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Power Flow Management With Demand Response Profiles Based on User-Defined Area, Load, and Phase Classification
- Source :
- IEEE Access, Vol 8, Pp 218813-218827 (2020)
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- 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.
- Subjects :
- energy management
General Computer Science
Energy management
Computer science
020209 energy
02 engineering and technology
Power factor
Dynamic load testing
Supply and demand
Demand response
Load management
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
smart grid
business.industry
General Engineering
Power flow analysis
load aggregation model
Energy consumption
Reliability engineering
dynamic demand response
Electricity generation
Smart grid
Distributed generation
020201 artificial intelligence & image processing
lcsh:Electrical engineering. Electronics. Nuclear engineering
Electric power
Voltage regulation
business
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....cdce4393bce2c08d4be7c4d47355fbd5