For the power market participators, there are competition and more trade opportunities in the power industry under the deregulation. In the electricity market, the bidding model is adopted instead of the cost model. GenCos try to maximize the profit under bidding model according to the power demand. Electricity becomes commodity and its price varies with power demand, bidding strategy and the grid. GenCos perform the unit commitment in a price volatile environment to reach the maximal profit. In a deregulation environment, Independent System Operator (ISO) is very often responsible for the electricity auction and secured power scheduling. The ISO operation may involve all kinds of risks. These risks include price volatility risk, bidding risk, congestion risk, and so on. For some markets, it is very important how GenCos determine the optimal unit commitment schedule considering risk management. A good risk analysis will help GenCo maximize profit and purse sustainable development. In this study, price forecasting is developed to provide information for power producers to develop bidding strategies to maximize profit. Profit-Based Unit Commitment (PBUC) model was also derived. An Enhanced Immune Algorithm (EIA) is developed to solve the PBUC problem. Finally, the Value-at-Risk (VAR) of GenCos is found with a present confident level. Simulation results provide a risk management rule to find an optimal risk control strategy to maximize profit and raise its compatibility against other players.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0727110-174022 |
| Date | 27 July 2010 |
| Creators | Gow, Hong-Jey |
| Contributors | Ming-Tang Tsai, Jen-Hao Teng, Gary W. Chang, Shyh-Jier Huang, Ching-Tzong Su, Whei-Min Lin, Hong-Tzer Yang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727110-174022 |
| Rights | unrestricted, Copyright information available at source archive |
Page generated in 0.0012 seconds