Optimal bidding strategy in a competitive market using genetic algorithm | |
| Author | Kritsada Japanya |
| Call Number | AIT Thesis no.ET-06-6 |
| Subject(s) | Genetic algorithms Monte Carlo method Letting of contracts |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Environment, Resources and Development |
| Publisher | Asian Institute of Technology |
| Abstract | In this thesis, genetic algorithm is proposed to determine the optimal bidding strategy in competitive auction market. The market includes generating companies (Gencos), large consumers who participate In demand side bidding and small Consumers whose demand is aggregated form. Gencos and large consumers are represented by the artificial intelligent agents, programmed to maximize their profit. BV using previous bidding information and multi-round auction process, the optimal bidding strategy for both Gencos and large consumers is obtained. Test results indicate that the proposed algorithm could provide the same solution but converge much faster and more reliable than Monte Carlo Simulation algorithm. The proposed algorithm can also be applicable to the 24 hours optimal bidding strategy in a day-ahead market. It is shown that the change of market price is in the sane direction as the forecasted demand in particular hour |
| Year | 2006 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Energy Technology (ET) |
| Chairperson(s) | Weerakom Ongsakul; |
| Examination Committee(s) | Surapong Chirarattananon ;Mithulananthan, Nadarajah; |
| Scholarship Donor(s) | Her Majesty the Queen of Thailand ; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2006 |