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In the paper, the maiden application of Tilted Integral Fractional Derivative with Filter plus Fractional Derivative controller (TIDμ1NDμ2$TI{D^{{\mu _1}}}N{D^{{\mu _2}}}$), called TIFDNFD controller, is proposed to achieve load frequency control (LFC) of two area‐multi source power system. In the study, both areas include thermal power, hydropower, and gas turbine power systems. In this study, generation rate constraint and governor dead‐band are integrated into the power system to evaluate the performance of the controller in a non‐linear environment. The wild horse optimizer (WHO) is used for controller parameter tuning in the LFC problem for the first time. The performance of the proposed controller is demonstrated by comparing it with the recently published studies including different controllers. In this study, to obtain more realistic results, solar photovoltaic (PV) power, wind power, and load demand with stochastic form have been added to the power system. In addition, the dynamic effect of the hydrogen storage system, consisting of an electrolyser and a fuel cell, is considered a grid supporter. The superiority of the WHO algorithm in optimization has been verified by comparing it with three optimization algorithms recently proposed. Finally, the resilience and robustness of the power system are evaluated in perturbed system parameters. [ABSTRACT FROM AUTHOR]

Sustainability is important in voltage regulation control in grids and must be done successfully. In this paper, a novel tilt-fractional order integral-derivative with a second order derivative and low-pass filters controller, referred to as TIλDND2N2 controller, is proposed to enhance the control performance of an automatic voltage regulator (AVR). In this article, the equilibrium optimizer (EO) algorithm is used to optimally determine the eight parameters of the proposed controller. In this study, a function consisting of time domain specifications is used as the objective function. To evaluate the performance of the proposed controller, it is compared with the proportional-integral-derivative (PID), fractional order PID (FOPID), PID accelerator (PIDA), PID plus second order derivative (PIDD2), and hybrid controllers used in previous studies. Then, Bode analysis is performed to determine the achievement of the proposed controller in the frequency domain. Finally, the robustness test is realized to assess the response of the proposed controller against the deterioration of the system parameters. As a result, the proposed controller demonstrates outstanding control performance compared to studies in terms of settling time, rise time and overshoot. The proposed controller shows superior performance not only in frequency domain analysis but also in perturbed system parameters. [ABSTRACT FROM AUTHOR]

In this study, a novel hybrid Simulated Annealing-Genetic Algorithm (hSA-GA) is proposed. In the hSA-GA, population-based SA is used and each solution in the population is improved using the local search operator. The information exchange between the improved solutions is provided by the crossover operator. A new selection operator is used to ensure the balance between intensification and diversification. The hSA-GA is tested first on nine benchmark functions. Then it is used for tuning proportional–integral–derivative (PID) parameters for automatic generation control (AGC) of multi-area interconnected power systems. Firstly, PID parameters are determined with hSA-GA on a two-area interconnected non-reheating thermal system (System-1) in two different generator time constants. Secondly, to demonstrate the effect of supplementary control in AGC systems, the system is simulated with hSA-GA tuned PID controller and without controller. Additionally, the performance of the proposed hSA-GA is observed on AGC system of two area thermal power system with governor dead-band (GDB) nonlinearity (System-2). Transient responses of Δ f 1 , Δ f 2 and Δ P t i e obtained for both System-1 and System-2 are compared with studies on the same systems in the literature and it is seen that hSA-GA exhibits better control performance on power systems than compared studies. The proposed algorithm shows the best performance in System-1 (when T g = 0. 08). Accordingly, settling times of Δ f 1 , Δ f 2 and Δ P t i e are reduced to 2.33 s, 3.783 s and 3.11 s, respectively. Finally, the non-linear two area thermal power system is tested with a load varying between ± 50% for 180 s to validation of proposed algorithm and results are compared relevant studies. • The simulated annealing was hybridized with the genetic algorithm and the hybrid SA-GA (hSA-GA) algorithm was proposed. • The performance of the novel hSA-GA algorithm was observed in the AGC of linear and non-linear interconnected power systems. • The objective function consists of four integral-based performance criteria and the settling time of the signals. • The simulation results outperformed recently reported studies on the same systems in literature. [ABSTRACT FROM AUTHOR]