Building agents for power trading agent competition (TAC)
Sustainable power system requires not only environmentally friendly, cost-efficient and renewable energy, but more efficient than the allocation. Power Trading Agent Competition (Power TAC) is organized by the independent transaction AAMAS annual contest, which models the future energy market. Part...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/10356/67397 |
| _version_ | 1811681017446006784 |
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| author | Chen, Jiaqi |
| author2 | Bo An |
| author_facet | Bo An Chen, Jiaqi |
| author_sort | Chen, Jiaqi |
| collection | NTU |
| description | Sustainable power system requires not only environmentally friendly, cost-efficient and renewable energy, but more efficient than the allocation. Power Trading Agent Competition (Power TAC) is organized by the independent transaction AAMAS annual contest, which models the future energy market.
Parties involved in simulation model including customers, power producers, and brokers. Customer representatives of both power consumption models, such as daily necessities, small to large -scale enterprises, multi- residential buildings, wind farms, solar panels and electric vehicle owners. At the same time who can resell excess electricity market parties. Brokers aim to provide electricity in the wholesale market for the energy customers and trading buy low sell high, and carefully balance their portfolio of power supply and demand profit. Power tariff duties may be generally who consume power or power purchase price from customers who generate electricity, and additional resale customers. In the wholesale market, the broker can buy or sell by the producers, industrial sites and other power brokers. In summary, profit maximizer broker acts as an intermediary in the competition.
The goal of the project is to establish a trade agency, to maximize profits provided scenarios. Therefore, we studied a number of other universities and research work already completed brokers. In addition, we also investigated a number of classical algorithms in order to make some assumptions, and through the establishment of a proxy simple scenario. |
| first_indexed | 2024-10-01T03:34:15Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/67397 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:34:15Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/673972023-03-03T20:31:22Z Building agents for power trading agent competition (TAC) Chen, Jiaqi Bo An School of Computer Engineering DRNTU::Science Sustainable power system requires not only environmentally friendly, cost-efficient and renewable energy, but more efficient than the allocation. Power Trading Agent Competition (Power TAC) is organized by the independent transaction AAMAS annual contest, which models the future energy market. Parties involved in simulation model including customers, power producers, and brokers. Customer representatives of both power consumption models, such as daily necessities, small to large -scale enterprises, multi- residential buildings, wind farms, solar panels and electric vehicle owners. At the same time who can resell excess electricity market parties. Brokers aim to provide electricity in the wholesale market for the energy customers and trading buy low sell high, and carefully balance their portfolio of power supply and demand profit. Power tariff duties may be generally who consume power or power purchase price from customers who generate electricity, and additional resale customers. In the wholesale market, the broker can buy or sell by the producers, industrial sites and other power brokers. In summary, profit maximizer broker acts as an intermediary in the competition. The goal of the project is to establish a trade agency, to maximize profits provided scenarios. Therefore, we studied a number of other universities and research work already completed brokers. In addition, we also investigated a number of classical algorithms in order to make some assumptions, and through the establishment of a proxy simple scenario. Bachelor of Engineering (Computer Science) 2016-05-16T06:57:50Z 2016-05-16T06:57:50Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67397 en Nanyang Technological University 39 p. application/pdf |
| spellingShingle | DRNTU::Science Chen, Jiaqi Building agents for power trading agent competition (TAC) |
| title | Building agents for power trading agent competition (TAC) |
| title_full | Building agents for power trading agent competition (TAC) |
| title_fullStr | Building agents for power trading agent competition (TAC) |
| title_full_unstemmed | Building agents for power trading agent competition (TAC) |
| title_short | Building agents for power trading agent competition (TAC) |
| title_sort | building agents for power trading agent competition tac |
| topic | DRNTU::Science |
| url | http://hdl.handle.net/10356/67397 |
| work_keys_str_mv | AT chenjiaqi buildingagentsforpowertradingagentcompetitiontac |