Rank Exponent Method Based Optimal Control of AGC for Two-Area Interconnected Power Systems

Abstract

Automatic generation control (AGC) is employed in power systems to maintain balance between generation and load by adjusting output of generators in real time. Controller continuously monitors system frequency and tie-line power flow by responding to fluctuations in electricity demand and supply and optimizes generator dispatch, reduces power imbalances, and enhances grid stability. This work proposes and solves the issues of the AGC in two-area interconnected power systems by proposing a new approach based on both Jaya algorithm and the rank exponent method. In particular, we design a proportional-integralderivative controller with derivative filtering (PIDm), where the effect of the noise is mitigated by the use of a filter with derivative gain. We propose to build the objective function, to tune the controller's parameters, as the linear combination of three sub-objectives, namely integral of time multiplied absolute error (ITAE) for frequency deviations, tie-line power deviation, and area-control errors (ACEs). The rank method is exploited to evaluate the weights of these sub-objectives, while the final overall objective function is minimized exploiting the Jaya algorithm. The proposed controller's performance is assessed in six different scenarios with load disturbances, and its effectiveness is compared to state-of-art controllers tuned using salp swarm algorithm (SSA), Nelder-Mead simplex (NMS), symbiotic organisms search (SOS), elephant herding optimization (EHO), and Luus-Jaakola (LJ) optimization algorithms. To illustrate the frequency and tie-line power changes, results are also shown, and a statistical study is finally carried out to evaluate the recommended controller's overall effectiveness. Additionally, Friedman rank test as no-parametric statistical analysis is also done in order to evaluate the significance level of optimization algorithms. Our numerical findings evidence that the proposed PIDm controller outperforms other existing optimizationbased controllers in terms of performance and utility, thus proving to be very effective for handling AGC issues in two-are interconnected power systems.INDEX TERMS Rank exponent method, AGC, Jaya optimization, Interconnected power system. I. INTRODUCTIONI N power system, load demand is constantly varying.To meet out the increasing demand for power, singlearea power systems are less reliable. Reliability is the main concern in operation of a power system. To ensure the reliability of power system, distinct areas' generators are interconnected via tie-lines. This type of interconnection is known as interconnected power system (IPS) [1]. In IPS, it is essential to operate all generators at the same frequency in a synchronized manner. The frequency of IPS will deviate VOLUME X, XXXX

Fuzzy analytic hierarchy process based generation management for interconnected power system

“…MADM techniques like rank sum weight, AHP and rank exponent are implemented for AGC problem of 2-APS in the literature 16 – 19 . AGC ensures maintaining the overall power balance of the system that is dependent on critical factors such as frequency deviation, area control errors, and tie-line power deviation 20 , 21 .…”