DocumentCode :
2590164
Title :
A Preliminary Study on Strategic Bidding for Load Server Entities in Single-Seller Electricity Markets with Step-Wise Bidding Protocol
Author :
Chen, Xingying ; Xie, Jun
Author_Institution :
Sch. of Electr. Eng., Hohai Univ., Nanjing
fYear :
2006
fDate :
11-15 June 2006
Firstpage :
1
Lastpage :
6
Abstract :
At the present time, the operating electricity markets of all over the world vary from one country to another, but from the aspect of bidding model, which can be classified into two types: the first one is generation-side bidding only, the second one is generation-side and demand-side bidding simultaneously. Broadly speaking, no matter adopt what type of bidding model, the implementation of electricity markets requires that electricity supplying is relatively sufficient; otherwise the electricity prices will rise and reach to an unreasonable degree. In this paper, single-seller bidding model is proposed, which makes a new way for the solving of electricity prices rising when the market is lack of electricity supply. In single-seller electricity markets, the profits of load server entities (LSEs), to a certain extent, depends on their bidding strategies. As a result, a methodological framework is proposed for developing optimal bidding strategies for LSEs participating in a single-seller 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 building optimal bidding strategies for LSEs is then formulated as a stochastic optimization problem, and solved by Monte-Carlo simulation and genetic algorithm. Finally, taking a single-seller electricity market with 4 LSEs as an example, the proposed bidding strategies model is demonstrated by the simulation results
Keywords :
Monte Carlo methods; genetic algorithms; power markets; pricing; stochastic programming; LSE; Monte-Carlo simulation; demand-side bidding; generation-side bidding; genetic algorithm; load server entities; normal distribution function; pricing; single-seller electricity market; step-wise strategic bidding protocol; stochastic optimization; Electricity supply industry; Energy management; Genetic algorithms; Optimization methods; Power generation; Power industry; Power systems; Protocols; Stochastic processes; Upper bound; Bidding strategies; Load Server Entities (LSEs); Monte-Carlo method; electricity market; genetic algorithm; single-seller; stochastic optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Probabilistic Methods Applied to Power Systems, 2006. PMAPS 2006. International Conference on
Conference_Location :
Stockholm
Print_ISBN :
978-91-7178-585-5
Type :
conf
DOI :
10.1109/PMAPS.2006.360196
Filename :
4202208
Link To Document :
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