• Energy Research

To stabilize frequency in a power system, this research study suggests a novel modified Gorilla Troops Optimizer (mGTO) technique, which builds on the original technique, and offers notable gains in effectiveness and efficiency when solving real-world optimization problems. A thorough comparative analysis reveals that the mGTO algorithm is the best option, outperforming its counterparts in terms of stability and overall performance. Interestingly, mGTO performs better than any of its competitors in terms of stability, making it the best option. The mGTO algorithm significantly reduces implementation time and enhances solution quality compared to the conventional GTO algorithm. A new linearized Phillips–Heffron model with an IPFC was developed to investigate power systems’ stability. To effectively dampen low-frequency oscillations, an auxiliary controller for modeling the IPFC is proposed. It provides four options for damping controllers, and the recommended mGTO algorithm is used to adjust the controller parameters. This method is superior to traditional controllers in stability control and has undergone extensive validation. It is a crucial instrument for controlling the frequency of an SMIB power system based on IPFC. Based on the simulation results, the updated strategy that has been suggested is the most effective way to define the mentioned damping controller by considering the percentage improvement in the goal function value.

This study proposes a novel modified grey-wolf optimization algorithm (MGWOA) to enhance power system stability. The power system stabilizer and static synchronous series compensator (SSSC) are used as damping controllers. Additionally, fractional-order PID (FOPID) controller is used to handle the system nonlinearities and thus achieve better performance. The control parameters are tuned using the proposed MGWOA method which has been verified on unimodal and multimodal functions. Single-machine infinite bus (SMIB) and multimachine power system (MMPS) are taken as case studies to analyze the efficacy of the proposed controller. Minimization of rotor speed deviation is considered an objective function. The results obtained from the MGWOA-tuned FOPID-based damping controllers are compared with those obtained using recently developed efficient and competitive heuristic algorithms. It was observed that the MGWOA method is well-suited for damping low-frequency oscillations. Furthermore, statistical analysis is performed on the obtained results to justify the superiority of the MGWOA method. The simulation results suggest that the MGWOA exhibits superior performance characteristics when applied to a real power system.

A grid-connected battery energy storage system (BESS) is a crucial component in modern electrical grids that enables efficient management of electricity supply and demand. BESS consists of a set of batteries connected to the power grid, allowing for the storage and release of electricity when needed. This paper addresses the challenges associated with intermittent renewable energy sources and enhancing grid stability and reliability. The primary objective of this work is to store surplus electricity during low demand and supply it to the grid during peak demand periods or when renewable energy generation is low. By storing surplus energy, BESS helps balance supply and demand fluctuations, reducing the need for expensive fossil fuel-based power plants and minimizing greenhouse gas emissions. Additionally, BESS provides frequency regulation, voltage support, and grid stabilization. Furthermore, BESS reduces the intermittency of renewable energy sources like solar and wind, allowing for its integration into the grid. It allows the captured energy to be stored and utilized when the renewable sources are not actively generating electricity. Grid-connected BESS are a vital component in the transition towards a more sustainable and resilient energy future. They facilitate the effective utilization of renewable energy, enhance grid flexibility, and contribute to the reduction of carbon emissions, ultimately promoting a cleaner and more reliable electricity supply. The simulation of grid connected solar system with BESS is carried out using MATLAB/Simulink environment.

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.