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
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;
Conference_Titel :
Industrial Technology (ICIT), 2015 IEEE International Conference on
Conference_Location :
Seville
DOI :
10.1109/ICIT.2015.7125450