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Solar energy seems to be most sustainable way which can conserve the environment from negative impacts caused by electrical power generation from fossil fuels. For achieving the utmost power in output, photovoltaic (PV) array should operate on its optimal power point. When PV arrays are subjected to a partial shading state, several local peaks are experienced by power-voltage performance curve of PV system which significantly trims down the efficiency of complete system. So it becomes vital to locate the global peak of PV system for harvesting the upper limit power for better performance. This paper presents an improved grey wolf optimization (IGWO) technique which employs the concepts of parallel grey wolf optimization and opposition-based learning to trace the GMPP under partial shading situation and also figure out the performance for gradually varying with irradiance and temperature for PV system. This IGWO-based MPPT scheme has been implemented in MATLAB simulation environment. The outcome of the simulation is verified by the past-proposed MPPT techniques namely perturb and observe (P&O) and particle swarm optimization (PSO). It has been found from the simulation results that the performance of the suggested IGWO based MPPT design is advanced than the P&O and PSO techniques in terms of tracking speed, steady-state oscillation under partial shading conditions (PSCs) and accuracy. [ABSTRACT FROM AUTHOR]

In modern power system, plugged in electric vehicle plays a very vital role in regulation of system frequency as it is a form of battery energy storage system. This paper presents an aggregate model consisting of a three area system embedded with electric vehicle (EV) in all the three control areas along with Dish-Stirling solar thermal system (DSTS) in only Area-1. The thermal systems are provided with single reheat turbine, governor dead band and generation rate constraint of 3% per minute to give a more realistic view to the designed system. Two degree of freedom Proportional-Integral-Derivative (2DOF-PID) controller with filter is applied as secondary controller in all the three control areas. Maiden application of a new nature inspired optimization technique called Wind Driven Optimization technique in load frequency control is made in this paper. A comparison is done between 2DOF-PID and Proportional-Integral-Derivative (PID) controller to verify the effectiveness of the former. Analysis reveals the advantage of including DSTS in the aggregate model which proves the role of renewable energy sources in overcoming the fluctuations in frequency and tie-line power in a power system under both nominal 1% step load perturbation and random load perturbation. An attempt has also been made to show the impact of incorporating EVs under nominal system condition into the system, and it has been observed that the number and magnitude of oscillations are decreased to great extent with its incorporation. [ABSTRACT FROM AUTHOR]