
Day-Ahead Demand Response Scheduling to Improve Voltage Stability with Consumer Preference Considerations
Author(s) -
Abdelrahman Abdelkader,
Saad Alzahrani,
Alaaeldein Abdelkader,
Mohammed Benidris,
Joydeep Mitra
Publication year - 2025
Publication title -
ieee transactions on industry applications
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 1.19
H-Index - 195
eISSN - 1939-9367
pISSN - 0093-9994
DOI - 10.1109/tia.2025.3595128
Subject(s) - power, energy and industry applications , signal processing and analysis , fields, waves and electromagnetics , components, circuits, devices and systems
To address the challenges of intermittent renewable energy and new load technologies, utilities have widely adopted Demand Response (DR) as a significant solution for enhancing system flexibility and maintaining stability. This paper proposes a day-ahead scheduling approach that leverages DR to support voltage stability while accounting for consumer preferences, to facilitate incorporating DR aggregations in day-ahead markets and operation planning. Existing DR approaches have been mainly focused on incentivized real-time response rather than exploring the capabilities of DR aggregations to contribute to energy markets and compensate for the controllability that renewables lack. However, communication limitations and uncertainty of consumer participation remains a major limiting factor for real-time implementation. The developed framework targets two main goals: a) it enables participation in energy markets by optimizing and evaluating DR support given consumers' preference, and b) it demonstrates the impact of varying consumer preference on available support. An NSGA-II-based approach is developed with modifications to crossover, mutation, and initialization to expedite convergence and ensure accurate data handling. The proposed approach is applied to the IEEE 33-bus and 141-bus systems for validation. The results show that the convenience/stability trade-off helps consumers to make informed participation decisions. Obtained results can be utilized by operators to set fair and effective DR compensation schemes to achieve the required support levels.
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