Real time optimal power flow integrating large scale storage devices and wind generation

A. Giorgio, F. Liberati, Andrea Lanna
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引用次数: 14

Abstract

This paper presents a real time strategy for optimal power flow in presence of storage devices and wind turbine driven by Doubly Fed Induction Generators. These elements work in cooperation defining a dynamic bus where the generated power is subject to temporal constraints, which establish a coupling between traditional power flow problems related to consecutive time periods; further the uncertainty in wind power generation forecasts requires a continuous update of the planned power profiles, in order to guarantee a dynamic equilibrium among demand and supply. Model predictive control is used for this purpose, considering the dynamic equations of the storage and the wind turbine rotor as prediction models. A proper target function is introduced in order to find a trade-off between the need of minimizing generation costs and the excursions of the storage state of charge and the wind turbine angular speed from reference states. In the case study under consideration storage, wind turbines and a traditional synchronous generator are operated by the Transmission System Operator in the form of a Virtual Power Plant working as slack bus to cover network losses. The proposed approach is validated on simulation basis.
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集成大型存储设备和风力发电的实时最优潮流
本文提出了一种双馈感应发电机驱动的存储设备和风力发电机组存在时的实时优化潮流策略。这些要素协同工作,定义了一个动态总线,其中产生的电力受时间约束,这在与连续时间段相关的传统潮流问题之间建立了耦合;此外,风力发电预测的不确定性要求不断更新计划的电力概况,以保证需求和供应之间的动态平衡。为此,采用模型预测控制方法,以风库和风机转子的动态方程为预测模型。引入合适的目标函数,在发电成本最小化的需求和电荷存储状态与风力机角速度偏离参考状态之间寻找平衡点。在考虑存储的案例研究中,风力涡轮机和传统的同步发电机由输电系统运营商以虚拟发电厂的形式运行,作为空闲总线来覆盖网络损耗。仿真结果验证了该方法的有效性。
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