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Wind power system with short-term scheduling and economic risk management

Author: RenBoQiang
Tutor: JiangChuanWen
School: Shanghai Jiaotong University
Course: Proceedings of the
Keywords: Wind Power Power Systems Risk Management Short-term scheduling Optimization
CLC: TM614
Type: Master's thesis
Year: 2010
Downloads: 383
Quote: 1
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Abstract


Compared with conventional power generation , wind energy has the advantage of no coal consumption and pollution , but because wind is intermittent and uncertainty , so large-capacity wind farm grid after the power system will give security and stability implications. This paper studies with short-term wind power system dispatch and economic risk management, and will quantify the uncertainty of wind wind power costs into short-term scheduling model and the use of intelligent optimization algorithm find the optimal solution, based on considerations different factors were established two different scheduling models : ( a ) the value at risk (VaR) and conditional value at risk (CvaR) theory into wind power system with short-term scheduling model is established based on CVaR containing Wind Farm power system short-term scheduling model and genetic algorithm, immune algorithm and adaptive theory established by combining the adaptive immune genetic algorithm (IAGA) for optimization calculations . ( 2 ) Considering wind power shortages and surpluses for the scheduling policy impact and wind power pollution-free advantages, in the model were added to the alternate penalty function, wind power surplus penalty function and contamination assessment penalty function, thus establishing consider comprehensive benefits including wind power system short-term scheduling model . Combined with chaos theory, particle swarm optimization, theory and adaptive immune algorithm based on artificial immune system chaotic particle swarm optimization (ICPSO) to optimize the model calculations . By ten systems and the Shanghai real simulation system simulation results can be seen , with the wind farm and the simulation system size increases , its non- coal and non-polluting and more obvious advantages , but the wind speed to the system with uncertainty to the effect increases. Meanwhile in the optimization algorithms , IAGA and ICPSO the convergence speed and accuracy are superior to traditional optimization algorithms.

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CLC: > Industrial Technology > Electrotechnical > Power generation, power plants > Variety of power generation > Wind power
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