skip to main content


This content will become publicly available on December 13, 2024

Title: Leveraging Predictions in Power System Frequency Control: An Adaptive Approach
Ensuring the frequency stability of electric grids with increasing renewable resources is a key problem in power system operations. In recent years, a number of advanced controllers have been designed to optimize frequency control. These controllers, however, almost always assume that the net load in the system remains constant over a sufficiently long time. Given the intermittent and uncertain nature of renewable resources, it is becoming important to explicitly consider net load that is time-varying. This paper proposes an adaptive approach to frequency control in power systems with significant time-varying net load. We leverage the advances in short-term load forecasting, where the net load in the system can be accurately predicted using weather and other features. We integrate these predictions into the design of adaptive controllers, which can be seamlessly combined with most existing controllers including conventional droop control and emerging neural network-based controllers. We prove that the overall control architecture achieves frequency restoration decentralizedly. Case studies verify that the proposed method improves both transient and frequency-restoration performances compared to existing approaches.  more » « less
Award ID(s):
2200692 2153937
NSF-PAR ID:
10493718
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IEEE
Date Published:
Journal Name:
2023 62nd IEEE Conference on Decision and Control (CDC)
ISSN:
2576-2370
ISBN:
979-8-3503-0124-3
Page Range / eLocation ID:
570 to 576
Format(s):
Medium: X
Location:
Singapore, Singapore
Sponsoring Org:
National Science Foundation
More Like this
  1. Inertia from rotating masses of generators in power systems influence the instantaneous frequency change when an imbalance between electrical and mechanical power occurs. Renewable energy sources (RES), such as solar and wind power, are connected to the grid via electronic converters. RES connected through converters affect the system's inertia by decreasing it and making it time-varying. This new setting challenges the ability of current control schemes to maintain frequency stability. Proposing adequate controllers for this new paradigm is key for the performance and stability of future power grids. The contribution of this paper is a framework to learn sparse time-invariant frequency controllers in a power system network with a time-varying evolution of rotational inertia. We model power dynamics using a Switched-Affine hybrid system to consider different modes corresponding to different inertia coefficients. We design a controller that uses as features, i.e. input, the systems states. In other words, we design a control proportional to the angles and frequencies. We include virtual inertia in the controllers to ensure stability. One of our findings is that it is possible to restrict communication between the nodes by reducing the number of features in the controller (from 22 to 10 in our case study) without disrupting performance and stability. Furthermore, once communication between nodes has reached a threshold, increasing it beyond this threshold does not improve performance or stability. We find a correlation between optimal feature selection in sparse controllers and the topology of the network. 
    more » « less
  2. With the increasing penetration of non-synchronous variable renewable energy sources (RES) in power grids, the system's inertia decreases and varies over time, affecting the capability of current control schemes to handle frequency regulation. Providing virtual inertia to power systems has become an interesting topic of research, since it may provide a reasonable solution to address this new issue. However, power dynamics are usually modeled as time-invariant, without including the effect of varying inertia due to the presence of RES. This paper presents a framework to design a fixed learned controller based on datasets of optimal time-varying LQR controllers. In our scheme, we model power dynamics as a hybrid system with discrete modes representing different rotational inertia regimes of the grid. We test the performance of our controller in a twelve-bus system using different fixed inertia modes. We also study our learned controller as the inertia changes over time. By adding virtual inertia we can guarantee stability of high-renewable (low-inertia) modes. The novelty of our work is to propose a design framework for a stable controller with fixed gains for time-varying power dynamics. This is relevant because it would be simpler to implement a proportional controller with fixed gains compared to a time-varying control. 
    more » « less
  3. The AC frequency in electrical power systems is conventionally regulated by synchronous machines. The gradual replacement of these machines by asynchronous renewable-based generation, which provides] little or no frequency control, increases system uncertainty and risk of instability. This poses hard limits on the proportion of renewables that can be integrated into the system. To address this issue, in this paper, we develop a framework for performing frequency control in power systems with arbitrary mixes of conventional and renewable generation. Our approach is based on a robust stability criterion that can be used to guarantee the stability of a full power system model based on a set of decentralised tests, one for each component in the system. It can be applied even when using detailed heterogeneous component models and can be verified using several standard frequency response, state-space, and circuit theoretic analysis tools. By designing decentralised controllers for individual components to meet these decentralised tests, strong apriori robust stability guarantees, that hold independently of the operating point and remain valid even as components are added to and removed from the grid, can be given. This allows every component to contribute to the regulation of system frequency in a simple and provable manner. Notably, our framework certifies the stability of several existing (non-passive) power system control schemes and models, and allows for the study of robustness with respect to delays. 
    more » « less
  4. Frequency restoration in power systems is conventionally performed by broadcasting a centralized signal to local controllers. As a result of the energy transition, technological advances, and the scientific interest in distributed control and optimization methods, a plethora of distributed frequency control strategies have been proposed recently that rely on communication amongst local controllers. In this paper, we propose a fully decentralized leaky integral controller for frequency restoration that is derived from a classic lag element. We study steady-state, asymptotic optimality, nominal stability, input-to-state stability, noise rejection, transient performance, and robustness properties of this controller in closed loop with a nonlinear and multivariable power system model. We demonstrate that the leaky integral controller can strike an acceptable trade-off between performance and robustness as well as between asymptotic disturbance rejection and transient convergence rate by tuning its DC gain and time constant. We compare our findings to conventional decentralized integral control and distributed- averaging-based integral control in theory and simulations. 
    more » « less
  5. null (Ed.)
    With more and more renewable energy resources integrated into the power grid, the system is losing inertia because power electronics-based generators do not provide natural inertia. The low inertia will cause the microgrid to be more sensitive to disturbance and thus a small load change may result in a severe deviation in frequency. Based on the basic VSG algorithm, which is to mimic the characteristic of the traditional synchronous generator, the frequency can be controlled to a stable value faster and more smoothly when there is a fluctuation in the PV power generation and/or load change. However, characteristic of the VSG depends on the system structure in consideration of multiple generations, such as Synchronous Generator (SG), PV and Battery Energy Storage System (BESS), which greatly increases the complexity of applying VSG in practical power system. Furthermore, with BESS-VSG, Maximum Power Point (MPP) operation of PV is guaranteed. In addition, an adaptive VSG method is developed for a microgrid system, and the corresponding simulation in Matlab/Simulink shows the effectiveness of the adaptive VSG method. 
    more » « less