12,169 research outputs found
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy
management mechanism for the smart grid that enables each prosumer of the
network to participate in energy trading with one another and the grid. This
poses a significant challenge in terms of modeling the decision-making process
of each participant with conflicting interest and motivating prosumers to
participate in energy trading and to cooperate, if necessary, for achieving
different energy management goals. Therefore, such decision-making process
needs to be built on solid mathematical and signal processing tools that can
ensure an efficient operation of the smart grid. This paper provides an
overview of the use of game theoretic approaches for P2P energy trading as a
feasible and effective means of energy management. As such, we discuss various
games and auction theoretic approaches by following a systematic classification
to provide information on the importance of game theory for smart energy
research. Then, the paper focuses on the P2P energy trading describing its key
features and giving an introduction to an existing P2P testbed. Further, the
paper zooms into the detail of some specific game and auction theoretic models
that have recently been used in P2P energy trading and discusses some important
finding of these schemes.Comment: 38 pages, single column, double spac
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
Decentralized Coalition Formation with Agent-based Combinatorial Heuristics
A steadily growing pervasion of the energy distribution grid with communication technology is widely seen as an enabler for new computational coordination techniques for renewable, distributed generation as well as for bundling with controllable consumers. Smart markets will foster a decentralized grid management. One important task as prerequisite to decentralized management is the ability to group together in order to jointly gain enough suitable flexibility and capacity to assume responsibility for a specific control task in the grid. In self-organized smart grid scenarios, grouping or coalition formation has to be achieved in a decentralized and situation aware way based on individual capabilities. We present a fully decentralized coalition formation approach based on an established agent-based heuristics for predictive scheduling with the additional advantage of keeping all information about local decision base and local operational constraints private. Two closely interlocked optimization processes orchestrate an overall procedure that adapts a coalition structure to best suit a given set of energy products. The approach is evaluated in several simulation scenarios with different type of established models for integrating distributed energy resources and is also extended to the induced use case of surplus distribution using basically the same algorithm
Reserve Allocation in Active Distribution Systems for Tertiary Frequency Regulation: A Coalitional Game Theory-based Approach
This paper proposes a coalitional game theory-based approach for reserve
optimization to enable DERs participate in tertiary frequency regulation. A
two-stage approach is proposed to effectively and precisely allocate spinning
reserve requirements from each DER in distribution systems. In the first stage,
two types of characteristic functions: worthiness index (WI) and power loss
reduction (PLR) of each coalition are computed. In the second stage, the
equivalent Shapley values are computed based on the characteristic functions,
which are used to determine distribution factors for reserve allocation among
DERs
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
Cloud Compute-and-Forward with Relay Cooperation
We study a cloud network with M distributed receiving antennas and L users,
which transmit their messages towards a centralized decoder (CD), where M>=L.
We consider that the cloud network applies the Compute-and-Forward (C&F)
protocol, where L antennas/relays are selected to decode integer equations of
the transmitted messages. In this work, we focus on the best relay selection
and the optimization of the Physical-Layer Network Coding (PNC) at the relays,
aiming at the throughput maximization of the network. Existing literature
optimizes PNC with respect to the maximization of the minimum rate among users.
The proposed strategy maximizes the sum rate of the users allowing nonsymmetric
rates, while the optimal solution is explored with the aid of the Pareto
frontier. The problem of relay selection is matched to a coalition formation
game, where the relays and the CD cooperate in order to maximize their profit.
Efficient coalition formation algorithms are proposed, which perform joint
relay selection and PNC optimization. Simulation results show that a
considerable improvement is achieved compared to existing results, both in
terms of the network sum rate and the players' profits.Comment: Submitted to IEEE Transactions on Wireless Communication
A new approach for multi-agent coalition formation and management in the scope of electricity markets
This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.
The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition.
In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and
analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in
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