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Development of smart controller for demand side management in smart grid using reactive power optimization
- Source :
- Soft Computing. 25:1581-1594
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Reactive power optimization is one of the major problems of concern in smart grid (SG) environment. Although several techniques have been proposed for reactive power optimization, demand side management (DSM) plays a vital role in smart grid networks. The main idea of this work is to address reactive power optimization by developing a smart controller for DSM by effective monitoring of real power loss in the smart grid network. The proposed smart controller is developed by formulating the DSM as an optimization problem and obtaining its solution by applying elephant herd optimization–firefly (EHO–FF) evolutionary algorithm. Further, the proposed smart controller for DSM aims to meet the power demand and limit the power flow in transmission network by adding distributed generation (DGs) units at optimal locations. The proposed work aims to improve the energy efficiency and voltage profile in the power grid network when operating under different load scenarios. The benchmark IEEE 30 bus system consisting of 6 generating units, 41 transmission lines with total load of 283.4 MW and 126.2 MVAR is used as the test system in this work. The test system is subjected to varying load pattern for 24 h in a typical day. The performance of the proposed smart controller is evaluated on the bench mark IEEE 30 bus system through program code developed in MATLAB environment. The simulation results have proved that the proposed smart controller for DSM minimizes the power loss and improves the voltage profile significantly by incorporating DG units in optimal locations. The effectiveness of the EHO–FF algorithm is analyzed by comparing the results obtained with PSO and bAT algorithm.
- Subjects :
- 0209 industrial biotechnology
Optimization problem
business.industry
Computer science
Control engineering
02 engineering and technology
AC power
Theoretical Computer Science
020901 industrial engineering & automation
Electric power transmission
Smart grid
Control theory
Distributed generation
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Smart grid network
Geometry and Topology
Power grid
business
Software
Bat algorithm
Voltage
Efficient energy use
Subjects
Details
- ISSN :
- 14337479 and 14327643
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- Soft Computing
- Accession number :
- edsair.doi...........ddb13aa0373c6c06da0ad8de359822ed
- Full Text :
- https://doi.org/10.1007/s00500-020-05246-3