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首页> 外文期刊>Renewable Power Generation, IET >Introduction to Laguerre-based stochastic economic predictive functional control for optimal real-time power dispatch under uncertainty
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Introduction to Laguerre-based stochastic economic predictive functional control for optimal real-time power dispatch under uncertainty

机译：基于Laguerre的随机经济预测功能控制介绍，在不确定性下最佳实时功率调度

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摘要

This study presents a Laguerre-based stochastic economic predictive functional control (L-SEPFC) method for realtime power dispatch of balance responsible parties (BRPs). In this regard, at the control layer, an L-SEPFC method operates on the energy time scale and optimises the expected economic performance of the BRP. Calculated set points in this layer are average power injection of controllable generators, as well as known disturbance of prediction wind generation. The novel L-SEPFC scheme is able to cope with the wind uncertainty occurring in the real-time operation of BRPs. Furthermore, the proposed algorithm is able to take into account the technical constraints of generators and transmission line constraints of the power network. Due to the parameterisation of the future control signal based on the Laguerre function, the proposed method is faster than the nominal predictive algorithms. Simulations on an IEEE 118-bus test system with proposed method shows improvements inability to track reference production, economic performance, imbalance energy and computational burden with respect to nominal predictive controllers.
机译：本研究提出了一种基于Laguerre的随机经济预测功能控制（L-SEPFC）方法，用于余额负责缔约方的实时功率调度（BRPS）。在这方面，在控制层，L-SEPFC方法在能量时间尺度上运行并优化BRP的预期经济性能。该层中计算的设定点是可控发电机的平均功率注入，以及已知的预测风力产生的干扰。新型L-SEPFC方案能够应对BRPS实时运行中发生的风不确定性。此外，所提出的算法能够考虑电网的发电机和传输线约束的技术约束。由于基于Laguerre功能的未来控制信号的参数，所提出的方法比标称预测算法快。具有提出方法的IEEE 118-BUS测试系统的模拟显示出改善无法跟踪标称预测控制器的参考生产，经济性能，不平衡能量和计算负担。

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