This paper conveys the unified control pattern of frequency and voltage of interconnected multi‐area power system through the automatic load frequency control (ALFC) loop and automatic voltage regulator (AVR) loop. Each area includes a single‐stage reheat thermal plant, combined cycle gas turbine (CCGT) plant, and electric vehicles (EVs). Pertinent generation rate constraint for thermal and CCGT plant and governor dead band for the thermal plant is considered. A maiden attempt has been made to introduce the two degree of freedom tilt‐integral‐derivative (2DOFTID) controller for both the ALFC and AVR loops. In this study, a meta‐heuristic algorithm called Harris Hawks optimization (HHO) is implemented to optimize the controller parameters. Study divulges that performance of the 2DOFTID controller predominates when compared with TID and proportional‐integral‐derivative with filter (PIDF) controller apropos time‐domain indices. By juxtaposition, the superiority of the proposed algorithm and performance index is observed. Also, improved system dynamics were independently exhibited by the influence of the lumped EV model and AVR. For the predominance of the 2DOFTID controller, different patterns of disturbances such as random and sinusoidal varying load perturbation have been investigated. Eventually, the sensitivity studies were accomplished to determine the sturdiness of the proposed controller for substantial variations in the system parameters.

-In this paper, a new approach of optimum design for a Hybrid PV/Wind energy system is presented in order to assist the designers to take into consideration both the economic and ecological aspects. When the stand alone energy system having photovoltaic panels only or wind turbine only are compared with the hybrid PV/wind energy systems, the hybrid systems are more economical and reliable according to climate changes. This paper presents an optimization technique to design the hybrid PV/wind system. The hybrid system consists of photovoltaic panels, wind turbines and storage batteries. Genetic Algorithm (GA) optimization technique is utilized to minimize the formulated objective function, i.e. total cost which includes initial costs, yearly replacement cost, yearly operating costs and maintenance costs and salvage value of the proposed hybrid system. A computer program is designed, using MATLAB code to formulate the optimization problem by computing the coefficients of the objective function. The method mentioned in this article is proved to be effective using an example of hybrid energy system. Finally, the optimal solution is received using Genetic Algorithm (GA) optimization method.

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Modern power systems are very complicated and have more obligation to uphold the supply of power be reliable, stable, and of decent quality at both the transmission and distribution phases. Preserving grid balance is a significant concern if there is an unforeseen generation deficit or grid disturbance, or intermittent renewable energy sources, such as bio‐diesel, electric vehicles (EVs), and solar power are incorporated into the energy mix. To compensate for this imbalance and enhance the power system's reliability and stability, the energy storage systems (ESS) can be regarded as an appropriate measure. Thus, ESS contributes to greenhouse gas (GHG) emission reductions by successfully integrating more renewable energy sources into the grid. This article presents multiple ESSs, such as pumped hydroelectric storage (PHS), accurate flywheel energy storage (AFES), battery energy storage (BES), capacitive energy storage (CE), and superconducting magnetic energy storage (SMEs) and their comparative performance analysis in unified voltage and frequency control of power system. The proposed interconnected power system includes thermal, solar‐thermal, bio‐diesel‐engine generator, and EVs. In both control systems, a maiden attempt was made to utilize Harris' Hawks optimization‐based fuzzy‐fractional‐order‐tilt‐integral‐derivative (FFOTID) controller. The repercussion of PHS proclaims a substantial amelioration in system performance than other ESSs. Likewise, the system exhibits better dynamics with the coalition of PHS and power system stabilizer (PSS) of AVR compared to their separate intervention. Lastly, sensitivity analysis of proposed controller is analyzed by alteration of load perturbation and nonlinearity of thermal plants, which ensures optimal controller parameters accomplished at nominal conditions are resilient enough.

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