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Power system dynamic economic dispatch with wind-solar integration based on particle swarm intelligent searching algorithm

机译:基于粒子群智能搜索算法的风光集成电力系统动态经济调度

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With the larger scale of renewable energy sources connected to power system, the power grid operation has to deal with even more uncertainties. It is significant to describe the randomness and intermittence of renewable energy accurately, and take into account the correlation of different renewable energy sources generation. Copula function is proposed to formulate the randomness and correlation of wind-solar power generation in this paper. Based on some important correlation indexes, such as Kendall correlation coefficient, the Copula function can be determined. In order to deal with the stochastic characteristics of wind-solar power generation, the scenario method is proposed to establish the day-ahead dynamic economic dispatch model considering the correlation of wind-solar power generation. The particle swarm intelligent searching algorithm is then introduced to solve it, which is good at overcoming the inherent “curses of dimensionality”. The proposed model and algorithm are finally verified by the IEEE 39-bus system.
机译:随着连接到电力系统的可再生能源的规模越来越大,电网运行必须处理更多的不确定性。准确描述可再生能源的随机性和间歇性,并考虑到不同可再生能源来源之间的相关性,具有重要意义。提出了Copula函数来表达风光发电的随机性和相关性。基于一些重要的相关指标,例如Kendall相关系数,可以确定Copula函数。针对风光发电的随机性,提出了一种情景方法,建立了考虑风光发电相关性的日动态经济调度模型。然后引入粒子群智能搜索算法对其进行求解,该算法很好地克服了固有的“维数曲线”。最终,所提出的模型和算法已通过IEEE 39总线系统进行了验证。

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