Power Flow Management With Demand Response Profiles Based on User-Defined Area, Load, and Phase Classification

In recent times, the electric power management based on customers' demand has drawn significant attention of smart-grid (SG) governors. The SG requires real-time management of dynamic load to maintain the quality of service (i.e., balance between supply and demand) by interfacing with users. In...

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Bibliographic Details
Main Authors: Md. Morshed Alam, Md. Shahjalal, Md. Mainul Islam, Moh. Khalid Hasan, Md. Faisal Ahmed, Yeong Min Jang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9276398/
Description
Summary:In recent times, the electric power management based on customers' demand has drawn significant attention of smart-grid (SG) governors. The SG requires real-time management of dynamic load to maintain the quality of service (i.e., balance between supply and demand) by interfacing with users. In this paper, we propose an approach to respond to the active demand (AD) based on user-defined energy-management policy. An algorithm is also proposed for the smart-controller device (SCD) modeled with the load aggregator and connected to the customers. The total contracted load and the user ADs are determined based on area, load, and phase classification, which specify the individual energy consumption. The proposed scheme is implemented in MATLAB/Simulink using the load-information of the IEEE 30-bus system, and the feasibility is assessed in IEEE 13 and IEEE 34 node test feeder systems. By applying the customer's controlled SCD device both the deficiency and redundancy of generation in terms of grid controllable load have been improved that lead the maximization of generation and distribution services. The voltage regulation and power factor of the particular area have been enhanced by integrating appropriate distributed generation and power factor improvement devices. The results garnered from the performance analysis show that the proposed scheme can optimize power generation based on the user-defined demand.
ISSN:2169-3536