A new control strategy for energy-saving dynamic voltage restoration

Author(s):  
B.H. Li ◽  
S.S. Choi ◽  
D.M. Vilathgamuwa
2020 ◽  
Vol 42 (1) ◽  
pp. 62-81
Author(s):  
Yanhuan Ren ◽  
Junqi Yu ◽  
Anjun Zhao ◽  
Wenqiang Jing ◽  
Tong Ran ◽  
...  

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.


2018 ◽  
Vol 3 (4) ◽  
pp. 595-606 ◽  
Author(s):  
Yingjie Zhang ◽  
Ying Zhang ◽  
Zhaoyang Ai ◽  
Yun Feng ◽  
Wei Cheng ◽  
...  

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1794
Author(s):  
Luis Ramon Merchan-Villalba ◽  
Jose Merced Lozano-Garcia ◽  
Juan Gabriel Avina-Cervantes ◽  
Hector Javier Estrada-Garcia ◽  
Alejandro Pizano-Martinez ◽  
...  

This paper presents the design of a decoupled linear control strategy for a Dynamic Voltage Restorer (DVR) that utilizes a Matrix Converter (MC) as its core element and obtains the compensation energy directly from the power system. This DVR is intended to cope with power quality problems present in supply system voltages such as balanced and unbalanced variations (sags and swells), and harmonic distortion. The dynamic model of the complete system that includes the Matrix Converter, the input filters and the electrical grid, is performed in the synchronous reference frame (dq0), to have constant signals at the fundamental frequency, in order to design the proposed linear control strategy. The coupling in the dq components of the system output signals caused by the Park Transformation, is eliminated by a change of variable proposed for the controller design, giving rise to a decoupled linear control. In this way, the strategy developed makes it possible to establish an adequate transient response for the converter in terms of convergence speed and overshoot magnitude, in addition to ensuring closed-loop system stability under bounded operating conditions. Unlike other proposals that utilize complex modulation strategies to control the MC under adverse conditions at the input terminals, in this case, the ability to generate fully controllable output voltages, regardless of the condition of the input signals, is provided by the designed linear controller. This allows the development of a multifunctional compensator with a simple control that could be of easy implementation. In order to verify the performance of the control strategy developed, and the effectiveness of the proposed DVR to mitigate the power quality problems already mentioned, several case studies are presented. The operational capacity of the MC is demonstrated by the obtained simulation results, which clearly reveals the capability of the DVR to eliminate voltage swells up to 50% and sags less than 50%. The compensation limit reached for sags is 37%. In relation to compensation for unbalanced voltage variations, the DVR manages to reduce the voltage imbalance from 11.11% to 0.37%. Finally, with regard to the operation of the DVR as an active voltage filter, the compensator is capable of reducing a THD of 20% calculated on the supply voltage, to a value of 1.53% measured at the load terminals. In the last two cases, the DVR mitigates disturbances to a level below the criteria established in the IEEE standard for power quality. Results obtained from numerical simulations performed in MATLAB/Simulink serve to validate the proposal, given that for each condition analyzed, the MC had succesfully generated the adequate compensation voltages, thus corroborating the robustness and effectiveness of the control strategy developed in this proposal.


2007 ◽  
Vol 16 (05) ◽  
pp. 745-767
Author(s):  
SUMITKUMAR N. PAMNANI ◽  
DEEPAK N. AGARWAL ◽  
GANG QU ◽  
DONALD YEUNG

Performance-enhancement techniques improve CPU speed at the cost of other valuable system resources such as power and energy. Software prefetching is one such technique, tolerating memory latency for high performance. In this article, we quantitatively study this technique's impact on system performance and power/energy consumption. First, we demonstrate that software prefetching achieves an average of 36% performance improvement with 8% additional energy consumption and 69% higher power consumption on six memory-intensive benchmarks. Then we combine software prefetching with a (unrealistic) static voltage scaling technique to show that this performance gain can be converted to an average of 48% energy saving. This suggests that it is promising to build low power systems with techniques traditionally known for performance enhancement. We thus propose a practical online profiling based dynamic voltage scaling (DVS) algorithm. The algorithm monitors system's performance and adapts the voltage level accordingly to save energy while maintaining the observed system performance. Our proposed online profiling DVS algorithm achieves 38% energy saving without any significant performance loss.


2015 ◽  
Vol 59 ◽  
pp. 268-279 ◽  
Author(s):  
Keivan Baghestan ◽  
Seyed Mehdi Rezaei ◽  
Heidar Ali Talebi ◽  
Mohammad Zareinejad

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