1
Financial transmission right bidding strategy in competitive power market using particle swarm optimization | |
Author | Yada Rungreang |
Call Number | AIT Thesis no.ET-10-09 |
Subject(s) | Electric power systems--Marketing |
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 | Financial Transmission Right (FTR) is a financial instrument designed to provide a risk hedge for market participants. The owner of an FTR receives a credit to counteract the congestion charge, and can transfer power over a constrained path for a fixed price. In this study, Particle Swarm Optimization (PSO) is used to solve FTR bidding strategies in auction markets. There are three cases study in this thesis. The first case study on 8-bus system is focusing on the implementation of PSO to solve FTR bidding strategies problem. The second case study on 3-bus system uses the same PSO to determine different considering option and obligation FTR bidding strategies. The third case study on the 3-bus system is risk analysis associated with holding an FTR. In the first case, test results indicate that FTR profit from PSO method is higher than bi-level optimization method. Small standard deviation for 30 runs shows the consistency of this algorithm. Comparison of obligation and option in indicate that bidder would have to pay a much higher price to buy an FTR option. For the third case, the results show that if the risk coefficient is low, bidders would obtain a higher available FTR. Conversely, when the risk coefficient is high, bidders would obtain no FTR. The reason is that when the risk coefficient is low, the risk penalty item in the objective function is relatively small, compared to the revenue item. That is, the risk penalty item would have little impact on the result of FTR bidding. A similar argument could be made when the risk coefficient is relatively high which will result in a high-risk penalty. Accordingly, proper risk coefficients play significant role in FTR bidding. |
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;Sing, Jai Govind; |
Scholarship Donor(s) | RTG Fellowship; |
Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2010 |