Wind farms providing secondary frequency regulation: evaluating the performance of model-based receding horizon control

Abstract

Abstract. This paper is an extended version of our paper presented at the 2016 TORQUE conference . We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large-eddy simulation (LES) model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, "RegA" and "RegD", which are used by PJM, an independent system operator in the eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation services or markets. Our results demonstrate that the dynamic-model-controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower timescales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further work is needed to enable this controlled wind farm to achieve qualifying performance for all regulation signals.

A Simulation Model for Providing Analysis of Wind Farms Frequency and Voltage Regulation Services in an Electrical Power System

“…Various simulation models are used in the studies, the features of which depend on the specific application. The models dedicated to closed loop on-line control to optimize the power production of wind turbines [24][25][26][27][28][29] belong to the class of control-oriented dynamic models and differ in terms of the degree of fidelity. Other models are used for the WFs layout optimization.…”

Regulating Reserve Dynamic Scheduling and Optimal Allocation in Systems with a Large Share of Wind-Power Generation

“…Active participation of WPPs in ancillary services is encountered frequently in the literature. For example, in References [1][2][3] WPPs with a doubly-fed induction generator were applied for primary frequency and power-reserve regulation, and for secondary regulation in Reference [4], whereas Reference [5] discusses inertial support from WPPs. However, in many countries, the owners of WPPs have no interest in participating due to their generating contracts.…”

Fast Control-Oriented Dynamic Linear Model of Wind Farm Flow and Operation

“…With regard to the power control of wind farms, model-free [7,8] and model-based approaches [9][10][11] have been investigated in literature. Model-based approaches typically employ dynamic models, since they result in a superior performance compared to static models [23]. The use of model-based approaches for the power control of wind farms can provide several advantages over model-free approaches.…”

“…A variety of dynamic, wind farm-scale flow models have been investigated in literature. These models are based on either engineering wake models [23][24][25] or two-dimensional computational fluid dynamics (CFD) [19,26]. The latter models estimate hub height wind farm flow using customized, two-dimensional Navier-Stokes equations.…”

“…The use of a CFD model is, however, typically more computationally expensive than the use of engineering models of wind farm flow. Engineering models have been investigated for model predictive control of wind farms, with good results that can perform wind farm-scale optimization in the order of minutes [23,27]. In the quest to further reduce the duration of the optimization, a natural step is to move towards linear control approaches, such as linear model predictive control.…”