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Flexible Robust Optimization Dispatch for Hybrid Wind/Photovoltaic/Hydro/Thermal Power System

机译:灵活的鲁棒优化调度,用于混合风力/光伏/水电/火电系统

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With sustained growth of intermittent power supplies connected to grid, the randomness and volatility of intermittent power supplies will bring new challenges to power system optimization dispatch. For dealing with the uncertainty of large-scale intermittent power supply, this paper introduces robust optimization theory into optimization dispatch for hybrid wind/photovoltaic/hydro/thermal power systems. Meanwhile in order to make an ideal compromise between reliability and economy of system dispatch, this paper also introduces concept of uncertainty to cover shortcoming of conventional robust optimization which is conservative. A flexible robust optimization with adjustable uncertainty budget dispatch model is built for hybrid power system to achieve coordination between reliability and economy, and then the uncertainty budget decision methods are studied to reduce blindness of uncertainty budget decisions. Moreover, a new compound differential evolution (CDE) algorithm is designed in this paper. The diversity of individuals and convergence speed are taken into account in process of differential evolution (DE) calculation by introducing a series of operations into DE algorithm, such as individual ranking, population dividing, CDE, and population restructuring. Finally, a sample application is carried out to verify the validity and practicability of the model and the method.
机译:随着连接到电网的间歇电源的持续增长,间歇电源的随机性和波动性将给电力系统优化调度带来新的挑战。为了解决大型间歇性电源的不确定性问题,本文将鲁棒优化理论引入到风电/光伏/水电/火电混合动力系统的优化调度中。同时,为了在可靠性和系统调度的经济性之间做出理想的折衷,本文还引入了不确定性的概念,以弥补传统鲁棒优化的不足。针对混合动力系统建立了具有可调不确定性预算分配模型的柔性鲁棒优化算法,以实现可靠性与经济性之间的协调,研究了不确定性预算决策方法,以减少不确定性预算决策的盲目性。此外,本文还设计了一种新的复合差分进化算法。通过在DE算法中引入一系列运算,例如个体排名,人口划分,CDE和人口重组,在差异演化(DE)计算过程中考虑了个体的多样性和收敛速度。最后,通过样本应用验证了该模型和方法的有效性和实用性。

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