Multi-objective bidding strategy for generation company using non-dominated sorting particle swarm optimization | |
| Author | Apinat Saksinchai |
| Call Number | AIT Thesis no.ET-10-02 |
| Subject(s) | Algorithms Power resources--Costs |
| Note | A thesis submitted in partial fulfillment of the requirements for the Degree of Master of Engineering in Energy |
| Publisher | Asian Institute of Technology |
| Abstract | In deregulated power market, the energy price is depending on the action and strategy of the market participants. So, the need of the algorithm to provide the strategic optimal bidding strategy concerning maximization of profit and minimizing risk which is the multi-objective optimization problem is occurred. Therefore, this thesis proposes Multi-objective bidding strategy for Genco using non-dominated sorting particle swarm optimization. Instead of using non-evolutionary algorithms, NSPSO is introduced to solve the multi-objective strategic bidding problem considering expected profit maximization and risk minimization. Monte Carlo simulation is employed to simulate rivals' bidding behavior. Test results indicate that the proposed approach can provide the efficient non-dominated solution front effectively. The proposed method is applied to find the optimal bidding strategy in uniform price spot market. |
| Year | 2010 |
| 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) | Weerakorn Ongsakul; |
| Examination Committee(s) | Marpaung, Charles O. P.;Singh, Jai Govind; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2010 |