Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

Caianiello, Pasquale; Costantini, Stefania; Gasperis, Giovanni De; Lorenzo, Mario Gimenez De

doi:10.1007/978-3-319-00551-5_71

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…The proposed approach has also been experimented in the context of energy management in smart buildings [123]. In this application domain, forms of intelligent control are needed which are dynamic by nature, and must fulfil real-time requirements: in fact, each building has its own dynamic thermo-physical behaviour and is immersed in a dynamic environment where weather events change its energy 'footprint' in function of time.…”

Section: Other Related Work and Concluding Remarksmentioning

confidence: 99%

Ensuring trustworthy and ethical behaviour in intelligent logical agents

Costantini

2022

Journal of Logic and Computation

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Autonomous intelligent agents are employed in many applications upon which the life and welfare of living beings and vital social functions may depend. Therefore, agents should be trustworthy. A priori certification techniques (i.e. techniques applied prior to system’s deployment) can be useful, but are not sufficient for agents that evolve, and thus modify their epistemic and belief state, and for open multi-agent systems, where heterogeneous agents can join or leave the system at any stage of its operation. In this paper, we propose/refine/extend dynamic (runtime) logic-based self-checking techniques, devised in order to be able to ensure agents’ trustworthy and ethical behaviour.

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Section: Other Related Work and Concluding Remarksmentioning

confidence: 99%

Ensuring trustworthy and ethical behaviour in intelligent logical agents

Costantini

2022

Journal of Logic and Computation

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“…In a preliminary work [23] we argue that the prosumer forecaster could be implemented with any suitable machine learning approach, where we proposed and experimented using a neural net to predict energy consumption that showed good performance, given the relative smoothness of the response of the system to changes.…”

Section: Case Studymentioning

confidence: 99%

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

Caianiello¹,

Costantini²,

Gasperis³

et al. 2013

IJIMAI

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We outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. We present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval.

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Modelling and control of multi-energy systems through Multi-Prosumer Node and Economic Model Predictive Control

Blaud

Haurant

Claveau

et al. 2020

International Journal of Electrical Power & Energy Systems

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The present study deals with Multi-Energy Systems (MES) modelling and advanced control with Economic Model Predictive Control (EMPC). MES provide energy flexibility, efficiency, and adaptability thanks to several energy carriers. MES are identified as a lever for integrating renewable energy. A MES novel formulation technique called Multi-Prosumer Node (MPN) is developed in this paper. MPN makes possible the modeling of MES, considering MES dynamics, several energy carriers, converters, on-grid, and off-grid. In addition, this MES modeling approach is compatible with predictive control strategies like the EMPC. In fact, EMPC is able to take into account loads, weather, renewable power and energy grid cost predictions to minimise economic costs. A real case study is implemented to examine MPN capabilities, which it is composed of renewable generators, loads, storages from two-energy carriers. Two real scenarios have been developed in order to represent realistic winter and summer cases. Simulation results, thanks to modelling with MPN and EMPC advanced control, demonstrate that the node is optimally controlled, devices dynamics are considered on a minute scale, and energy conversion from one carrier to another one is taken into account while economic cost minimisation is performed. The gained results indicate that the presented MPN modelling and optimisation approach reduces economic cost by 8.21% in winter case and 84.24% in summer case compared to the benchmarks which are composed of rule-based control.

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Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

Cited by 6 publications

References 19 publications

Ensuring trustworthy and ethical behaviour in intelligent logical agents

Ensuring trustworthy and ethical behaviour in intelligent logical agents

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

Modelling and control of multi-energy systems through Multi-Prosumer Node and Economic Model Predictive Control

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