Multi-Agent Systems for Power Engineering Applications—Part II: Technologies, Standards, and Tools for Building Multi-agent Systems

McArthur, S.D.J.; Davidson, E.M.; Catterson, Victoria M.; Dimeas, Aris; Hatziargyriou, Nikos D.; Ponci, Ferdinanda; Funabashi, Toshihisa

doi:10.1109/tpwrs.2007.908472

Cited by 449 publications

(179 citation statements)

References 17 publications

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“…This step is modeled by the optimization problem (10). The producer procures and activates flexibility services based on the solution of problem (11).…”

Section: Producer and Retailermentioning

confidence: 99%

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DSIMA: A testbed for the quantitative analysis of interaction models within distribution networks

Mathieu

Louveaux

Ernst

et al. 2016

Sustainable Energy, Grids and Networks

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a b s t r a c tThis article proposes an open-source testbed to simulate interaction models governing the exchange of flexibility services located within a distribution network. The testbed is an agent-based system in which the distribution system operator, the transmission system operator, producers and retailers make their decisions based on mixed-integer linear programs. This testbed helps to highlight the characteristics of an interaction model, the benefits for the agents and eases the detection of unwanted or abusive behaviors which decreases the welfare. The testbed is implemented in Python and the optimization problems are encoded in the modeling language ZIMPL. A web interface is coupled with an instance generator using macroscopic parameters of the system such as the total power production. This testbed is, therefore, well suited to test the implemented interaction models on various scenarios and to extend the implementation to other models. Five interaction models developed with industrial partners are simulated over a year on a 75-bus test system. Simulations show that interaction models relying on active network management, as they have been developed, lead to substantial welfare even though they suffer from a lack of coordination between the DSO and the TSO. A conservative interaction model restricting grid users to an access range that is computed ahead of time to prevent any congestion, avoids shedding distributed generation but considerably restrains the amount of distributed production.

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“…This step is modeled by the optimization problem (10). The producer procures and activates flexibility services based on the solution of problem (11).…”

Section: Producer and Retailermentioning

confidence: 99%

“…Agent-based modeling has been extensively used in the literature to model electric systems [10][11][12][13]. The OPTI-MATE open platform is an example of an agent-based tool used in power systems.…”

Section: Introductionmentioning

confidence: 99%

DSIMA: A testbed for the quantitative analysis of interaction models within distribution networks

Mathieu

Louveaux

Ernst

et al. 2016

Sustainable Energy, Grids and Networks

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“…The advantages (e.g., scalability, autonomy and intelligence) are illustrated through a case study describing a SCADA system for electricity transportation management. In [6,7] the authors focus on the application of MAS to power engineering, where problems are formalized, technologies are discussed, and several implementation issues are addressed. In [10] it is reported that MAS technologies outperform classical technologies in the protection of power distribution systems.…”

Section: Related Workmentioning

confidence: 99%

“…BDI agents have been used to develop SCADA systems by treating system components as autonomous agents, to provide better scalability, autonomy and intelligence [6,7,2]. Each agent's beliefs (knowledge about the environment), desires (goals), and intentions (commitments to act) are explicitly represented.…”

Section: Introductionmentioning

confidence: 99%

Incorporating PGMs into a BDI Architecture

Chen

Hong

Liu

et al. 2013

Lecture Notes in Computer Science

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Abstract. In this paper, we present a hybrid BDI-PGM framework, in which PGMs (Probabilistic Graphical Models) are incorporated into a BDI (belief-desire-intention) architecture. This work is motivated by the need to address the scalability and noisy sensing issues in SCADA (Supervisory Control And Data Acquisition) systems. Our approach uses the incorporated PGMs to model the uncertainty reasoning and decision making processes of agents situated in a stochastic environment. In particular, we use Bayesian networks to reason about an agent's beliefs about the environment based on its sensory observations, and select optimal plans according to the utilities of actions defined in influence diagrams. This approach takes the advantage of the scalability of the BDI architecture and the uncertainty reasoning capability of PGMs. We present a prototype of the proposed approach using a transit scenario to validate its effectiveness.

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“…Several recent reviews show that multi-agent systems research in the power systems domain is well-established [18,36,66,67,83,92]. While their original application was often for power system market simulation [85], they have also been used in the context of power system stability control [71].…”

Section: Introduction: Resilience In Power System Coordination and Controlmentioning

confidence: 99%

Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems

Farid

2015

Intell Ind Syst

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Recently, the academic and industrial literature has coalesced around an enhanced vision of the electric power grid that is intelligent, responsive, dynamic, adaptive and flexible. One particularly emphasized "smart-grid" property is that of resilience where healthy regions of the grid continue to operate while disrupted and perturbed regions bring themselves back to normal operation. Multi-agent systems have recently been proposed as a key enabling technology for such a resilient control scheme. While the power system literature has often addressed multi-agent systems, many of these works did not have resilience as the central design intention. This paper now has a two-fold purpose. First, it seeks to identify a set of multi-agent system design principles for resilient coordination and control of future power systems. To that end, it draws upon an axiomatic design for large flexible engineering systems model which was recently used in the development of resilience measures. From this quantitative model, a set of design principles are easily distilled. Second, the paper assesses the adherence of existing multi-agent system implementations with respect to these design principles. The paper concludes that while many multi-agent systems have been developed for power grids, they have been primarily intended as the decentralization of a particular decision-making/control algorithm. Thus many of the works make only limited contributions to power grid resilience.B Amro M. Farid

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Multi-Agent Systems for Power Engineering Applications—Part II: Technologies, Standards, and Tools for Building Multi-agent Systems

Abstract: T. (2007) Multi-agent systems for power engineering applicationspart 2: technologies, standards and tools for building multi-agent systems. IEEE Transactions on Power Systems, 22 (4). pp. 1753-1759.

Cited by 449 publications

References 17 publications

DSIMA: A testbed for the quantitative analysis of interaction models within distribution networks

DSIMA: A testbed for the quantitative analysis of interaction models within distribution networks

Incorporating PGMs into a BDI Architecture

Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems

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