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Journal articles on the topic 'RESTRUCTURED POWER SYSTEMS'

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Author: Grafiati

Published: 11 September 2023

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1

od G. Bhongade, Kunal M. Lokhande, Vin. "Transmission Congestion Management in Restructured Power Systems." International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 04, no. 07 (July 20, 2015): 5977–85. http://dx.doi.org/10.15662/ijareeie.2015.0407023.

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2

Pai, M. A. "Operation of restructured power systems [Book Review]." IEEE Power Engineering Review 21, no. 12 (December 2001): 48–49. http://dx.doi.org/10.1109/mper.2001.969600.

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3

Conejo, A. J., R. Garcia-Bertrand, and M. Diaz-Salazar. "Generation Maintenance Scheduling in Restructured Power Systems." IEEE Transactions on Power Systems 20, no. 2 (May 2005): 984–92. http://dx.doi.org/10.1109/tpwrs.2005.846078.

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4

Ramesh, Guguloth, and T. K. Sunil Kumar. "Optimal power flow-based congestion management in restructured power systems." International Journal of Power and Energy Conversion 7, no. 1 (2016): 84. http://dx.doi.org/10.1504/ijpec.2016.075067.

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5

Nargėlas, A. "Automatic Generation Control in Restructured Electric Power Systems." IFAC Proceedings Volumes 33, no. 12 (June 2000): 233–36. http://dx.doi.org/10.1016/s1474-6670(17)37316-0.

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6

Amelink, H. "Power systems engineers in the restructured utility industry." IEEE Computer Applications in Power 14, no. 1 (January 2001): 10–12. http://dx.doi.org/10.1109/mcap.2001.893349.

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7

Ding, Yi, Peng Wang, and Anatoly Lisnianski. "Optimal reserve management for restructured power generating systems." Reliability Engineering & System Safety 91, no. 7 (July 2006): 792–99. http://dx.doi.org/10.1016/j.ress.2005.08.001.

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8

Liu, F., Y. H. Song, J. Ma, S. Mei, and Q. Lu. "Optimal load-frequency control in restructured power systems." IEE Proceedings - Generation, Transmission and Distribution 150, no. 1 (2003): 87. http://dx.doi.org/10.1049/ip-gtd:20020683.

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9

Kheradmandi, Morteza, Mehdi Ehsan, René Feuillet, and Nouredine Hadj-Saied. "Rescheduling of power systems constrained with transient stability limits in restructured power systems." Electric Power Systems Research 81, no. 1 (January 2011): 1–9. http://dx.doi.org/10.1016/j.epsr.2010.07.008.

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10

Bhatt, Praghnesh, Ranjit Roy, and S. P. Ghoshal. "Optimized multi area AGC simulation in restructured power systems." International Journal of Electrical Power & Energy Systems 32, no. 4 (May 2010): 311–22. http://dx.doi.org/10.1016/j.ijepes.2009.09.002.

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11

VENU, V. VIJAY, and A. K. VERMA. "REINFORCEMENT OF POWER SYSTEM RELIABILITY MEASURES THROUGH JOINT DETERMINISTIC AND PROBABILISTIC APPROACHES." International Journal of Reliability, Quality and Safety Engineering 16, no. 06 (December 2009): 551–66. http://dx.doi.org/10.1142/s0218539309003575.

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By adapting the emerging conceptualization of reliability network equivalents, originally developed to obtain reliability indices in the restructured scenario, a suitable framework encapsulating relatively independent modularity could be evolved that shall enable the application of joint deterministic- probabilistic well being-analysis for the composite restructured power systems. Reliability management forms the core component of successful transition from vertical integration of power systems to their deregulation. Timely reinforcements to the resource adequacy will ensure reliably operating power systems. Redundancy apportioning without pessimistic appraisals or exceedingly optimistic estimates is a vital ingredient for the success of restructured systems. With these goals in mind, this paper puts forward a philosophical modeling paradigm that investigates the feasibility of extending the hybrid approach of well-being analysis to a composite bilateral contracts market structure, a potential indicator of generation reinforcements to gear up for. Probabilistic load flow studies as a means to justify transmission reinforcements is also brought forward. Also presented is an overview of the reliability cost-worth methods, information from which forms an integral part of the reinforcement strategies.

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12

Shahidehpour, M., and M. Alomoush. "Restructured Electric Power Systems: Operation, Trading, and Volatility [Book Review]." IEEE Computer Applications in Power 15, no. 2 (April 2002): 60–62. http://dx.doi.org/10.1109/mcap.2002.993762.

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13

Latify, Mohammad Amin, Mohammad Kazem Sheikh-El-Eslami, Habib Rajabi Mashhadi, and Hossein Seifi. "Cobweb theory-based generation maintenance coordination in restructured power systems." IET Generation, Transmission & Distribution 7, no. 11 (November 1, 2013): 1253–62. http://dx.doi.org/10.1049/iet-gtd.2012.0370.

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14

Shayeghi, H., A. Pirayeshnegab, A. Jalili, and H. A. Shayanfar. "Application of PSO technique for GEP in restructured power systems." Energy Conversion and Management 50, no. 9 (September 2009): 2127–35. http://dx.doi.org/10.1016/j.enconman.2009.04.018.

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15

Amudha, A., and C. Christober Asir Rajan. "On Line Application of Profit Based Unit Commitment Using Hybrid Algorithms of Memory Management Algorithm." Advanced Materials Research 403-408 (November 2011): 3965–72. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3965.

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As the electrical industry restructures, many of the traditional algorithms for controlling generating units need modification or replacement. In the past, utilities had to produce power to satisfy their customers with the objective to minimize costs and actual demand/reserve were met. But it is not necessary in a restructured system. The main objective of restructured system is to maximize their own profit without the responsibility of satisfying the forecasted demand. The PBUC is a highly dimensional mixed-integer optimization problem, which might be very difficult to solve. Hence a new software tool is developed in java using Memory Management Algorithm (MMA) by Best Fit (BF) & Worst Fit (WF) allocation for web based application. The proposed method MMA using Best Fit & Worst Fit allocation for generator scheduling in order to receive the maximum profit by considering the softer demand. Also this method gives an idea regarding how much power and reserve should be sold in markets. The Madurai Power Grid Corporation in Tamil Nadu, India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different power systems consisting of 3, 10and 7 generating units. Simulations of the proposed are carried out for maximizing profit and computation time and results are compared with existing methods.

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16

Lindsay, N. Mahiban, and A. K. Parvathy. "Power System Reliability Assessment in a Complex Restructured Power System." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (August 1, 2019): 2296. http://dx.doi.org/10.11591/ijece.v9i4.pp2296-2302.

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The basic purpose of an electric power system is to supply its consumers with electric energy as parsimoniously as possible and with a sensible degree of continuity and quality. It is expected that the solicitation of power system reliability assessment in bulk power systems will continue to increase in the future especially in the newly deregulated power diligence. This paper presents the research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission paucities in complex system adequacy assessment. The incentives for electricity market participants to endow in new generation and transmission facilities are highly influenced by the market risk in a complex restructured environment. This paper also presents a procedure to identify transmission deficiencies and remedial modification in the composite generation and transmission system and focused on the application of probabilistic techniques in composite system adequacy assessment

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17

Chung, C. Y., T. S. Chung, C. W. Yu, and X. J. Lin. "Cost-based reactive power pricing with voltage security consideration in restructured power systems." Electric Power Systems Research 70, no. 2 (July 2004): 85–91. http://dx.doi.org/10.1016/j.epsr.2003.11.002.

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18

R, Manikandan, Kavya P, and Shalini R. "Congestion Management in Restructured Power Systems with Economic and Technical Considerations." Bulletin of Scientific Research 1, no. 1 (May 30, 2019): 41–46. http://dx.doi.org/10.34256/bsr1916.

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In this paper, restructuring of monopolistic power systems is inevitable in this day and age to cope up with the radical growth of power demand. In developed countries restructuring is already in place while developing countries are getting accustomed to it. Above and beyond the benefits to customers in terms of economy and quality, there are several challenges prevailing particularly in transmission while exercising deregulation. The foremost challenging task of Independent System Operator (ISO) is managing the transmission line congestion in a deregulated power system. In most of the congestion management techniques, only the economic aspects are considered. The minimum voltage derivation for electronic industries and acceptable voltage derivation for high power applications are considered with suitable weighting factors in the objective function.

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19

FOTUHI-FIRUZABAD, Mahmud, Farrokh AMINIFAR, and Abbas SHAHZADEH. "Reliability-based maintenance scheduling of generating units in restructured power systems." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 22 (2014): 1147–58. http://dx.doi.org/10.3906/elk-1208-79.

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20

Boucher, Jacqueline, and Yves Smeers. "Alternative Models of Restructured Electricity Systems, Part 1: No Market Power." Operations Research 49, no. 6 (December 2001): 821–38. http://dx.doi.org/10.1287/opre.49.6.821.10017.

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21

Guguloth, Ramesh, and T. K. Sunil Kumar. "Congestion management in restructured power systems for smart cities in India." Computers & Electrical Engineering 65 (January 2018): 79–89. http://dx.doi.org/10.1016/j.compeleceng.2017.04.016.

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22

Delfino, B., F. Fornari, and S. Massucco. "Load-frequency control and inadvertent interchange evaluation in restructured power systems." IEE Proceedings - Generation, Transmission and Distribution 149, no. 5 (2002): 607. http://dx.doi.org/10.1049/ip-gtd:20020368.

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23

Sinha, S. K., R. Prasad, and R. N. Patel. "Automatic generation control of restructured power systems with combined intelligent techniques." International Journal of Bio-Inspired Computation 2, no. 2 (2010): 124. http://dx.doi.org/10.1504/ijbic.2010.032128.

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24

Wang, P., L. Goel, and Y. Ding. "Reliability assessment of restructured power systems using optimal load shedding technique." IET Generation, Transmission & Distribution 3, no. 7 (July 1, 2009): 628–40. http://dx.doi.org/10.1049/iet-gtd.2008.0308.

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25

Mehrtash, Amir, Peng Wang, and Lalit Goel. "Reliability evaluation of restructured power systems using a novel optimal power-flow-based approach." IET Generation, Transmission & Distribution 7, no. 2 (February 1, 2013): 192–99. http://dx.doi.org/10.1049/iet-gtd.2011.0655.

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26

D, Danalakshmi, Kannan S, and Gnanadass R. "Generator reactive power pricing for practical utility system using power flow tracing method." International Journal of Engineering & Technology 7, no. 1.8 (February 9, 2018): 20. http://dx.doi.org/10.14419/ijet.v7i1.8.9444.

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The shift from regulated to restructured power system results in an increased competition among the electricity market. In restructured power system, the separation of transmission services from generation and distribution makes it necessary to find the contribution of power from individual generator to individual load. The power flow tracing method is used to obtain the generator power output to a particular load. The reactive power has to be maintained in order to sustain the voltage level throughout the system for reliable and secure operation. Hence the reactive power cost allocation has become imperative in the power system. In this paper, the tracing method is integrated with the optimal reactive power dispatch problem to trace the generator minimal reactive power for sustaining the real power transaction and enhancing the system security by meeting the demand. The Differential Evolution is used for optimal reactive power dispatch. The cost allocation to the generators for the reactive power service based on the opportunity cost method is obtained for 62 Bus Indian Utility Systems.

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27

Suganthi, S. T., and D. Devaraj. "An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system." Measurement and Control 53, no. 7-8 (June 7, 2020): 1231–37. http://dx.doi.org/10.1177/0020294020914930.

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In restructured power systems, transmission congestion is an imperative issue. Establishment of solar photovoltaic system at appropriate areas is likely to relieve congestion in transmission lines in the restructured power systems. Congestion management technique by utilizing solar photovoltaic sources, using an improved teaching learning–based optimization, is investigated in this article. Bus sensitivity factors which have the direct influence on the congested lines are utilized to locate the solar photovoltaic sources at appropriate areas. Congestion management is figured as an optimization problem with a goal of limiting the congestion management price utilizing the improved teaching learning–based optimization approach, which espouses the self-driven learning principle. IEEE-30 bus test system is simulated and tested in MATLAB environment so as to demonstrate the viability of the suggested methodology than different methodologies.

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28

Kavitha, M. "Designing of Dynamic Voltage Restorer (DVR) to Improve the Power Quality for Restructured Power Systems." American Journal of Electrical Power and Energy Systems 2, no. 3 (2013): 94. http://dx.doi.org/10.11648/j.epes.20130203.15.

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29

Eladl, A., A. Elmitwally, S. Eskander, and I. Mansy. "Optimal Allocation of FACTS Devices in Restructured Power Systems Integrated Wind Generation." Bulletin of the Faculty of Engineering. Mansoura University 40, no. 1 (July 5, 2020): 26–41. http://dx.doi.org/10.21608/bfemu.2020.100769.

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30

Manikandan, B. V., S. Charles Raja, P. Venkatesh, and Manasarani Mandala. "Comparative Study of Two Congestion Management Methods for the Restructured Power Systems." Journal of Electrical Engineering and Technology 6, no. 3 (May 2, 2011): 302–10. http://dx.doi.org/10.5370/jeet.2011.6.3.302.

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31

Fetanat, Abdolvahhab, and Gholamreza Shafipour. "Mixed Biogeography-Based Optimization for GENCOs’ Maintenance Scheduling in Restructured Power Systems." Applied Artificial Intelligence 32, no. 1 (January 2, 2018): 65–84. http://dx.doi.org/10.1080/08839514.2018.1448158.

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32

Vahidinasab, V., S. Jadid, and A. Kazemi. "Day-ahead price forecasting in restructured power systems using artificial neural networks." Electric Power Systems Research 78, no. 8 (August 2008): 1332–42. http://dx.doi.org/10.1016/j.epsr.2007.12.001.

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33

Ding, Yi, Anatoly Lisnianski, Peng Wang, Lalit Goel, and Loh Poh Chiang. "Dynamic reliability assessment for bilateral contract electricity providers in restructured power systems." Electric Power Systems Research 79, no. 10 (October 2009): 1424–30. http://dx.doi.org/10.1016/j.epsr.2009.04.014.

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34

Arya, Yogendra, and Narendra Kumar. "Optimal AGC with redox flow batteries in multi-area restructured power systems." Engineering Science and Technology, an International Journal 19, no. 3 (September 2016): 1145–59. http://dx.doi.org/10.1016/j.jestch.2015.12.014.

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35

Geetha, T., and K. Shanti Swarup. "Coordinated preventive maintenance scheduling of GENCO and TRANSCO in restructured power systems." International Journal of Electrical Power & Energy Systems 31, no. 10 (November 2009): 626–38. http://dx.doi.org/10.1016/j.ijepes.2009.06.006.

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36

Vaahedi, E., and M. Shahidehpour. "Decision Support Tools in Restructured Electricity Systems: An Overview." IEEE Transactions on Power Systems 19, no. 4 (November 2004): 1999–2005. http://dx.doi.org/10.1109/tpwrs.2004.831668.

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37

Debbarma, Sanjoy, and Arunima Dutta. "Utilizing Electric Vehicles for LFC in Restructured Power Systems Using Fractional Order Controller." IEEE Transactions on Smart Grid 8, no. 6 (November 2017): 2554–64. http://dx.doi.org/10.1109/tsg.2016.2527821.

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38

Felder, Frank A. "The Need for Governance of Restructured Electric Power Systems and Some Policy Implications." Electricity Journal 15, no. 1 (January 2002): 36–43. http://dx.doi.org/10.1016/s1040-6190(01)00265-2.

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39

Wang, P., Y. Ding, and Y. Xiao. "Technique to evaluate nodal reliability indices and nodal prices of restructured power systems." IEE Proceedings - Generation, Transmission and Distribution 152, no. 3 (2005): 390. http://dx.doi.org/10.1049/ip-gtd:20041250.

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40

Elmitwally, A., and A. Eladl. "Planning of multi-type FACTS devices in restructured power systems with wind generation." International Journal of Electrical Power & Energy Systems 77 (May 2016): 33–42. http://dx.doi.org/10.1016/j.ijepes.2015.11.023.

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41

Kamyab, G. R., M. Fotuhi-Fri, and M. Rashidinej. "Transmission Expansion Planning in Restructured Power Systems Considering Investment Cost and n-1 Reliability." Journal of Applied Sciences 8, no. 23 (November 15, 2008): 4312–20. http://dx.doi.org/10.3923/jas.2008.4312.4320.

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42

Samadi, Mahdi, Mohammad Hossein Javidi, and Mohammad Sadegh Ghazizadeh. "Modeling the effects of demand response on generation expansion planning in restructured power systems." Journal of Zhejiang University SCIENCE C 14, no. 12 (December 2013): 966–76. http://dx.doi.org/10.1631/jzus.c1300008.

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43

Tam, Kwa-Sur. "New opportunities for fuel cells in the restructured power systems of the United States." Journal of Power Sources 71, no. 1-2 (March 1998): 190–94. http://dx.doi.org/10.1016/s0378-7753(97)02759-6.

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44

Reddy, K. Srikanth, Lokesh Panwar, B. K. Panigrahi, and Rajesh Kumar. "Modelling and analysis of resource scheduling in restructured power systems considering wind energy uncertainty." International Journal of Sustainable Energy 37, no. 8 (May 31, 2017): 736–60. http://dx.doi.org/10.1080/14786451.2017.1334655.

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45

Shaban-Boloukat, M. H., K. Afshar, and N. Bigdeli. "An effective method for generation expansion planning in restructured power systems with considering emission." International Journal of Advanced Manufacturing Technology 73, no. 9-12 (May 22, 2014): 1399–411. http://dx.doi.org/10.1007/s00170-014-5909-1.

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46

Nikzad, Mehdi, and Babak Mozafari. "Reliability assessment of incentive- and priced-based demand response programs in restructured power systems." International Journal of Electrical Power & Energy Systems 56 (March 2014): 83–96. http://dx.doi.org/10.1016/j.ijepes.2013.10.007.

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47

Feng, Changyou, Xifan Wang, and Jianxue Wang. "Iterative approach to generator maintenance schedule considering unexpected unit failures in restructured power systems." European Transactions on Electrical Power 21, no. 1 (February 26, 2010): 142–54. http://dx.doi.org/10.1002/etep.422.

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48

Zhou, Hanmei, Qishui Zhong, Shaoyu Hu, Jin Yang, Kaibo Shi, and Shouming Zhong. "Dissipative Discrete PID Load Frequency Control for Restructured Wind Power Systems via Non-Fragile Design Approach." Mathematics 11, no. 14 (July 24, 2023): 3252. http://dx.doi.org/10.3390/math11143252.

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This article proposes a discrete proportional-integral-derivative (PID) load frequency control (LFC) scheme to investigate the dissipative analysis issue of restructured wind power systems via a non-fragile design approach. Firstly, by taking the different power-sharing rates of governors into full consideration, a unified model is constructed for interconnected power systems containing multiple governors. Secondly, unlike existing LFC schemes, a non-fragile discrete PID control scheme is designed, which has the performance of tolerating control gain fluctuation and relieving the huge computational burden. Further, by constructing a discrete-type Lyapunov–Krasovskii functional, improved stability criteria with a strict dissipative performance index are established. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed control method.

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49

Vaahedi, E., and M. Shahidehpour. "Guest editorial special section on tools for managing restructured energy systems." IEEE Transactions on Power Systems 18, no. 2 (May 2003): 420–21. http://dx.doi.org/10.1109/tpwrs.2003.810668.

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50

Pourahmadi, Farzaneh, and Payman Dehghanian. "A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations." Mathematics 6, no. 9 (September 6, 2018): 158. http://dx.doi.org/10.3390/math6090158.

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Allocation of the power losses to distributed generators and consumers has been a challenging concern for decades in restructured power systems. This paper proposes a promising approach for loss allocation in power distribution systems based on a cooperative concept of game-theory, named Shapley Value allocation. The proposed solution is a generic approach, applicable to both radial and meshed distribution systems as well as those with high penetration of renewables and DG units. With several different methods for distribution system loss allocation, the suggested method has been shown to be a straight-forward and efficient criterion for performance comparisons. The suggested loss allocation approach is numerically investigated, the results of which are presented for two distribution systems and its performance is compared with those obtained by other methodologies.

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