• Title/Summary/Keyword: Operating optimization

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Optimal air-conditioning system operating control strategies in summer (여름철 공조시스템의 최적 운전 제어 방식)

  • Huh, J.H.
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.9 no.3
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    • pp.410-425
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    • 1997
  • Buildings are mostly under part load conditions causing an inefficient system operation in terms of energy consumption. It is critical to operate building air-conditioning system with a scientific or optimal manner which minimizes energy consumption and maintains thermal comfort by matching building sensible and latent loads. Little research has been performed in developing general methodologies for the optimal operation of air-conditioning system. Based on this research motivation, system simulation program was developed by adopting various equipment operating strategies which are energy efficient especially for humidity control in summer. A numerical optimization technique was utilized to search optimal solution for multi-independent variables and then linked to the developed system simulation model within a mam program. The main goal of the study is to provide a systematic framework and guideline for the optimal operation of air-conditioning system focusing on air-side. For given cooling loads and ambient outdoor conditions the optimal operating strategies of a commercial building are determined by minimizing a constrained objective function by a nonlinear programming technique. Desired space setpoint conditions were found through evaluating the trade-offs between comfort and system power consumption. The results show that supply airflow rate and compressor fraction play main roles in the optimization process. It was found that variable setpoint optimization technique could produce lower indoor humidity level demanding less power consumption which will be benefits for building applications of humidity problem.

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Study on Optimization of Operating Conditions for High Temperature PEM Fuel Cells Using Design of Experiments (실험계획법을 이용한 고온 고분자 전해질 막 연료전지의 운전조건 최적화 연구)

  • Kim, Jintae;Kim, Minjin;Sohn, Youngjun
    • Transactions of the Korean hydrogen and new energy society
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    • v.24 no.1
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    • pp.50-60
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    • 2013
  • High temperature proton exchange membrane fuel cells (PEMFCs) using phosphoric acid (PA) doped polybenzimidazole (PBI) membranes have been concentrated as one of solutions to the limits with traditional low temperature PEMFCs. However, the amount of reported experimental data is not enough to catch the operational characteristics correlated with cell performance and durability. In this study, design of experiments (DOE) based operational optimization method for high temperature PEMFCs has been proposed. Response surface method (RSM) is very useful to effectively analyze target system's characteristics and to optimize operating conditions for a short time. Thus RSM using central composite design (CCD) as one of methodologies for design of experiments (DOE) was adopted. For this work, the statistic models which predict the performance and degradation rate with respect to the operating conditions have been developed. The developed performance and degradation models exhibit a good agreement with experimental data. Compared to the existing arbitrary operation, the expected cell lifetime and average cell performance during whole operation could be improved by optimizing operating conditions. Furthermore, the proposed optimization method could find different new optimal solutions for operating conditions if the target lifetime of the fuel cell system is changed. It is expected that the proposed method is very useful to find optimal operating conditions and enhance performance and durability for many other types of fuel cell systems.

Efficiency Optimization Control of SynRM with ANN Speed Estimation (ANN의 속도 추정에 의한 SynRM의 효율 최적화 제어)

  • Choi, Jung-Sik;Ko, Jae-Sub;Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.55 no.3
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    • pp.133-140
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    • 2006
  • This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor(SynRM) which minimizes the copper and iron losses. Also, this paper presents a speed estimated control scheme of SynRM using artificial neural network(ANN). There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of ANN is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

An Improved Particle Swarm Optimization for Economic Dispatch Problems with Prohibited Operating Zones (경제급전 문제에의 개선된 PSO 알고리즘 적용)

  • Jeong, Yun-Won;Lee, Woo-Nam;Kim, Hyun-Houng;Park, Jong-Bae;Shin, Joong-Rin
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.850-851
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    • 2007
  • This paper presents an efficient approach for solving the economic dispatch (ED) problems with prohibited operating zones using an improved particle swarm optimization (PSO). Although the PSO-based approaches have several advantages suitable to the heavily constrained nonconvex optimization problems, they still have the drawbacks such as local optimal trapping due to the premature convergence (i.e., exploration problem) and insufficient capability to find nearly-by extreme points (i.e., exploitation problem). This paper proposes an improved PSO framework adopting a crossover operation scheme to increase both exploration and exploitation capability of the PSO. The proposed method is applied to ED problem with prohibited operating zones. Also, the results are compared with those of the state-of-the-art methods.

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Optimization of the Operating Stiffness of a Two-Axis Parallel Robot (2축 병렬로봇의 작동강성 최적설계)

  • Lee, Jae-Wook;Jang, Jin-Seok;Lee, Sang-Kon;Jeong, Myeong-Sik;Cho, Yong-Jae;Kim, Kun-Woo;Yoo, Wan-Suk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.6
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    • pp.561-566
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    • 2015
  • In this paper, the operating stiffness of a parallel robot used to handle heavy packages is optimized. Because the studied model, called a "pick and place robot," is applied for packaging logistics, it is important for the robot to be lightweight so that it may respond rapidly and have high stiffness to allow sufficient operating precision. However, these two requirements of low weight and high stiffness are mutually exclusive. Thus, the dynamic characteristics of the robot are analyzed through multibody dynamics analysis, and topology optimization is conducted to achieve this exclusive performance. Lastly, the reliability of the topology optimization is verified by applying the optimized design to the parallel robot.

Economic Profit Analysis for Centralized Operation of Economic Load Dispatch Problem (경제급전문제의 통합운영에 관한 경제적 이득 분석)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.181-188
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    • 2016
  • This paper demonstrates that centralized economic load dispatch optimization is much more economical than independent optimization carried out by individual power generating companies. The algorithm applied here optimizes by balancing the generation power at the valve-point, then readjusting generation power by comparing incremental operating cost incurred by marginal increase in the generation power and decremental operating cost likewise incurred by marginal decrease in the generation power. Upon comparing 3 individual optimization cases of 10, 13, and 40 generators respectively with centralized optimization of 63 generators, centralized operation for economic load dispatch optimization has proven to maximize economic benefits by markedly reducing operation costs of individual optimization.

A multi-level approach for the optimization of an ultrafiltration plant processing surface water

  • Zondervan, E.;Roffel, B.
    • Membrane and Water Treatment
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    • v.1 no.1
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    • pp.61-74
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    • 2010
  • This paper will integrate models at different levels (from filtration, backwashing to chemical cleaning and membrane lifetime) that can be used to minimize overall operating costs of a dead-end ultra filtration process that is used for the purification of surface water. Integration of the models leads to a multi-level optimization problem (at different levels different objectives should be reached). This problem is solved as a MINLP. Systematic modelling and optimization of membrane systems is not extensively discussed in the scientific literature. In this paper the first steps are taken in the formulation of proper models and the use of systems engineering tools to come to real optimal operating conditions. The optimized variables are used to calculate fouling profiles which can subsequently be used as inputs for a control system that actually enforces the profiles to a real pilot plant.

Automated optimization for memory-efficient high-performance deep neural network accelerators

  • Kim, HyunMi;Lyuh, Chun-Gi;Kwon, Youngsu
    • ETRI Journal
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    • v.42 no.4
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    • pp.505-517
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    • 2020
  • The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high-performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high-performance accelerators along with dataflow control. Furthermore, the processing of various neural networks (NNs) requires a flexible memory architecture, programmable control scheme, and automated optimizations. We first propose an efficient architecture with flexibility while operating at a high frequency despite the large memory and PE-array sizes. We then improve the efficiency and usability of our architecture by automating the optimization algorithm. The experimental results show that the architecture increases the data reuse; a diagonal write path improves the performance by 1.44× on average across a wide range of NNs. The automated optimizations significantly enhance the performance from 3.8× to 14.79× and further provide usability. Therefore, automating the optimization as well as designing an efficient architecture is critical to realizing high-performance DNN accelerators.

A Novel Efficiency Optimization Strategy of IPMSM for Pump Applications

  • Zhou, Guangxu;Ahn, Jin-Woo
    • Journal of Electrical Engineering and Technology
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    • v.4 no.4
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    • pp.515-520
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    • 2009
  • According to the operating characteristics of pump applications, they should exhibit high efficiency and energy saving capabilities throughout the whole operating process. A novel efficiency optimization control strategy is presented here to meet the high efficiency demand of a variable speed Permanent Magnet Synchronous Motor (PMSM). The core of this strategy is the excellent integration of mended maximum torque to the current control algorithm, based on the losses model during the dynamic and the grade search method with changed step by fuzzy logic during the steady. The performance experiments for the control system of a variable speed high efficiency PMSM have been completed. The test results verified that the system can reliably operate with a different control strategy during dynamic and steady operation, and the system exhibits better performance when using the efficiency-optimization control.

Improved Performance of Permanent Magnet Synchronous Motor by using Particle Swarm Optimization Techniques

  • Elwer, A.S.;Wahsh, S.A.
    • Journal of Power Electronics
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    • v.9 no.2
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    • pp.207-214
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    • 2009
  • This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.