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Relevant bibliographies by topics / Optimal power dispatch

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Journal articles

Academic literature on the topic 'Optimal power dispatch'

Author: Grafiati

Published: 23 September 2022

Last updated: 11 June 2025

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Journal articles on the topic "Optimal power dispatch"

1

Dhillon, J. S., S. C. Parti, and D. P. Kothari. "Multiobjective optimal thermal power dispatch." International Journal of Electrical Power & Energy Systems 16, no. 6 (1994): 383–89. http://dx.doi.org/10.1016/0142-0615(94)90025-6.

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2

Ajjarapu, Venkataramana, J. Carr, and R. S. Ramshaw. "Security constrained optimal reactive power dispatch." Electric Power Systems Research 16, no. 3 (1989): 209–16. http://dx.doi.org/10.1016/0378-7796(89)90013-8.

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3

Fikri Ruslan, Nabil, Ismail Musirin, Mohamad Khairuzzaman Mohamad Zamani, et al. "Power Tracing Monitoring incorporating Optimal Reactive Power Dispatch." International Journal of Engineering & Technology 7, no. 3.15 (2018): 1. http://dx.doi.org/10.14419/ijet.v7i3.15.17394.

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General power flow studies do not manage to trace the contributors by generators on power losses in the whole power transmission system. Thus, power tracing approach is utilized to address this issue. Power tracing is a termed used to describe the contributors for the power losses dissipated on the transmission line. The traditional technique made use the knowledge of circuit analysis such as cut set theory. However, there was no element of optimization which can help to achieve the optimal solution. This paper presents the power tracing monitoring during voltage stability improvement process, implemented by optimal reactive power dispatch. In this study, the impact of power tracing on voltage stability variation was investigated. Evolutionary Programming (EP) was developed and utilized to incorporate power tracing, along with voltage stability improvement. A pre-developed scalar voltage stability index was incorporated to indicate the voltage stability condition. On the other hand, the voltage stability initiative was conducted via the optimal reactive power dispatch. The power tracing was monitored for both; the pre-optimization and post-optimization scenarios. Small system model was tested to realize the power tracing phenomenon, which is rather rare study in power system community. Results on power tracing obtained during the pre- and post-optimal reactive power dispatch revealed that not all generators will involve in the contribution on the total transmission loss in the system. This can be beneficial to power system operators for allocating the cost without discrimination in the long run.

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4

Moreno, Ricardo, Johan Obando, and Gabriel Gonzalez. "An integrated OPF dispatching model with wind power and demand response for day-ahead markets." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 2794. http://dx.doi.org/10.11591/ijece.v9i4.pp2794-2802.

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In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system.

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5

M, Lakshmi, and Ramesh Kumar A. "Optimal Reactive Power Dispatch using Crow Search Algorithm." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 3 (2018): 1423. http://dx.doi.org/10.11591/ijece.v8i3.pp1423-1431.

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<p>The optimal reactive power dispatch is a kind of optimization problem that plays a very important role in the operation and control of the power system. This work presents a meta-heuristic based approach to solve the optimal reactive power dispatch problem. The proposed approach employs Crow Search algorithm to find the values for optimal setting of optimal reactive power dispatch control variables. The proposed way of approach is scrutinized and further being tested on the standard IEEE 30-bus, 57-bus and 118-bus test system with different objectives which includes the minimization of real power losses, total voltage deviation and also the enhancement of voltage stability. The simulation results procured thus indicates the supremacy of the proposed approach over the other approaches cited in the literature.</p>

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6

Peng, Lai. "Optimal Dispatch in Power Systems with Intermittent Power Sources." Computational Water, Energy, and Environmental Engineering 09, no. 04 (2020): 101–7. http://dx.doi.org/10.4236/cweee.2020.94008.

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7

Wu, Q. H., and J. T. Ma. "Power system optimal reactive power dispatch using evolutionary programming." IEEE Transactions on Power Systems 10, no. 3 (1995): 1243–49. http://dx.doi.org/10.1109/59.466531.

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8

Loriya, Vismay, and Vishnu Patel. "A Review on Optimal Reactive Power Dispatch." IJIREEICE 4, no. 1 (2016): 83–87. http://dx.doi.org/10.17148/ijireeice.2016.4120.

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9

Preedavichit, Preecha, and S. C. Srivastava. "Optimal reactive power dispatch considering FACTS devices." Electric Power Systems Research 46, no. 3 (1998): 251–57. http://dx.doi.org/10.1016/s0378-7796(98)00075-3.

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10

Bhongade, Sandeep, and Aakash Tomar. "Optimal Reactive Power Dispatch Optimization Using STATCOM." Journal of The Institution of Engineers (India): Series B 102, no. 2 (2021): 277–93. http://dx.doi.org/10.1007/s40031-021-00537-1.

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