A 57mW 10-bit 80-MS/s pipeline ADC adopting improved power optimization approach

Author(s):  
Bo Li ◽  
Zheying Li ◽  
Yuemei Li ◽  
Chunlei Wang
Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1796
Author(s):  
Francesco Castellani ◽  
Davide Astolfi

This Special Issue collects innovative contributions in the field of wind turbine optimization technology. The general motivation of the present Special Issue is given by the fact that there has recently been a considerable boost of the quest for wind turbine efficiency optimization in the academia and in the wind energy practitioners communities. The optimization can be focused on technology and operation of single turbine or a group of machines within a wind farm. This perspective is evidently multi-faced and the seven papers composing this Special Issue provide a representative picture of the most ground-breaking state of the art about the subject. Wind turbine power optimization means scientific research about the design of innovative aerodynamic solutions for wind turbine blades and of wind turbine single or collective control, especially for increasing rotor size and exploitation in offshore environment. It should be noticed that some recently developed aerodynamic and control solutions have become available in the industry practice and therefore an interesting line of development is the assessment of the actual impact of optimization technology for wind turbines operating in field: this calls for non-trivial data analysis and statistical methods. The optimization approach must be 360 degrees; for this reason also offshore resource should be addressed with the most up to date technologies such as floating wind turbines, in particular as regards support structures and platforms to be employed in ocean environment. Finally, wind turbine power optimization means as well improving wind farm efficiency through innovative uses of pre-existent control techniques: this is employed, for example, for active control of wake interactions in order to maximize the energy yield and minimize the fatigue loads.


2019 ◽  
Vol 28 (6) ◽  
pp. 1144-1151
Author(s):  
Zhenxue HE ◽  
Limin XIAO ◽  
Zhisheng HUO ◽  
Chao WANG ◽  
Jia LIU ◽  
...  

Author(s):  
Saloua Belaid ◽  
Djamila Rekioua ◽  
Adel Oubelaid ◽  
Djamel Ziane ◽  
Toufik Rekioua

This paper contributes to the feasibility of a wind turbine/battery system with a hybrid power optimization controller. The proposed method is based on a mathematical optimization approach and allows to achieve an efficient operation of the maximum power point tracking (MPPT) algorithms to obtain an optimal performance level of the wind system and a minimal stress on the battery storage. The different powers have been controlled by a power management control (PMC) method. The objectives of the PMC based are, in first part to satisfy the load power demand and in second part to maintain the state of charge of the battery bank to prevent blackout and to extend the batteries life. A measurement of wind speeds was made during a whole day using a data acquisition system at the laboratory. Also, the different wind turbine parameters were identified at the same Laboratory. All these parameters have been used in simulation models in order to obtain the most realistic mathematical models that are close to the experiment. Real time simulation is performed using RT LAB simulator and the obtained results were matching those obtained in numerical simulation using Matlab/Simulink. The obtained results under two different wind speed profile, with the different comparisons are presented to show the feasibility and the improvement of the proposed study in terms of power, efficiency, time response and effect on battery state of charge under two different wind speeds profile.


2020 ◽  
Vol 54 (6) ◽  
pp. 1703-1722 ◽  
Author(s):  
Narges Soltani ◽  
Sebastián Lozano

In this paper, a new interactive multiobjective target setting approach based on lexicographic directional distance function (DDF) method is proposed. Lexicographic DDF computes efficient targets along a specified directional vector. The interactive multiobjective optimization approach consists in several iteration cycles in each of which the Decision Making Unit (DMU) is presented a fixed number of efficient targets computed corresponding to different directional vectors. If the DMU finds one of them promising, the directional vectors tried in the next iteration are generated close to the promising one, thus focusing the exploration of the efficient frontier on the promising area. In any iteration the DMU may choose to finish the exploration of the current region and restart the process to probe a new region. The interactive process ends when the DMU finds its most preferred solution (MPS).


Sign in / Sign up

Export Citation Format

Share Document