Distributed Control Strategy with Smith's Predictor in a Pilot‐Scale Diabatic Distillation Unit

2020 ◽  
Vol 43 (9) ◽  
pp. 1884-1896 ◽  
Author(s):  
Elton Joao Zierhut ◽  
Rodrigo Battisti ◽  
Ricardo Antonio Francisco Machado ◽  
Cintia Marangoni
Keyword(s):  
Distributed Control ◽  
Control Strategy ◽  
Pilot Scale ◽  
Distillation Unit ◽  
Diabatic Distillation

Techno-economic and energetic assessment of an innovative pilot-scale thermosyphon-assisted falling film distillation unit for sanitizer-grade ethanol recovery

2021 ◽  
Vol 297 ◽  
pp. 117185
Author(s):  
Rodrigo Battisti ◽  
Andrea Galeazzi ◽  
Kristiano Prifti ◽  
Flavio Manenti ◽  
Ricardo Antonio Francisco Machado ◽  
...  
Keyword(s):  
Pilot Scale ◽  
Distillation Unit ◽  
Falling Film ◽  
Ethanol Recovery

Machine learning modeling and genetic algorithm-based optimization of a novel pilot-scale thermosyphon-assisted falling film distillation unit

2021 ◽  
Vol 259 ◽  
pp. 118122
Author(s):  
Rodrigo Battisti ◽  
Carlos Alberto Claumann ◽  
Flavio Manenti ◽  
Ricardo Antonio Francisco Machado ◽  
Cintia Marangoni
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Pilot Scale ◽  
Distillation Unit ◽  
Falling Film

scholarly journals Hierarchical Distributed Control Strategy for Electric Vehicle Mobile Energy Storage Clusters

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1195 ◽  
Author(s):  
Mei Wu ◽  
Yu-Qing Bao ◽  
Gang Chen ◽  
Jinlong Zhang ◽  
Beibei Wang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Power System ◽  
Distributed Control ◽  
Control Strategy ◽  
Optimal Allocation ◽  
Lower Layer ◽  
Power Grid ◽  
Consensus Algorithm ◽  
Renewable Energy Resources ◽  
Storage Unit

The stability problem of the power system becomes increasingly important for the penetration of renewable energy resources (RESs). The inclusion of electric vehicles (EVs) in a power system can not only promote the consumption of RESs, but also provide energy for the power grid if necessary. As a mobile energy storage unit (MESU), EVs should pay more attention to the service life of their batteries during operation. A hierarchical distributed control strategy was proposed in this paper for mobile energy storage clusters (MESCs) considering the life loss of each EV’s battery. This strategy was divided into a two-layer control structure. Firstly, numerous EVs were divided into different clusters according to their regional relationships. The lower layer adopted a distributed collaborative control approach for allocating energy among EVs in the cluster. Under this condition, an aggregate EVs response model was established and the characteristic of the MESC was analyzed. Secondly, the upper layer applied the multi-agent consensus algorithm to achieve the optimal allocation among different clusters. Therefore, the control strategy realized the two-way communication of energy between EVs and the power grid, and ensured the optimal economical dispatch for the mobile energy storage system (MESS). Finally, the simulation of testing examples verified the effectiveness of the proposed strategy.

scholarly journals Distributed Control Strategy for Smart Home Appliances Considering the Discrete Response Characteristics of the On/Off Loads

2019 ◽  
Vol 9 (3) ◽  
pp. 457 ◽  
Author(s):  
De-Yin Kong ◽  
Yu-Qing Bao ◽  
Ying-Yi Hong ◽  
Bei-Bei Wang ◽  
Hong-Bin Huang ◽  
...  
Keyword(s):  
Distributed Control ◽  
Control Strategy ◽  
Smart Home ◽  
Control Method ◽  
Consensus Algorithm ◽  
Centralized Control ◽  
Response Characteristics ◽  
Fitting Method ◽  
Discrete Response ◽  
Smart Home Appliances

With the development of smart home technology, more and more electrical appliances can participate in demand response, providing support for active power balance of the power grid. However, the conventional centralized control method faces vast amounts of electrical appliances, resulting in problems such as communication congestion and dimension curse. This paper proposes a distributed control strategy for electrical appliances based on a multi-agent consensus algorithm. Considering the discrete response characteristics of the on/off loads, a priority ranking mechanism is established, and the customer cost function is established by a fitting method. Based on the incremental cost consensus (ICC) algorithm, the optimal power allocation of customers is realized through distributed control. Simulation and analysis of the examples verify the effectiveness of the proposed strategy.

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