Protocol conversion for real-time energy management systems

Author(s):  
A.F.J. von Gordon ◽  
G.P. Hancke
2017 ◽  
Vol 143 ◽  
pp. 624-633 ◽  
Author(s):  
Mousa Marzband ◽  
Seyedeh Samaneh Ghazimirsaeid ◽  
Hasan Uppal ◽  
Terrence Fernando

2014 ◽  
Vol 659 ◽  
pp. 395-400 ◽  
Author(s):  
Ciprian Lapusan ◽  
Radu Balan ◽  
Olimpiu Hancu ◽  
Ciprian Rad

The article investigates the development of home energy management systems based on real-time control algorithms and online identification. The proposed system optimizes the energy consumption for heating and cooling of a household using model predictive control strategies. The virtual prototype of the energy management system is developed, simulated and optimized using Matlab/Simulink. The simulated system is then implemented using dSpace platform and rapid control prototyping on real-time hardware and tested on a laboratory surrogate system. The system performance is evaluated by comparing the results with the response of classic systems used for heating and cooling in domestic houses. The obtained results confirmed the viability of the proposed solution in home energy management systems.


2020 ◽  
Vol 45 (1) ◽  
pp. 203-219
Author(s):  
Wilson L. Rodrigues Junior ◽  
Fabbio A. S. Borges ◽  
Ricardo de A. L. Rabelo ◽  
Joel J. P. C. Rodrigues ◽  
Ricardo A. S. Fernandes ◽  
...  

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4260 ◽  
Author(s):  
Alessandro Serpi ◽  
Mario Porru

Modelling and design of real-time energy management systems for optimising the operating costs of a fuel cell/battery electric vehicle are presented in this paper. The proposed energy management system consists of optimally sharing the propulsion power demand between the fuel cell and battery by enabling them to support each other for operating cost minimisation. The optimisation is achieved through real-time minimisation of a cost function, which accounts for fuel cell and battery degradation, hydrogen consumption and charge sustaining costs. A detailed analysis of each term of the overall cost function is performed and presented, which enables the development of a real-time, advanced energy management system for improving a previously presented simplified version using more accurate modelling and by considering cost function minimisation over a given time horizon. The performance of the proposed advanced energy management system are verified through numerical simulations over different driving cycles; particularly, simulations were performed in MATLAB-Simulink by considering a hysteresis-based energy management system and both simplified and advanced versions of the proposed energy management system for comparison.


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