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Journal articles on the topic 'Intelligent Load Shedding(ILS)'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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1

Shokooh, Farrokh, J. J. Dai, Shervin Shokooh, Jacques Tastet, Hugo Castro, Tanuj Khandelwal, and Gary Donner. "Intelligent Load Shedding." IEEE Industry Applications Magazine 17, no. 2 (March 2011): 44–53. http://dx.doi.org/10.1109/mias.2010.939814.

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2

Lee, W. J., and J. C. Gu. "A microcomputer-based intelligent load shedding relay." IEEE Transactions on Power Delivery 4, no. 4 (1989): 2018–24. http://dx.doi.org/10.1109/61.35626.

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3

Lee, Wei-Jen, and Jyh-Cherng Gu. "A Microcomputer-Based Intelligent Load Shedding Relay." IEEE Power Engineering Review 9, no. 10 (1989): 44–45. http://dx.doi.org/10.1109/mper.1989.4310313.

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4

Wang, Ji Dong, Di Jin, Hui Ying Zhang, Hua Dong Sun, and Qing He. "The Existing Investigation and Prospect of Under-Frequency and Under-Voltage Load Shedding in Power Systems." Applied Mechanics and Materials 347-350 (August 2013): 1293–97. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1293.

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Under-frequency load shedding (UFLS) and under-voltage load shedding (UVLS) as the last defense of the power system to maintain its stability are of great significance, especially for the current development of large-scale interconnected power system. At first, this paper presents the existing methods of load shedding and analyses their drawbacks. Then, a brief overview of the application of wide area measurement system (WAMS) in UFLS and UVLS is provided. Finally, a novel intelligent load shedding scheme which realizes load adjustment instead of load shedding based on the characteristics of smart grid and smart home is proposed.

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5

Raza, Muhammad Qamar, Muhammad Ali, Nauman Tareen, Waheed ur Rehman, Asadullah Khan, and Azam Ul Asar. "Intelligent Load Shedding Using TCP/IP for Smart Grids." Energy and Power Engineering 04, no. 06 (2012): 398–403. http://dx.doi.org/10.4236/epe.2012.46053.

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6

Abd Shukor, Saiful Firdaus, Ismail Musirin, Zulkifli Abd Hamid, Mohamad Khairuzzaman Mohamad Zamani, Mohamed Zellagui, and Hadi Suyono. "Intelligent based technique for under voltage load shedding in power transmission systems." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 1 (January 1, 2020): 110. http://dx.doi.org/10.11591/ijeecs.v17.i1.pp110-117.

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<p>The increasing demand of electric power energy and the presence of disturbances can be identified as the factors of voltage instability condition in a power system. A secure and reliable power system should be considered to ensure smooth delivery of electricity to the consumers. A power system may experience undesired event such as voltage instability condition leading to voltage collapse or cascading collapse if the system experiences lack of reactive power support. Thus, to avoid blackout and cascaded tripping, load shedding is the last resort to prevent a total damage. Under Voltage Load Shedding (UVLS) scheme is one of the possible methods which can be conducted by thepower system operators to avoid the occurrence of voltage instability condition. This paper presents the intelligent based technique for under voltage load shedding in power transmission systems. In this study, a computational based technique is developed in solving problem related to UVLS. The integration between a known computational intelligence-based technique termed as Evolutionary Programming (EP) with the under-voltage load shedding algorithm has been able to maintain the system operated within the acceptable voltage limit. Loss and minimum voltage control as the objective function implemented on the IEEE 30-Bus Reliability Test System (RTS) managed to optimally identify the optimal location and sizing for the load shedding scheme. Results from the studies, clearly indicate the feasibility of EP for load shedding scheme in loss and minimum voltage control in power system.</p>

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7

HAIDAR, AHMED M. A., AZAH MOHAMED, MAJID AL-DABBAGH, AINI HUSSAIN, and MOHAMMAD MASOUM. "AN INTELLIGENT LOAD SHEDDING SCHEME USING NEURAL NETWORKS AND NEURO-FUZZY." International Journal of Neural Systems 19, no. 06 (December 2009): 473–79. http://dx.doi.org/10.1142/s0129065709002178.

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Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power supply. This was confirmed by the results obtained in this research of which sample results are given in this paper.

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8

Jemai, Kamel, Hafedh Trabelsi, and Abdelaziz Ouederni. "Fuzzy load shedding strategy based on the anticipation of the point of voltage collapse." Journal of Intelligent & Fuzzy Systems 26, no. 4 (2014): 1845–56. http://dx.doi.org/10.3233/ifs-130864.

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9

Jouini, Houda, Kamel Jemai, and Souad Chebbi. "Voltage Stability Control of Electrical Network Using Intelligent Load Shedding Strategy Based on Fuzzy Logic." Mathematical Problems in Engineering 2010 (2010): 1–17. http://dx.doi.org/10.1155/2010/341257.

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As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.

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10

Berec, Zoltan. "OPTIMIZACIJA AUTOMATSKOG PODFREKVENTNOG RASTEREĆENJA POTROŠAČA PRIMENOM GENETSKOG ALGORITMA." Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 34, no. 09 (August 22, 2019): 1610–13. http://dx.doi.org/10.24867/04be27berec.

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U ovom radu predstaviće se rešenje optimizacije Automatskog podfrekventnog rasterećenja potrošača (AFRP) primenom genetskog algoritma. Opisaće se realizacija AFRP-a ILS metodom (Intelllegent Load Shedding) koja se koriste za očuvanje stabilnosti kao krajnje opcije i kao rešenje je ponuđen Genetski algoritam kao metod optimizacije za pronalaženje adekvatne liste potrošača za isključenje.

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11

Ahmad, Ishtiaq, Faizullah Khan, Surat Khan, Akbar Khan, Abdul Wahid Tareen, and Muhammad Saeed. "Blackout Avoidance through Intelligent Load Shedding in Modern Electrical Power Utility Network." Journal of Applied and Emerging Sciences 8, no. 1 (December 19, 2018): 48. http://dx.doi.org/10.36785/jaes.81242.

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12

Chen, Chao Shun, Te Tien Ku, and Chia Hung Lin. "Design of Intelligent Power Meter for Demand Response of Smart Grid." Advanced Materials Research 516-517 (May 2012): 1692–98. http://dx.doi.org/10.4028/www.scientific.net/amr.516-517.1692.

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To support the demand response function for smart grid, an intelligent power meter with hybrid communication module has been proposed in this paper. The circuit module consisting of VI measurement, power calculation chip, microprocessor and PLC/ZigBee/RS-485 communication is designed to support load control to achieve load reduction after receiving the demand response command of via two way communication. The load control function can also be activated by the real time pricing information, which has been downloaded from utility control center. The embedded power management system is developed to perform the management of intelligent power meters to monitor and control electrical appliances. Based on the field test, the intelligent power meter can be used for load shedding or power due to achieve energy conservation and enhance system stability for smart grid application.

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13

Skrjanc, Tadej, Rafael Mihalic, and Urban Rudez. "Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm." Energies 13, no. 22 (November 12, 2020): 5896. http://dx.doi.org/10.3390/en13225896.

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This research represents a conceptual shift in the process of introducing flexibility into power system frequency stability-related protection. The existing underfrequency load shedding (UFLS) solution, although robust and fast, has often proved to be incapable of adjusting to different operating conditions. It triggers upon detection of frequency threshold violations, and functions by interrupting the electricity supply to a certain number of consumers, both of which values are decided upon beforehand. Consequently, it often does not comply with its main purpose, i.e., bringing frequency decay to a halt. Instead, the power imbalance is often reversed, resulting in equally undesirable frequency overshoots. Researchers have sought a solution to this shortcoming either by increasing the amount of available information (by means of wide-area communication) or through complex changes to all involved protection relays. In this research, we retain the existing concept of UFLS that performs so well for fast-occurring frequency events. The flexible rebalancing of power is achieved by a small and specialized group of intelligent electronic devices (IEDs) with machine learning functionalities. These IEDs interrupt consumers only when the need to do so is detected with a high degree of certainty. Their small number assures the fine-tuning of power rebalancing and, at the same time, poses no serious threat to system stability in cases of malfunction.

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14

Mahesh, C., F. T.Josh, and A. Sanjeevi Gandhi. "A comprehensive study on protection, control and communication techniques: a key concept for microgrid intelligent operation." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 35. http://dx.doi.org/10.14419/ijet.v7i2.8.10320.

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Microgrid is an integrated network of renewable and non renewable resources to supply the green power to a small range of community. An effective communication technology is necessary to be implemented among the power generations, storages and loads of microgrid in order to manage the load sharing, shedding and protection issues. This paper provides the study on architecture, characteristics, load managements, protection schemes, communication techniques and research challenges of microgrid.

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15

SHAHGHOLIAN, Ghazanfar, and Bahman ZAHEDI. "An intelligent Approach to Combinational Load Shedding with Tracing Reactive Power based on Genetic Algorithm." Cumhuriyet Science Journal 38, no. 1 (February 16, 2017): 95. http://dx.doi.org/10.17776/csj.26288.

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16

Wang, Qi, Yi Tang, Feng Li, Mengya Li, Yang Li, and Ming Ni. "Coordinated Scheme of Under-Frequency Load Shedding with Intelligent Appliances in a Cyber Physical Power System." Energies 9, no. 8 (August 10, 2016): 630. http://dx.doi.org/10.3390/en9080630.

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17

Sadoudi, Slimane, Mohamed Boudour, and Nour El Yakine Kouba. "Multi‐microgrid intelligent load shedding for optimal power management and coordinated control with energy storage systems." International Journal of Energy Research 45, no. 11 (May 4, 2021): 15857–78. http://dx.doi.org/10.1002/er.6819.

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18

Wang, Jidong, Huiying Zhang, and Yue Zhou. "Intelligent Under Frequency and Under Voltage Load Shedding Method Based on the Active Participation of Smart Appliances." IEEE Transactions on Smart Grid 8, no. 1 (January 2017): 353–61. http://dx.doi.org/10.1109/tsg.2016.2582902.

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19

MAJIDI, Mehrdad, Mohammad-Reza AGHAMOHAMMADI, and Moein MANBACHI. "New design of intelligent load shedding algorithm based on critical line overloads to reduce network cascading failure risks." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 22 (2014): 1395–409. http://dx.doi.org/10.3906/elk-1112-52.

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20

Rwegasira, Diana, Imed Ben Dhaou, Masoumeh Ebrahimi, Anders Hallén, Nerey Mvungi, and Hannu Tenhunen. "Energy trading and control of islanded DC microgrid using multi-agent systems." Multiagent and Grid Systems 17, no. 2 (August 23, 2021): 113–28. http://dx.doi.org/10.3233/mgs-210345.

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The energy sector is experiencing a revolution that is fuelled by a multitude of factors. Among them are the aging grid system, the need for cleaner energy and the increasing demands on energy sector. The demand-response program is an advanced feature in smart grid that strives to match suppliers to their demands using price-based and incentive programs. The objective of the work is to analyse the performance of the load shedding technique using dynamic pricing algorithm. The system was designed using multi-agent system (MAS) for a DC microgrid capable of real-time monitoring and controlling of power using price-based demand-response program. As a proof of concept, the system was implemented using intelligent physical agents, Java Agent Development Framework (JADE), and agent simulation platform (REPAST) with two residential houses (non-critical loads) and one hospital (critical load). The architecture has been implemented using embedded devices, relays, and sensors to control the operations of load shedding and energy trading in residential areas that have no access to electricity. The measured results show that the system can shed the load with the latency of less than 600 ms, and energy cost saving with an individual houses by 80% of the total cost with 2USD per day. The outcome of the studies demonstrates the effectiveness of the proposed multi-agent approach for real-time operation of a microgrid and the implementation of demand-response program.

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21

Sodin, Denis, Rajne Ilievska, Andrej Čampa, Miha Smolnikar, and Urban Rudez. "Proving a Concept of Flexible Under-Frequency Load Shedding with Hardware-in-the-Loop Testing." Energies 13, no. 14 (July 13, 2020): 3607. http://dx.doi.org/10.3390/en13143607.

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It is widely recognized that in the transition from conventional electrical power systems (EPSs) towards smart grids, electrical voltage frequency will be greatly affected. This is why this research is extremely valuable, especially since rate-of-change-of-frequency (RoCoF) is often considered as a potential means of resolving newly arisen problems, but is often challenged in practice due to the noise and its oscillating character. In this paper, the authors further developed and tested one of the new technologies related to under-frequency load shedding (UFLS) protection. Since the basic idea was to enhance the selected technology’s readiness level, a hardware-in-the-loop (HIL) setup with an RTDS was assembled. The under-frequency technology was implemented in an intelligent electronic device (IED) and included in the HIL setup. The IED acted as one of several protection devices, representing a last-resort system protection scheme. All main contributions of this research deal with using RoCoF in an innovative UFLS scheme under test: (i) appropriate selection and parameterization of RoCoF filtering techniques does not worsen under-frequency load shedding during fast-occurring events, (ii) locally measured RoCoF can be effectively used for bringing a high level of flexibility to a system-wide scheme, and (iii) diversity of relays and RoCoF-measuring techniques is an advantage, not a drawback.

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22

Rauf, Shoaib, and Nasrullah Khan. "Application of DC-AC Hybrid Grid and Solar Photovoltaic Generation with Battery Storage Using Smart Grid." International Journal of Photoenergy 2017 (2017): 1–16. http://dx.doi.org/10.1155/2017/6736928.

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Smart grid for the past few years has been the prime focus of research in power systems. The aim is to eliminate load shedding and problematic blackout conditions, further offering cheap and continuous supply of electricity for both large and small consumers. Another benefit is to integrate renewable energy resources with existing dump grid in more efficient and cost-effective manner. In past few years, growing demand for sustainable energy increases the consumption of solar PV. Since generation from solar PV is in DC and most of the appliances at home could be operated on DC, AC-DC hybrid distribution system with energy management system is proposed in this paper. EMS helps to shift or control the auxiliary load and compel the users to operate specific load at certain time slots. These techniques further help to manage the excessive load during peak and off peak hours. It demonstrates the practical implementation of DC-AC network with integration of solar PV and battery storage with existing infrastructure. The results show a remarkable improvement using hybrid AC-DC framework in terms of reliability and efficiency. All this functioning together enhances the overall efficiency; hence, a secure, economical, reliable, and intelligent system leads to a smart grid.

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23

Bulatov, Yu N., A. V. Kryukov, and K. V. Suslov. "The study of the isolated power supply system operation with controlled distributed generation plants, energy storage units and drive load." E3S Web of Conferences 288 (2021): 01012. http://dx.doi.org/10.1051/e3sconf/202128801012.

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Energy storage units (ESU) and distributed generation (DG) plants including those using renewable energy sources can be used to develop isolated power supply systems (IPSS) and enhance their reliability. Operation of DG plants in the IPSS requires to consider restrictions for consumers maximum load, as well as effects of abrupt load increase or load shedding on the generating plants. These problems can be resolved using ESU and intelligent technologies for DG plants control. The paper considers IPSS of an industrial facility with turbogenerator plants (TGP), wind power plant (WPP) and high-capacity ESU for which fuzzy control systems and prognostic controllers were used. The simulation was performed in the MATLAB system using the Simulink and SimPowerSystems software packages. Normal and emergency modes were studied in IPSS with TGP, WPP, and high-capacity ESU. The simulation results indicated that combined use of high-capacity ESU and prognostic controller of TGP generator rotor speed allows to ensure stability and survivability of IPSS enhancing its damping properties. The auto-prognostic controller of the TGP generator, which does not require special adjustment, provides high quality indicators of the IPSS control in all considered modes.

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24

Guo, Yuanjun, Zhile Yang, Shengzhong Feng, and Jinxing Hu. "Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study." Complexity 2018 (September 20, 2018): 1–21. http://dx.doi.org/10.1155/2018/8496187.

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Efficient and valuable strategies provided by large amount of available data are urgently needed for a sustainable electricity system that includes smart grid technologies and very complex power system situations. Big Data technologies including Big Data management and utilization based on increasingly collected data from every component of the power grid are crucial for the successful deployment and monitoring of the system. This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. This paper proposed a modified and optimized structure of the Big Data processing platform according to the power data sources and different structures. Numerous open-sourced Big Data analytical tools and software are integrated as modules of the analytic engine, and self-developed advanced algorithms are also designed. The proposed framework comprises a data interface, a Big Data management, analytic engine as well as the applications, and display module. To fully investigate the proposed structure, three major applications are introduced: development of power grid topology and parallel computing using CIM files, high-efficiency load-shedding calculation, and power system transmission line tripping analysis using 3D visualization. The real-system cases demonstrate the effectiveness and great potential of the Big Data platform; therefore, data resources can achieve their full potential value for strategies and decision-making for smart grid. The proposed platform can provide a technical solution to the multidisciplinary cooperation of Big Data technology and smart grid monitoring.

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25

H, Nagesh, and R. S. Shivakumara Aradhya. "Intelligent controller-based optimum load shedding for photovoltaic and wind energy-integrated power systems." International Journal of Ambient Energy, July 30, 2021, 1–13. http://dx.doi.org/10.1080/01430750.2021.1949388.

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26

Ahiakwo, Christopher O., Sunny Orike, and Ahuruezemma O. Obioma. "A Computationally Intelligent Power Transmission Expansion Strategy in a Deregulated Energy System." European Journal of Electrical Engineering and Computer Science 2, no. 4 (May 14, 2018). http://dx.doi.org/10.24018/ejece.2018.2.4.22.

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This paper aims to simulate a computationally intelligent electrical power transmission expansion system and study the factors affecting power transmission expansion in a deregulated energy system to improve on the current economic conditions. The main problem facing most power system transmission is the failure to actually forecast the load expansion accurately this leads to failure in the transmission expansion design. a hybrid algorithm for the ac/dc transmission expansion planning (HTEP) and multi algebraic formulation of the stochastic TEP model in a multi-stage planning framework will be used to analyze the transmission expansion system, optimization problem will considers a weighted sum of multiple objectives including cost of operation and maintenance, emission, load shedding and line investments, simulation method would consider random outages of generating units and ac/dc transmission lines as well as load forecast .The independent system operator would utilize the proposed method to select the optimal set of ac/dc transmission lines for satisfying TEP criteria. The proposed set of dc transmission system may use either current source converters or voltage source converters. The proposed algorithms are simulated on IEEE 24-bus reliability test system (RTS) and Gerner’s 6 bus system to compare optimal plans between the original and equivalent system. Further assumptions and adjustments are searched and tested to get more accurate optimal plans. results obtained showed that the hybrid model was capable of handling future generation and load patterns in deregulated, unbundled, and competitive electricity system. the results of the study showed the hybrid model was tested in the Gerner’s 6 bus system and the expansion model after a load forecast. On the IEEE 24-bus system showed that the hybrid expansion model was able to take care of the load forecast for future expansion.

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