DocumentCode
713408
Title
Energy bidding in a day-ahead electricity market using fuzzy optimization
Author
Ijaz, Muhammad ; Sahito, Muhammad Faraz ; Al-Awami, Ali T.
Author_Institution
Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
fYear
2015
fDate
17-19 March 2015
Firstpage
2388
Lastpage
2393
Abstract
Optimal bidding is considered to be one of the most challenging task for energy producers to bid in a day ahead electricity market. The randomness and uncertain nature associated with the generation of stochastic resources further increase the complexity of the problem. In this paper, an optimal bidding strategy is developed for a Generation Company (GENCO) to participate in a day ahead electricity market, taking into account conventional and stochastic generation resources. GENCO tries to maximize the profit and minimize the risk associated with the uncertainty of stochastic generation and market price. An optimal bidding strategy is developed to participate in a day-ahead market to achieve GENCO owner maximized profit and reduced risk for the system operator. The problem is formulated as a fuzzy Mixed Integer Linear Programming (MILP).
Keywords
fuzzy systems; integer programming; linear programming; power generation economics; power markets; tendering; GENCO; Generation Company; MILP; day-ahead electricity market; energy bidding; fuzzy mixed integer linear programming; fuzzy optimization; stochastic resources generation; Electricity supply industry; Generators; Optimization; Production; Schedules; Stochastic processes; Uncertainty; Day-Ahead Market; Energy Bidding; Fuzzy optimization; MILP; Market Price Forecast;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology (ICIT), 2015 IEEE International Conference on
Conference_Location
Seville
Type
conf
DOI
10.1109/ICIT.2015.7125450
Filename
7125450
Link To Document