MASGriP &amp;#x2014; A Multi-Agent Smart Grid Simulation Platform

Oliveira, Pedro; Pinto, Tiago; Morais, Hugo; Vale, Zita

doi:10.1109/pesgm.2012.6345649

Cited by 69 publications

(59 citation statements)

References 20 publications

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“…SHIM is part of a large simulation platform based in multi-agents systems. Multi-Agent Smart Grid Simulation Platform (MASGriP) is a test platform that simulates a competitive environment in future power systems [10]. SHIM is included in consumers' agents in MASGriP.…”

Section: Dynamic Load Management Algorithms During a Demand Response mentioning

confidence: 99%

“…Other interesting feature of SHIM is the possibility of managing real and virtual loads in the same simulation. On the other hand, SHIM is included in a smart grids simulation platform based on multi-agent systems called Multi-Agent Smart Grid Simulation Platform (MASGriP) [10]. In fact, MASGriP integrates several SHIM, one in each consumer agent.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic load management in a smart home to participate in demand response events

Fernandes

Morais

Vale

et al. 2014

Energy and Buildings

123

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In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heat-ing systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources' management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

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Section: Dynamic Load Management Algorithms During a Demand Response mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic load management in a smart home to participate in demand response events

Fernandes

Morais

Vale

et al. 2014

Energy and Buildings

123

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“…These entities operate under the management and supervision of VPPs (Oliveira et al, 2012). In the proposed model, the responsible administrative entity for demand side management is the VPP.…”

Section: Virtual Power Playersmentioning

confidence: 99%

“…MAS is an appropriate platform for implementing the smart grid concepts, because it provides intelligent decision making and adaptive local control (Oliveira et al, 2012). …”

Section: Proposed Multi-agent-based Schemementioning

confidence: 99%

“…The proposed approach is integrated with MASGriP (Oliveira et al, 2012), a smart grid environment simulator, which provides an interface with the MASCEM (Multi-Agent Simulator for Competitive Electricity Markets) (Vale et al, 2011b), a system that models the electricity markets, using real data in order to test and validate the proposed approach.…”

Section: Introductionmentioning

confidence: 99%

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Multiagent System Architecture for Short-term Operation of Integrated Microgrids

Ghazvini

Abedini

Pinto

et al. 2014

IFAC Proceedings Volumes

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Abstract:The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid's internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

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