Frequency Management in Power Systems with Uncertain Loads and Generation: A Model Predictive Control Approach

Abstract

The primary purpose of Load Frequency Control (LFC) is to minimize the frequency and tie-line power deviations in a power system, by optimally rescheduling the generation settings. However, the increasing penetration of Renewable Energy Sources (RESs) in a power system makes the conventional LFC more challenging, since the power output from RESs is unpredictable or stochastic. In this paper, a novel MPC based Stochastic Load Frequency Control (SLFC) technique is proposed, that enables high amounts of RESs to be integrated while maintaining reliable and stable operation. A structure-preserving linear statespace model for power systems is derived which more precisely represents a practical power system behavior. The proposed controller calculates optimal generation settings by minimizing an optimization problem subject to a set of constraints. To model the stochastic nature of RES power outputs, frequency deviation is added as a chance constraint in the optimization problem, transforming it to a chance constrained optimization problem. This ensures that the probability of frequency deviation at the end of prediction horizon, lying outside a specific range, is always less than some predefined confidence level. The proposed MPC based stochastic control technique is then tested on IEEE 39-bus standard test system under different operating conditions and for 200 different scenarios.