Data-Driven Load Modeling to Analyze the Frequency of System Including Demand Response: A Colombian Study Case

• Published in: IEEE access Vol. 9; pp. 50332 - 50343
• Main Authors: Arango-Manrique, Adriana, Lopez, Luis, Ramirez-Ortiz, Juan, Oliveros, Ingrid
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biological system modeling; Demand response; Distributed generation; Distributed power generation; DR strategies; Electric power demand; Electrical loads; Electricity supply industry; Frequency analysis; Frequency variation; Impact analysis; Load management; Load modeling; Power measurement; Power systems; Reactive power; renewable energy; Stress concentration; Time of use
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3069006

This paper analyzes the potential impact of implementing demand response strategies in a power system. This work aims to present a methodology to evaluate three demand response models to reduce frequency variations in the system. The method starts with the modeling of the system load and the demand response strategies. The power loads are modeled through active power and reactive power measurements in the system's different buses. A data-driven methodology is proposed to obtain three profiles that simulate residential, commercial, and industrial users' behavior. Mathematical modeling is proposed for demand response strategies. Time of Use tariff, Solar PV Distributed Generation, and Load Curtailment are the strategies used for residential, commercial, and industrial users, respectively. A brand-new combination of scenarios is developed in this paper with different penetration levels of the demand response strategy. Besides, a novel analysis of the frequency profile is performed for the proposed scenarios. A modified IEEE-39 power system is proposed, adjusting generation and demand using the Colombian demand profile and the generating units' energy mix. The results indicate that the implementation of demand response strategies improves the system's frequency profile. The frequency drop was reduced by 11.4 %, and power generator units released up to 2.1 GWh through the day with the implementation of the DR strategies.