Synchronous Generator Excitation System Optimization Control Based on Multi-agent Genetic Algorithm

2013 ◽  
Vol 12 (19) ◽  
pp. 4959-4967
Author(s):  
Ruofa Cheng ◽  
Jianchao Gao ◽  
Xinhong Yu ◽  
Hongfeng Deng
Keyword(s):  
Genetic Algorithm ◽  
Synchronous Generator ◽  
System Optimization ◽  
Excitation System ◽  
Optimization Control ◽  
Multi Agent ◽  
Synchronous Generator Excitation

Study on Large Capacity 4-Pole Synchronous Generator Excitation System

2016 ◽  
Vol 136 (1) ◽  
pp. 18-24
Author(s):  
Daisuke Hiramatsu ◽  
Yoichi Uemura ◽  
Dai Nozaki ◽  
Shinji Mukoyama ◽  
Kazuma Tsujikawa ◽  
...  
Keyword(s):  
Synchronous Generator ◽  
Excitation System ◽  
Large Capacity ◽  
Synchronous Generator Excitation

scholarly journals Heating, Ventilation, and Air Conditioning System Optimization Control Strategy Involving Fan Coil Unit Temperature Control

2019 ◽  
Vol 9 (11) ◽  
pp. 2391 ◽  
Author(s):  
Chang-Ming Lin ◽  
Hsin-Yu Liu ◽  
Ko-Ying Tseng ◽  
Sheng-Fuu Lin
Keyword(s):  
Genetic Algorithm ◽  
Energy Conservation ◽  
Temperature Control ◽  
Control Strategy ◽  
Air Conditioning ◽  
Minimum Energy ◽  
System Optimization ◽  
Hvac System ◽  
Minimum Energy Consumption ◽  
Optimization Control

The objective of this study was to develop a heating, ventilation, and air conditioning (HVAC) system optimization control strategy involving fan coil unit (FCU) temperature control for energy conservation in chilled water systems to enhance the operating efficiency of HVAC systems. The proposed control strategy involves three techniques, which are described as follows. The first technique is an algorithm for dynamic FCU temperature setting, which enables the FCU temperature to be set in accordance with changes in the outdoor temperature to satisfy the indoor thermal comfort for occupants. The second technique is an approach for determining the indoor cold air demand, which collects the set FCU temperature and converts it to the refrigeration ton required for the chilled water system; this serves as the control target for ensuring optimal HVAC operation. The third technique is a genetic algorithm for calculating the minimum energy consumption for an HVAC system. The genetic algorithm determines the pump operating frequency associated with minimum energy consumption per refrigeration ton to control energy conservation. To demonstrate the effectiveness of the proposed HVAC system optimization control strategy combining FCU temperature control, this study conducted a field experiment. The results revealed that the proposed strategy enabled an HVAC system to achieve 39.71% energy conservation compared with an HVAC system operating at full load.

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