Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/424635
Title: | Optimal sizing with cost analysis of Distributed energy resources in smart Grid environment |
Researcher: | Muthukumaran, E |
Guide(s): | Kalyani, S |
Keywords: | Engineering and Technology Engineering Engineering Electrical and Electronic smart Grid energy resources |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | There is a great challenge in electricity due to the introduction of newlineSmart Grid concept. The distributed generation with renewable energy resources newlineintegration has become the major part of smart grid. The main aim of the smart newlinegrid network is to reduce the system power loss and improve the bus voltage newlineprofile which in turn will help the customers to reduce the total cost incurred. newlineThe varying demand is very normal in distribution system; hence it is necessary newlineto consider generation system with varying load conditions. The Demand Side newlineManagement (DSM) satisfies the varying demand based on consumer newlineparticipation in choice of power generation. DSM makes the customer to avail newlinepower at less cost by optimal allocation of resources for power generation and newlineby reducing their demand. The reactive power optimization problem reduces the newlinepower loss in power system and improves the voltage profile in the system. The newlinemain aim of this work is to address the reactive power optimization and optimal newlinepower flow with integration of Renewable Energy Sources in smart grid newlineenvironment. newlineReactive power optimization is carried out by developing a proposed newlinehybrid Elephant Herd Optimization Firefly (EHO-FF) algorithm for DSM to newlinemeet the power demand and limit the power flow in transmission network by newlineadding Distributed Generation (DGs) units at optimal locations. To show the newlinerobustness of the proposed method, IEEE 30 bus test system and IEEE 57 Bus newlinetest system are considered with randomly varying load patterns. Further, the newlineresults obtained with the proposed hybrid EHO-FF algorithm is verified and newlinecompared with other meta-heuristic algorithms such as PSO and Bat algorithm. newlineThe simulation results have proven that the proposed hybrid EHO-FF algorithm newlineminimizes the real power loss with DG units and also improves the voltage newlineprofile significantly. Thus, the proposed hybrid EHO-FF shows better newlineperformance in meeting the constraints and saving time compared to the other newlineequivalent methods newline |
Pagination: | xvi, 132p. |
URI: | http://hdl.handle.net/10603/424635 |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 412.08 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.65 MB | Adobe PDF | View/Open | |
03_content.pdf | 557.04 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 176.49 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 3.9 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 2.51 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 2.41 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 5.14 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 4.27 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 7.33 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 1.05 MB | Adobe PDF | View/Open |
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