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Energy storage dispatch using adaptive control scheme considering wind-PV in smart distribution network

机译:智能配电网中考虑风能-光伏发电的自适应控制方案的储能调度

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This paper presents an adaptive control scheme for optimal dispatch of energy storage systems (ESS) to follow the pattern of intermittent power output of renewable energy sources (RES) in electric power distribution networks with the goal to minimize costs and reduce the need to compensate the variability and uncertainty of RES, mainly wind and solar. The proposed control scheme utilizes day-ahead forecasts of wind and photovoltaic (PV) power output obtained from hybrid intelligent methods. Once the forecasts are obtained, unit commitment (UC) is executed using forecasted data of load as well as wind and PV power in order to schedule optimal generation. The operational decisions are then fed into the economic dispatch (ED) problem, which has the control scheme embedded. As the actual power output of wind-PV deviates from the desired value due to forecast error, the adaptive control scheme developed in this paper assists the ESS to compensate the difference by charging or discharging. In order to evaluate the effectiveness of the proposed model, this paper considers a case study of a sixteen-bus test system and the results indicate that the ESS can reduce the deviation of the wind-PV power output between 1-5%.
机译:本文提出了一种自适应控制方案,用于优化储能系统(ESS)的分布,以遵循配电网络中可再生能源(RES)的间歇性输出功率的模式,旨在最大程度地降低成本并减少对电网的补偿需求RES的可变性和不确定性,主要是风能和太阳能。提出的控制方案利用了从混合智能方法获得的风能和光伏(PV)功率输出的日前预测。一旦获得了预测,就可以使用负荷以及风能和光伏发电的预测数据执行机组承诺(UC),以安排最佳发电量。然后将操作决策输入到经济调度(ED)问题中,该问题已嵌入控制方案。由于风电PV的实际功率输出由于预测误差而偏离了期望值,因此本文开发的自适应控制方案可帮助ESS通过充电或放电来补偿差异。为了评估该模型的有效性,本文考虑了一个16总线测试系统的案例研究,结果表明ESS可以将风力PV功率输出的偏差减小1至5%。

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