Title :
Optimal bidding strategies for LSEs in single-bargainer electricity markets
Author :
Wang, Ping ; Chen, Xingying ; Xie, Jun ; Liao, Yingchen ; Liu, Haoming
Author_Institution :
Coll. of Electr. Eng., Hohai Univ., Nanjing
Abstract :
The single-bargainer bidding model makes a new way for solving electricity prices rising when the market is lack of electricity supply. In the single-bargainer electricity markets, the profits of load serving entities (LSEs), to a certain extent, depend on their bidding strategies. In this paper, a methodological framework is proposed for developing optimal bidding strategies for LSEs participating in a single-bargainer electricity market in which sealed auction with step-wise quantity/price bidding functions and pay-as-bid settlement protocols are utilized. A normal distribution function is used to describe the bidding behaviors of rivals, and the problem of constructing optimal bidding strategies for distribution companies is then formulated as a stochastic optimization problem. The solution is based on the Monte-Carlo method. Finally, a single-bargainer electricity market with 4 LSEs is selected as an bench mark example to demonstrate the effectiveness of the proposed model.
Keywords :
Monte Carlo methods; power distribution economics; power markets; pricing; Monte-Carlo method; electricity pricing; load serving entity; normal distribution function; optimal bidding strategy; pay-as-bid settlement protocol; power distribution company; single-bargainer electricity market; Electricity supply industry; Energy management; Fuzzy sets; Game theory; Gaussian distribution; Probability distribution; Protocols; Relays; Stochastic processes; Upper bound; Bidding strategies; Load Serving Entities (LSEs); electricity market; single-bargainer; stochastic optimization;
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
Conference_Location :
Nanjuing
Print_ISBN :
978-7-900714-13-8
Electronic_ISBN :
978-7-900714-13-8
DOI :
10.1109/DRPT.2008.4523460