MARTINE—A Platform for Real-Time Energy Management in Smart Grids

Author:

Vale ZitaORCID,Faria PedroORCID,Abrishambaf OmidORCID,Gomes LuisORCID,Pinto TiagoORCID

Abstract

This paper presents MARTINE (Multi-Agent based Real-Time INfrastruture for Energy), a simulation, emulation and energy management platform for the study of problems related to buildings and smart grids. Relevant advances related to buildings and smart grid management and operation have been proposed, focusing either on software models for decision support or on physical infrastructure and control approaches. These two perspectives are, however, complementary, and no practical assessment can be achieved without a suitable interaction and analysis of the impact that decision-making models have on physical resources, and vice-versa. MARTINE overcomes this limitation by integrating, in a single platform: real buildings with the associated devices and resources; emulated components that complement the ones present in the buildings; simulated resources, players and buildings using multi-agent systems, real-time simulation with hardware in the loop capabilities, which enables integrating virtual and physical components; and a knowledge layer that incorporates all the required decision support and energy management models. MARTINE thus provides a comprehensive platform for the study and management of energy resources. The advantages of this platform are demonstrated in this paper through three use cases, related to agriculture irrigation, practical implementation of demand response and load modeling using various network configurations.

Funder

Fundação para a Ciência e a Tecnologia

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MARTINE’s real-time local market simulation with a semantically interoperable society of multi-agent systems;Sustainable Energy, Grids and Networks;2023-03

2. Multi-agent system implementation in demand response: A literature review and bibliometric evaluation;AIMS Energy;2023

3. Dataset of an energy community's generation and consumption with appliance allocation;Data in Brief;2022-12

4. CPU Computation Influence on Energy Consumption Forecasting Activities of a Building;Lecture Notes in Networks and Systems;2022-10-12

5. Energy Forecast in Buildings Addressing Computation Consumption in a Green Computing Approach;2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe);2022-06-28

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