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Economic Analysis of Demand Response Incorporated Optimal Power Flow

Ulagammai Meyyappan*, S. Joyal Isac

Department of EEE, Saveetha Engineering College, Chennai, 602105, India

* Corresponding Author: Ulagammai Meyyappan. Email: email

Intelligent Automation & Soft Computing 2023, 35(1), 399-413. https://doi.org/10.32604/iasc.2023.026627

Abstract

Demand Response (DR) is one of the most cost-effective and unfailing techniques used by utilities for consumer load shifting. This research paper presents different DR programs in deregulated environments. The description and the classification of DR along with their potential benefits and associated cost components are presented. In addition, most DR measurement indices and their evaluation are also highlighted. Initially, the economic load model incorporated thermal, wind, and energy storage by considering the elasticity market price from its calculated locational marginal pricing (LMP). The various DR programs like direct load control, critical peak pricing, real-time pricing, time of use, and capacity market programs are considered during this study. The effect of demand response in electricity prices is highlighted using a simulated study on IEEE 30 bus system. Simulation is done by the Shuffled Frog Leap Algorithm (SFLA). Comprehensive performance comparison on voltage deviations, losses, and cost with and without considering DR is also presented in this paper.

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Cite This Article

APA Style
Meyyappan, U., Isac, S.J. (2023). Economic analysis of demand response incorporated optimal power flow. Intelligent Automation & Soft Computing, 35(1), 399-413. https://doi.org/10.32604/iasc.2023.026627
Vancouver Style
Meyyappan U, Isac SJ. Economic analysis of demand response incorporated optimal power flow. Intell Automat Soft Comput . 2023;35(1):399-413 https://doi.org/10.32604/iasc.2023.026627
IEEE Style
U. Meyyappan and S.J. Isac, “Economic Analysis of Demand Response Incorporated Optimal Power Flow,” Intell. Automat. Soft Comput. , vol. 35, no. 1, pp. 399-413, 2023. https://doi.org/10.32604/iasc.2023.026627



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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