Optimal load frequency control through combined state and control gain estimation for noisy measurements

Anju G Pillai,Elizabeth Rita Samuel,A Unnikrishnan

doi:10.1186/s41601-020-00169-5

Abstract

Combined estimation of state and feed-back gain for optimal load frequency control is proposed. Load frequency control (LFC) addresses the problem of controlling system frequency in response to disturbance, and is one of main research areas in power system operation. A well acknowledged solution to this problem is feedback stabilization, where the Linear Quadratic Regulator (LQR) based controller computes the feedback gain K from the known system parameters and implements the control, assuming the availability of all the state variables. However, this approach restricts control to cases where the state variables are readily available and the system parameters are steady. Alternatively, by estimating the states continuously from available measurements of some of the states, it can accommodate dynamic changes in the system parameters. The paper proposes the technique of augmenting the state variables with controller gains. This introduces a non-linearity to the augmented system and thereby the estimation is performed using an Extended Kalman Filter. This results in producing controller gains that are capable of controlling the system in response to changes in load demand, system parameter variation and measurement noise.

Highlights

To control a power system against frequency variation in response to changes in demand, load frequency control (LFC) is a well acknowledged strategy
Following the linearized single-area power system outð18Þ lined in [6], the proposed algorithm is simulated in MATLAB R2018a, where the single-area power system ð19Þ has the following components: where Xa = [X, K]T and G is the disturbance vector of dimension 2n
8 Conclusion This paper has demonstrated a new observer-based approach for implementing the LFC in power systems

Summary

Introduction

To control a power system against frequency variation in response to changes in demand, load frequency control (LFC) is a well acknowledged strategy. The Kalman Filter estimates the unmeasurable states and incorporates the optimal gain of LQR for the control of frequency. To avoid the difficulties in computing Q and R matrices for LQR controller, an estimation technique is proposed in [9] which augments the required feedback gain K, along with the system state estimation through Extended Kalman Filter method. The paper proposes a novel technique of augmenting the states with optimal gains for estimation It incorporates parameter uncertainties in the system. The present paper proposes to use the Kalman Estimator for estimating states from the available measurement of frequency change. It estimates the gain vector K by augmenting the state vector with the K vector given by.

Kalman estimator

Results and discussion

Conclusion

Δ f ðsÞ þ 1