Local energy trading in a community micro-grid
In this report, we focus on recreating an incremental welfare consensus algorithm to calculate the optimal price of electricity for users in a grid with multiple consumers and producers. The algorithm functions in place of a central coordinator that is normally required and used to price electricity...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/139908 |
| _version_ | 1826123839997739008 |
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| author | Chan, Adriel Chun Whye |
| author2 | Gooi Hoay Beng |
| author_facet | Gooi Hoay Beng Chan, Adriel Chun Whye |
| author_sort | Chan, Adriel Chun Whye |
| collection | NTU |
| description | In this report, we focus on recreating an incremental welfare consensus algorithm to calculate the optimal price of electricity for users in a grid with multiple consumers and producers. The algorithm functions in place of a central coordinator that is normally required and used to price electricity. Two algorithms were recreated; one to obtain data using a method requiring the use of a central coordinator to calculate the optimal price of electricity, and one implementing the IWC algorithm to calculate the optimal price of electricity without a central coordinator i.e. the consumers/producers coordinate among themselves to find the optimal price. The main points of data gathered were each consumer/producer unit’s power demand or generation, and the optimal price of electricity. Data analysis was done using pandas, and output via .csv file for plotting in Microsoft Excel. |
| first_indexed | 2024-10-01T06:11:13Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/139908 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:11:13Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1399082023-07-07T18:41:26Z Local energy trading in a community micro-grid Chan, Adriel Chun Whye Gooi Hoay Beng School of Electrical and Electronic Engineering EHBGOOI@ntu.edu.sg Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution In this report, we focus on recreating an incremental welfare consensus algorithm to calculate the optimal price of electricity for users in a grid with multiple consumers and producers. The algorithm functions in place of a central coordinator that is normally required and used to price electricity. Two algorithms were recreated; one to obtain data using a method requiring the use of a central coordinator to calculate the optimal price of electricity, and one implementing the IWC algorithm to calculate the optimal price of electricity without a central coordinator i.e. the consumers/producers coordinate among themselves to find the optimal price. The main points of data gathered were each consumer/producer unit’s power demand or generation, and the optimal price of electricity. Data analysis was done using pandas, and output via .csv file for plotting in Microsoft Excel. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-22T08:03:53Z 2020-05-22T08:03:53Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/139908 en A1073-191 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution Chan, Adriel Chun Whye Local energy trading in a community micro-grid |
| title | Local energy trading in a community micro-grid |
| title_full | Local energy trading in a community micro-grid |
| title_fullStr | Local energy trading in a community micro-grid |
| title_full_unstemmed | Local energy trading in a community micro-grid |
| title_short | Local energy trading in a community micro-grid |
| title_sort | local energy trading in a community micro grid |
| topic | Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution |
| url | https://hdl.handle.net/10356/139908 |
| work_keys_str_mv | AT chanadrielchunwhye localenergytradinginacommunitymicrogrid |