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Journal articles on the topic 'Real load'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Gan, Lingwen, Adam Wierman, Ufuk Topcu, Niangjun Chen, and Steven H. Low. "Real-time deferrable load control." ACM SIGMETRICS Performance Evaluation Review 41, no. 3 (January 10, 2014): 77–79. http://dx.doi.org/10.1145/2567529.2567553.

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2

Smith, R. A., and R. D. Shultz. "Real time bus load processing." Electric Power Systems Research 16, no. 3 (May 1989): 237–44. http://dx.doi.org/10.1016/0378-7796(89)90016-3.

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3

Stucchi, Fernando Rebouças, and Lorenzo Augusto Ruschi e. Luchi. "Real road load compared to standard load for Brazilian bridges." Proceedings of the Institution of Civil Engineers - Bridge Engineering 168, no. 3 (September 2015): 245–58. http://dx.doi.org/10.1680/jbren.13.00028.

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4

Stucchi, Fernando Rebouças, and Lorenzo Augusto Ruschi e. Luchi. "Real road load compared to standard load for Brazilian bridges." Proceedings of the ICE - Bridge Engineering 168, no. 3 (September 1, 2015): 245–58. http://dx.doi.org/10.1680/bren.13.00028.

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5

Mamat, Anwar, Ying Lu, Jitender Deogun, and Steve Goddard. "Efficient real-time divisible load scheduling." Journal of Parallel and Distributed Computing 72, no. 12 (December 2012): 1603–16. http://dx.doi.org/10.1016/j.jpdc.2012.09.003.

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6

Risholt, L. P., W. Schilling, V. Erbe, and J. Alex. "Pollution based real time control of wastewater systems." Water Science and Technology 45, no. 3 (February 1, 2002): 219–28. http://dx.doi.org/10.2166/wst.2002.0082.

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Wastewater systems are traditionally built as static systems to handle a design load. The real load varies, though, and hardly ever equals the design load. This implies that wastewater systems hardly ever operate in an optimum way, especially during wet weather. Real time control (RTC) of regulators can improve the operation by better fit of the system to the actual state and load. RTC based on pollutant concentrations together with hydraulic conditions (pollution based real time control, PBRTC) is investigated in this paper to assess the potential pollutant load reduction on receiving waters at wet weather without expansion of transport or storage capacity. Both CSOs and WWTP effluents contribute to the pollutant discharges to receiving waters and both are considered. Three cases are studied to assess the potential benefit of PBRTC. Giving priority to the most polluted wastewater for treatment and storage in branched interceptor systems can reduce CSO discharge loads by more than 20%. Biological WWTPs and especially activated sludge plants are more complex and less stable than chemical precipitation plants during and after high pollutant and hydraulic load. Biological plants can hence profit more from PBRTC than chemical precipitation plants. Receiving waters that are sensitive to acute effects caused by intermittent discharges can benefit more from PBRTC than receiving waters with problems connected to long-term accumulation of pollution.

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7

Saied, M. M. "The real cost of air conditioning load." IEEE Industry Applications Magazine 5, no. 5 (1999): 42–46. http://dx.doi.org/10.1109/2943.783121.

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8

Bestavros, Azer. "Load profiling in distributed real-time systems." Information Sciences 101, no. 1-2 (September 1997): 1–27. http://dx.doi.org/10.1016/s0020-0255(97)00040-6.

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9

Mayer, Wolfgang, Jochen Wiedemann, and Jens Neubeck. "Road load determination in real road tests." ATZ worldwide 104, no. 5 (May 2002): 18–21. http://dx.doi.org/10.1007/bf03224561.

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10

Shah, Kirti, Mateo San Miguel, Rick Hofstetter, and Mark Tiffany. "Load preservation systems - Real-time cogeneration source protection of critical utility loads." IEEE Industry Applications Magazine 13, no. 5 (September 2007): 31–37. http://dx.doi.org/10.1109/mia.2007.901384.

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11

Liu, Dunnan, Pengfei Li, Xiaofeng Xu, Yiding Jin, Shanzhe Shi, Shilin Li, and Jinshan Han. "Ultra-short-term Load Forecasting Based on Real-Time Response of Classified Flexible Loads." E3S Web of Conferences 165 (2020): 03048. http://dx.doi.org/10.1051/e3sconf/202016503048.

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Ultra-short-term load forecasting is an important basis for optimization and adjustment of power generation plans and dispatch plans. Based on the radial basis function neural network, the inert load is predicted, and the flexible load is predicted based on the price elasticity of electricity demand. Then, combined with the range of the flexible load, an ultra-short-term forecast interval for the total load is constructed. This paper studies the total load after considering the flexible load for demand response, and verifies the feasibility of the proposed method with an example.

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12

Shahid, Syed Maaz, Sunghoon Ko, and Sungoh Kwon. "Real-Time Classification of Diesel Marine Engine Loads Using Machine Learning." Sensors 19, no. 14 (July 18, 2019): 3172. http://dx.doi.org/10.3390/s19143172.

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An engine control system is responsible for controlling the combustion parameters of an internal combustion engine to increase the efficiency of the engine. An optimized parameter setting of an engine control system is highly influenced by the engine load. Therefore, with a change in engine load, the parameter settings need to be updated for higher engine efficiency. Hence, to optimize parameter settings during operation, engine load information is necessary. In this paper, we propose a real-time engine load classification from sensed signals. For the classification, an artificial neural network is used and trained using processed, real, measured data. To that end, a magnetic pickup sensor extracts the rotational speed of the prime mover of a four-stroke V12 marine diesel engine. The measured signal is then converted into a crank angle degree (CAD) signal that shows the behavior of the combustion strokes of firing cylinders at a particular engine load. The CAD signals are considered an input feature to the designed network for classification of engine loads. For verification, we considered five classes of engine load, and the trained network classifies these classes with an accuracy of 99.4%.

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13

Jain, Monika, Sushma Gupta, Deepika Masand, Gayatri Agnihotri, and Shailendra Jain. "Real-Time Implementation of Islanded Microgrid for Remote Areas." Journal of Control Science and Engineering 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/5710950.

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Islanding is a condition in which a microgrid or a portion of power grid, consisting of distributed generation (DG) sources, converter, and load, gets disconnected from the utility grid. Under this condition the DG sources in a microgrid must switch to a voltage control mode, in order to provide constant voltage to local loads. In grid connected mode, the microgrid works as current controller and injects power to the main grid, depending on the power generation and local load with suitable market policies. Providing constant voltage at a stable frequency with proper synchronization amongst each DG in a microgrid is a challenge. The complexity of such grid requires careful study and analysis before actual implementation. These challenges of microgrid are addressed using real time OPAL-RT simulation technology. Thus the paper describes an islanded microgrid with master slave controller for power balance, voltage/frequency regulation, and synchronization. Based on an advanced real-time platform named Real-Time Laboratory (RT-LAB), the impacts of the micro sources, load, and converters in an islanded microgrid is studied in this paper. The effectiveness of the proposed controller is analyzed through experimental results under balanced/unbalanced nonlinear loads condition.

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14

Liu, Ting Zhang, An Hong Gong, and Li Xia Yao. "A Real-Time Experimental Method for Room Cooling Load Calculations." Advanced Materials Research 433-440 (January 2012): 4490–95. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4490.

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A real-time experimental method for room cooling load calculations is developed in this paper. Experimental based study was also performed during summer months of 2010 in a reference office room in Shanghai. Hourly indoor temperature curves were drawn and the cooling capacity of air conditioner was measured. One energy simulation tool, Designer’s Simulation Toolkits (DeST), was used to calculate the basic dynamic temperature and hourly cooling loads. Comparison of results from real-time experimental method and DeST simulation shows that the proposal model can be used in cooling load calculations, with an average 2.5% relative error to DeST results.

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15

Alkaldy, Esam A. Hashim, Maythem A. Albaqir, and Maryam Sadat Akhavan Hejazi. "A new load forecasting model considering planned load shedding effect." International Journal of Energy Sector Management 13, no. 1 (April 1, 2019): 149–65. http://dx.doi.org/10.1108/ijesm-03-2018-0008.

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PurposeLoad forecasting is important to any electrical grid, but for the developing and third-world countries with power shortages, load forecasting is essential. When planed load shedding programs are implemented to face power shortage, a noticeable distortion to the load curves will happen, and this will make the load forecasting more difficult.Design/methodology/approachIn this paper, a new load forecasting model is developed that can detect the effect of planned load shedding on the power consumption and estimate the load curve behavior without the shedding and with different shedding programs. A neuro-Fuzzy technique is used for the model, which is trained and tested with real data taken from one of the 11 KV feeders in Najaf city in Iraq to forecast the load for two days ahead for the four seasons. Load, temperature, time of the day and load shedding schedule for one month before are the input parameters for the training, and the load forecasting data for two days are estimated by the model.FindingsTo verify the model, the load is forecasted without shedding by the proposed model and compared to real data without shedding and the difference is acceptable.Originality/valueThe proposed model provides acceptable forecasting with the load shedding effect available and better than other models. The proposed model provides expected behavior of load with different shedding programs an issue helps to select the appropriate shedding program. The proposed model is useful to estimate the real demands by assuming load shedding hours to be zero and forecast the load. This is important in places suffer from grid problems and cannot supply full loads to calculate the peak demands as the case in Iraq.

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16

Xu, Tao, Shi Yu Zhang, Xiao Xue Wang, Tian Chu Li, Jun Lin, Jing Sheng Chen, and Jian Hua Zhou. "Clustering Techniques in Load Characteristic Analysis." Applied Mechanics and Materials 785 (August 2015): 68–72. http://dx.doi.org/10.4028/www.scientific.net/amm.785.68.

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Today, load characteristic analysis plays a vital role in network planning, operation and control. In particular, with massive demand side participation activities on the network, the characteristics of individual load determines the way of the active load management as well as the network pricing strategies. In this paper, the load characteristics are analyzed utilizing clustering techniques for a tropical isle with massive temperature sensitive loads. Through deeply mining of real data, the features of individual loads were observed to define the way of load participation.

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17

Sekine, M., M. Ukita, and H. Nakanishi. "Systematic Pollutegraph Simulation for Real Scale River Basin." Water Science and Technology 23, no. 1-3 (January 1, 1991): 141–50. http://dx.doi.org/10.2166/wst.1991.0410.

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This study describes the model for predicting the run-off load of pollutants through rivers into eutrophic lakes and inner sea areas. The model is composed of three stages: discharged load prediction; flow-rate prediction; and run-off load prediction. The discharged load in the river basin is estimated by using a pollutant loading factor method. The flow-rate which is necessary for the formula to predict the run-off load, was obtained by a tank model method. The run-off load prediction process consists of two stages: flow-out stage and flow-down stage. The flow-out stage represents the process in which the discharged load, including that from non-point source, flows out through gutters or small streams into the main river. The flow-down stage represents the process in which the flow-out load flows down through the main river to an observing station. There have been many studies dealing with water quality and load of pollutants in rivers. However, only a few of these studies have analyzed the relationship of human activities in the river basins quantitatively. Using this model, a computer program for pollutegraph simulation was constructed and applied to the river Ibo in Hyougo prefecture, JAPAN. The results obtained showed in accordance with the data obtained from field investigation.

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18

Shi, Xiao Hui, Xi Hong Zou, Quan Shi, and Shun Li Xiao. "Motorcycle Dynamics Simulation Based on Real Road Load." Applied Mechanics and Materials 16-19 (October 2009): 318–22. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.318.

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The motorcycle dynamics simulation method based on the road simulation test and virtual prototype is developed, and a rigid-flexible coupling virtual prototype with test platform of motorcycle is created with CATIA, NASTRAN and ADAMS software. According to two-channel tire-coupled road simulator of MTS Systems Corporation, the simulation model and platform are repetitively refined to fairly high precision by comparing simulation results with experimental results. The iterated excitation signal based on real road load or typical spectrum of different roads is imported into the virtual test platform, the comfort and durability tests of motorcycle can be undertaken to replace road simulator, the test period and cost are greatly reduced, and test security is increased.

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19

Chandran, Anandhu. "Real Time Smart Energy Meter and Load Automation." International Journal of Advances in Computer Science and Technology 9, no. 6 (June 25, 2020): 10–14. http://dx.doi.org/10.30534/ijacst/2020/02962020.

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20

Yorino, Naoto, Habibuddin M. Hafiz, Yutaka Sasaki, and Yoshifumi Zoka. "High-Speed Real-Time Dynamic Economic Load Dispatch." IEEE Transactions on Power Systems 27, no. 2 (May 2012): 621–30. http://dx.doi.org/10.1109/tpwrs.2011.2169285.

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21

Teppati, V., A. Ferrero, and U. Pisani. "Recent Advances in Real-Time Load-Pull Systems." IEEE Transactions on Instrumentation and Measurement 57, no. 11 (November 2008): 2640–46. http://dx.doi.org/10.1109/tim.2008.926044.

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22

Chang, Y. C., and K. G. Shin. "Optimal Load Sharing in Distributed Real-Time Systems." Journal of Parallel and Distributed Computing 19, no. 1 (September 1993): 38–50. http://dx.doi.org/10.1006/jpdc.1993.1088.

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23

Teppati, V., A. Ferrero, D. Parena, and U. Pisani. "Accuracy Improvement of Real-Time Load-Pull Measurements." IEEE Transactions on Instrumentation and Measurement 56, no. 2 (April 2007): 610–13. http://dx.doi.org/10.1109/tim.2007.891049.

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24

SRIMANI, PRADIP K., and RACHAMALLU L. N. REDDY. "Load sharing in soft real-time distributed systems." International Journal of Systems Science 23, no. 7 (July 1992): 1115–30. http://dx.doi.org/10.1080/00207729208949369.

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25

Golshani, Amir, Wei Sun, and Kai Sun. "Real-Time Optimized Load Recovery Considering Frequency Constraints." IEEE Transactions on Power Systems 34, no. 6 (November 2019): 4204–15. http://dx.doi.org/10.1109/tpwrs.2019.2922653.

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26

Brinkschulte, Lars, Julian Hafner, and Marcus Geimer. "Real-time Load Determination of Wheel Loader Components." ATZheavy duty worldwide 12, no. 4 (November 2019): 62–68. http://dx.doi.org/10.1007/s41321-019-0043-5.

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27

Liu, Zhong Hui, Zhen Shu Wang, and Mei Hua Su. "Dynamic Load Modeling Based on Extreme Learning Machine." Applied Mechanics and Materials 195-196 (August 2012): 1043–48. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.1043.

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The dynamic load characteristics have significant impact on the power flow, transient stability computation, voltage stability calculation of the power system, and so on. Noticing that traditional mechanism loads model has difficulty in precisely describing the dynamic characteristics of synthetic load, this paper presents a non-mechanism dynamic load model based on Extreme Learning Machine (ELM). The Power Fault Recorder and Measurement System (PFRMS) is used to obtain data for load modeling. Take voltage and real/reactive power with different time delay as inputs, and take real/reactive power as output, train the ELM using the samples formed by fault data, the real power model and reactive power model are established respectively. The number of hidden layer nodes which has impact on the ELM model is also discussed. Dynamic simulation experiment is conducted at power system dynamic simulation laboratory. The simulation result shows that the ELM load model is simple and flexible, its parameters are easy to be identified. The ELM load model can describe the dynamic load characteristics accurately.

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28

Weinreich, Gabriela, Wolfgang Schilling, Ane Birkely, and Tallak Moland. "Pollution based real time control strategies for combined sewer systems." Water Science and Technology 36, no. 8-9 (October 1, 1997): 331–36. http://dx.doi.org/10.2166/wst.1997.0688.

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This paper presents results from an application of a newly developed simulation tool for pollution based real time control (PBRTC) of urban drainage systems. The Oslo interceptor tunnel is used as a case study. The paper focuses on the reduction of total phosphorus Ptot and ammonia-nitrogen NH4-N overflow loads into the receiving waters by means of optimized operation of the tunnel system. With PBRTC the total reduction of the Ptot load is 48% and of the NH4-N load 51%. Compared to the volume based RTC scenario the reductions are 11% and 15%, respectively. These further reductions could be achieved with a relatively simple extension of the operation strategy.

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29

Shareef, Hussain, Saifulnizam Abd Khalid, Mohd Wazir Mustafa, and Azhar Khairuddin. "An ANFIS Approach for Real Power Transfer Allocation." Journal of Applied Mathematics 2011 (2011): 1–14. http://dx.doi.org/10.1155/2011/414258.

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This paper proposes an adaptive neurofuzzy interface system (ANFIS) approach to identify the real power transfer between generators. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to train the designed ANFIS. It also incorporated an enhanced feature extraction method called principle component analysis (PCA) to reduce the input features to the ANFIS. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the ANFIS output compared to that of the MNE method. The ANFIS output provides promising results in terms of accuracy and computation time. Furthermore, it can be concluded that the ANFIS with enhanced feature extraction method reduces the time taken to train the ANFIS without affecting the accuracy of the results.

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30

Baroogh, Farshid Abdolahnejad, Milad Gheydi, and Payam Farhadi. "Induction Motor Drive based on Efficiency Optimisation andDrive Loss Minimization in Real-Time Control of Linkage Flux of Drive Reference." International Journal of Advances in Applied Sciences 6, no. 3 (September 1, 2017): 244. http://dx.doi.org/10.11591/ijaas.v6.i3.pp244-257.

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Induction motor drives are commonly used for applications with vast variations in mechanical load for torques under nominal values. HVAC loads are among these loads. The most ideal scheme for induction motor drive design should include drive loss reduction, or efficiency improvement, proportional to load torque such that optimal performance of drive is not affected. In this paper, using analytical methods, an accurate model is proposed for induction motor drive design. This model allows us to utilize real control and classical control theory for better performance of drive control system. The most damaging mechanical load for induction motor drive is impulse load or so-called periodic load. A scheme proposed for power loss control includes loss control for this type of load, meanwhile, robustness of drive system and stator frequency stability are retained. Main advantages for this scheme are applicability and implementation on various induction motor drives with various powers, without any specific requirements and the least possible computation for the processors.

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31

Joseph, Shibily, and Jasmin Erakkath Abdu. "Real-time retail price determination in smart grid from real-time load profiles." International Transactions on Electrical Energy Systems 28, no. 3 (January 5, 2018): e2509. http://dx.doi.org/10.1002/etep.2509.

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32

Li, Jinghua, Yongsheng Lei, Qian Huang, Zhijun Qin, and Bo Chen. "Feature Analysis of Generalized Load Patterns Considering Active Load Response to Real-Time Pricing." IEEE Access 7 (2019): 119443–53. http://dx.doi.org/10.1109/access.2019.2936497.

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33

Jun, Zhang, Ming Kang Gou, and Chuan Liang. "Experimental Simulation of Bridges Subjected by Moving Loads." Applied Mechanics and Materials 873 (November 2017): 208–11. http://dx.doi.org/10.4028/www.scientific.net/amm.873.208.

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The effect of bridge vibrationinduced bylive loads such as vehicles and pedestrians is an important factor of bridge fatigue damage. It takes much labor and material resource to perform vibration experiments on bridges subjected by real moving loads in field. In order to carry out laboratory experiments on bridges subjected by moving loads, a fixed load with harmonic vibration simulates a moving load on bridge in the beam theory. A simply supported bridge is considered in the present study. The dynamic responses of bridge under different loads are established by the analytic method. Amplitude and frequency of the simulated load are generated on the principle of equal displacements due to both a moving load and a fixed harmonic load impacting on a simply supported beam. Comparisons of numerical results of two types of load on the same beam indicate that the harmonic load can simulate a moving load effectively. It is possible that the field test on bridge can be carried out indoors.

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34

Valcárcel, D. F., D. Alves, P. Card, B. B. Carvalho, S. Devaux, R. Felton, A. Goodyear, et al. "The JET real-time plasma-wall load monitoring system." Fusion Engineering and Design 89, no. 3 (March 2014): 243–58. http://dx.doi.org/10.1016/j.fusengdes.2013.10.010.

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35

Kurose, James F., and Renu Chipalkatti. "Load Sharing in Soft Real-Time Distributed Computer Systems." IEEE Transactions on Computers C-36, no. 8 (August 1987): 993–1000. http://dx.doi.org/10.1109/tc.1987.5009522.

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36

Bonino, Serena, Valeria Teppati, and Andrea Ferrero. "Further Improvements in Real-Time Load-Pull Measurement Accuracy." IEEE Microwave and Wireless Components Letters 20, no. 2 (February 2010): 121–23. http://dx.doi.org/10.1109/lmwc.2009.2038619.

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37

Berger, Arthur W., and Fred C. Schweppe. "Real Time Pricing to Assist in Load Frequency Control." IEEE Power Engineering Review 9, no. 8 (August 1989): 38. http://dx.doi.org/10.1109/mper.1989.4310876.

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38

Niesters, Hubert G. M. "Quantitation of Viral Load Using Real-Time Amplification Techniques." Methods 25, no. 4 (December 2001): 419–29. http://dx.doi.org/10.1006/meth.2001.1264.

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39

Berger, A. W., and F. C. Schweppe. "Real time pricing to assist in load frequency control." IEEE Transactions on Power Systems 4, no. 3 (1989): 920–26. http://dx.doi.org/10.1109/59.32580.

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40

Noussan, Michel, Matteo Jarre, and Alberto Poggio. "Real operation data analysis on district heating load patterns." Energy 129 (June 2017): 70–78. http://dx.doi.org/10.1016/j.energy.2017.04.079.

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41

Gómez-Expósito, Antonio, Esther Romero-Ramos, and Izudin Džafić. "Hybrid real–complex current injection-based load flow formulation." Electric Power Systems Research 119 (February 2015): 237–46. http://dx.doi.org/10.1016/j.epsr.2014.10.002.

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42

Sailesh Babu, G. S., D. Bhagwan Das, and C. Patvardhan. "Real-parameter quantum evolutionary algorithm for economic load dispatch." IET Generation, Transmission & Distribution 2, no. 1 (2008): 22. http://dx.doi.org/10.1049/iet-gtd:20060495.

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43

Bevrani, Hassan, and Takashi Hiyama. "Robust load–frequency regulation: A real-time laboratory experiment." Optimal Control Applications and Methods 28, no. 6 (2007): 419–33. http://dx.doi.org/10.1002/oca.802.

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44

Bintoudi, Angelina D., Napoleon Bezas, Lampros Zyglakis, Georgios Isaioglou, Christos Timplalexis, Paschalis Gkaidatzis, Athanasios Tryferidis, Dimosthenis Ioannidis, and Dimitrios Tzovaras. "Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration." Energies 14, no. 14 (July 17, 2021): 4315. http://dx.doi.org/10.3390/en14144315.

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In 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR) has been identified as a promising tool for unlocking the hidden flexibility potential of residential consumption. In this work, a holistic incentive-based DR framework aiming towards load shifting is proposed for residential applications. The proposed framework is characterised by several innovative features, mainly the formulation of the optimisation problem, which models user satisfaction and the economic operation of a distributed household portfolio, the customised load forecasting algorithm, which employs an adjusted Gradient Boosting Tree methodology with enhanced feature extraction and, finally, a disaggregation tool, which considers electrical features and time of use information. The DR framework is first validated through simulation to assess the business potential and is then deployed experimentally in real houses in Northern Greece. Results demonstrate that a mean 1.48% relative profit can be achieved via only load shifting of a maximum of three residential appliances, while the experimental application proves the effectiveness of the proposed algorithms in successfully managing the load curves of real houses with several residents. Correlations between market prices and the success of incentive-based load shifting DR programs show how wholesale pricing should be adjusted to ensure the viability of such DR schemes.

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45

Hodás, Stanislav, and Alžbeta Pultznerová. "Modelling of Railway Track Temperature Regime with Real Heat-Technical Values for Different Climatic Characteristics." Civil and Environmental Engineering 13, no. 2 (December 20, 2017): 134–42. http://dx.doi.org/10.1515/cee-2017-0018.

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Abstract High quality of railway track construction is a major priority. One of the quality elements is the resistance to load of railway formation with individual structural layers caused by negative temperatures during the critical freezing period of winter. Numerical modelling allows obtaining more control outputs at different climatic loads. The presented paper shows the load of railway track model with different variants of climate and shows the importance in the designing of the non-transport load under negative temperatures, i.e. observation of transition of the zero isotherm through the layers of railway subgrade. If the subgrade layers of the railway formation are built with high quality and durability then the axis of the track will keep its geometric spatial position during the long-time operation.

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46

Lv, Wenjie, Jian Wu, Zhao Luo, Min Ding, Xiang Jiang, Hejian Li, and Qian Wang. "Load Aggregator-Based Integrated Demand Response for Residential Smart Energy Hubs." Mathematical Problems in Engineering 2019 (April 18, 2019): 1–14. http://dx.doi.org/10.1155/2019/6925980.

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In order to attract more flexible resource to take part in integrated demand response (IDR), this can be realized by introducing load aggregator-based framework. In this paper, based on residential smart energy hubs (S.E. Hubs), a two-level IDR framework is proposed, in which S.E. Hub operators play the role of load aggregators. The framework includes day-ahead bidding and real-time scheduling. In day-ahead bidding, S.E. Hub operators have to compete dispatching amount for maximal profit; hence, noncooperative game approach is formulated to describe the competition behavior among operators. In real-time scheduling, the dispatching model is formulated to minimize the error between real-time scheduling amount and bidding amount. Moreover, in order to reduce the influence of IDR on residential users, 4 categories of users’ flexible loads are modeled according to load consumption characteristic, and then these models are considered as the constraints in real-time scheduling. A case study is designed to validate the effectiveness of the proposed two-level IDR framework. And simulation results confirm that smart grid, S.E. Hub operators, and residential users can benefit simultaneously.

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Musthofa, Musthofa. "Sistem Monitoring Online Real Time Beban Unbalance dan Overload Trafo Distribusi di PT PLN (Persero)." Energi & Kelistrikan 12, no. 2 (December 22, 2020): 156–64. http://dx.doi.org/10.33322/energi.v12i2.1163.

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Public and government demands for PLN to serve all people to enjoy electricity with a target of 100% Electrification Ratio. To fulfill the Electrification Ratio, of course, it is necessary to increase the capacity of the distribution transformer with the addition of an insert transformer and a new transformer. So that the increasing number of connections to customers' homes or buildings will result in overload or unbalance loading of the distribution transformer. The problem is the number of transformers 3,938 units at PLN UP3 Padang with limited load measuring officers only 70 teams, there is still a transformer failure of 0.41% in 2019. This is because the load measurement is done directly (manually on site) so it requires large human resources and costs. Under these conditions, a realtime online load measurement system is needed. This study uses the Root Couse Problem Solving (RCPS) methodology and system and equipment design by creating a transformer load monitoring system both unbalance and overload online Real Time. With this System and Equipment, the substation load in realtime with a speed of 2 seconds, the condition of the transformer is known. Telemetering function by sending load data so that the risk of damage to the transformer can be reduced because this tool is an early warning against unbalanced loads, single phase outages and so on. So that PLN can maintain life time and recovery time in maintaining the quality of its service.

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Lallemand, Francis, Nathalie Desire, Willy Rozenbaum, Jean-Claude Nicolas, and Vincent Marechal. "Quantitative Analysis of Human Herpesvirus 8 Viral Load Using a Real-Time PCR Assay." Journal of Clinical Microbiology 38, no. 4 (2000): 1404–8. http://dx.doi.org/10.1128/jcm.38.4.1404-1408.2000.

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We have developed a quantitative real-time PCR (TaqMan) assay aimed at measuring the cellular human herpesvirus 8 (HHV-8) DNA load in various clinical samples. Standard curves were obtained by serial dilutions of a control plasmid containing both HHV-8 (ORF73 gene) and the cellular target (human albumin gene). The assay appeared to be very sensitive (100% detection rate for at least 10 copies per well) and specific and was easily reproducible (less than 3% intra-assay variability, 5% interassay variability). This method allowed us to quantify precisely the average HHV-8 copy number per cell in various persistently HHV-8-infected cell lines (BBG-1 cells, n= 200; BC-1 cells, n = 59; BCBL-1 cells,n = 70). A retrospective study was also conducted to assess the HHV-8 DNA load in 12 human immunodeficiency virus-infected patients with either Kaposi's sarcoma (KS; seven patients monitored over a 3-month period) or multicentric Castleman's disease (MCD; five patients). The HHV-8 DNA load ranged from 0 to 9,171 copies/106 cells in low-risk KS patients (T0, I0, S0 according to the classification of the AIDS Clinical Trials group). We also measured the viral loads in MCD patients either during symptomatic periods or during remission. The results are in agreement with previously published data, with high viral loads correlating with clinical symptoms (1.3 × 106 copies/106cells) and low viral loads correlating with asymptomatic periods (less than 5,000 copies/106 cells).

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Long, Thomas G. "God Be Merciful to Me, a Miscalculator." Theology Today 50, no. 2 (July 1993): 165–68. http://dx.doi.org/10.1177/004057369305000201.

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If I could I'd confess Good and loud, nice and slow Get this load off my chest Yes, but how, Lord—I don't know. What I say I don't feel What I feel I don't show What I show isn 't real What is real, Lord, I don't know No, no, no—I don't know. …(“Trope: I Don't Know,” Mass, Leonard Bernstein)

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Wang, Cheng, and Jin Gou. "Equivalent Load Identification Algorithm Based on Least-squares in Frequency Domain." Applied Mechanics and Materials 275-277 (January 2013): 2677–80. http://dx.doi.org/10.4028/www.scientific.net/amm.275-277.2677.

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Because the real load location of structure in working condition is unknown or cannot be reached, a new equivalent load identification algorithm in frequency domain is proposed. This new algorithm can guarantee the same vibration response signals for key examination points and can reach purposes of reliability test and environmental adaptability test then. Based on the assumptions of linear system and uncorrelated of each load, combined transfer functions, least-squares of generalized matrix inverse in frequency domain, this new algorithm identify multi-sources loads at the same time. In this new algorithm, the Identification load location, direction and form can be specify prior and not be the same with real load location, the boundary condition of structure in test cannot be the same with working condition. Formula derivation, application scope and steps of this method were summarized then. Load identification results of vibration simulations in cylindrical shell showed that this new method could basically meet the engineering precision requirement of ± 3db at last, which valid the effectiveness and reasonableness of this method.

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