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首页> 外文期刊>Electric power systems research >Optimal capacity planning of generation system integrating uncertain solar and wind energy with seasonal variability
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Optimal capacity planning of generation system integrating uncertain solar and wind energy with seasonal variability

机译：结合不确定性的太阳能和风能的季节性变化的发电系统的最优容量规划

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摘要

This paper presents a generation capacity planning model for integration of utility-scale wind farms and grid-connected solar photovoltaic (PV) generation systems via multi-stage stochastic programming. A multi-stage scenario tree for available wind power, electric load, and solar irradiance is constructed with nine stages for a year. Random samples for wind, load, and solar irradiance are generated using Gaussian copula which represents correlation between random samples. Environmental energy policies to control carbon dioxide (CO2) emissions and increase energy generation from renewable sources are implemented, and the resulting generation capacity mix is investigated. A case study with a modified IEEE 300-bus system is performed. With the presented model, optimal generation capacity satisfying policy constraints in a future time was found within a reasonable amount of time.
机译：本文提出了一种发电容量规划模型，用于通过多阶段随机规划将公用事业规模的风电场和并网太阳能光伏发电系统集成在一起。一年中有九个阶段，用于构建可用风能，电负载和太阳辐照度的多阶段方案树。使用代表随机样本之间相关性的高斯copula生成风，负载和太阳辐照度的随机样本。实施了控制二氧化碳（CO2）排放并增加可再生能源发电量的环境能源政策，并研究了由此产生的发电量组合。用改进的IEEE 300总线系统进行了案例研究。利用提出的模型，可以在合理的时间内找到满足政策约束的最优发电能力。

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