-market environment. The paper presents a multi-agent approach to resolve the multilateral trading problem. The authors have implemented a prototype based on bilateral Shapley value and Internet technologies. The prototype has been tested with a classical six-bus system.published_or_final_versio

Virtual power producers integration into MASCEM

All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. Under this context distributed generators, owned by different decentralized players can provide a significant amount of the electricity generation. To get negotiation power and advantages of scale economy, these players can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multi-technology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the integration of Virtual Power Producers into an electricity market simulator –MASCEM – as a coalition of distributed producers

Anytime Coalition Structure Generation with Worst Case Guarantees

Coalition formation is a key topic in multiagent systems. One would prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. But then, can the coalition structure found via a partial search be guaranteed to be within a bound from optimum? We show that none of the previous coalition structure generation algorithms can establish any bound because they search fewer nodes than a threshold that we show necessary for establishing a bound. We present an algorithm that establishes a tight bound within this minimal amount of search, and show that any other algorithm would have to search strictly more. The fraction of nodes needed to be searched approaches zero as the number of agents grows. If additional time remains, our anytime algorithm searches further, and establishes a progressively lower tight bound. Surprisingly, just searching one more node drops the bound in half. As desired, our algorithm lowers the bound rapidly early on, and exhibits diminishing returns to computation. It also drastically outperforms its obvious contenders. Finally, we show how to distribute the desired search across self-interested manipulative agents

Models of Interaction as a Grounding for Peer to Peer Knowledge Sharing

Most current attempts to achieve reliable knowledge sharing on a large scale have relied on pre-engineering of content and supply services. This, like traditional knowledge engineering, does not by itself scale to large, open, peer to peer systems because the cost of being precise about the absolute semantics of services and their knowledge rises rapidly as more services participate. We describe how to break out of this deadlock by focusing on semantics related to interaction and using this to avoid dependency on a priori semantic agreement; instead making semantic commitments incrementally at run time. Our method is based on interaction models that are mobile in the sense that they may be transferred to other components, this being a mechanism for service composition and for coalition formation. By shifting the emphasis to interaction (the details of which may be hidden from users) we can obtain knowledge sharing of sufficient quality for sustainable communities of practice without the barrier of complex meta-data provision prior to community formation