One of the main challenges of the microgrid (MG) operation in autonomous mode is the uncertain output due to the fluctuating nature of renewable energy resources (RES). This study investigates the effects of RES uncertainties to the oscillatory stability of a hybrid MG in islanded operation. A comprehensive model of Wind Energy Conversion System (WECS), a two-stage Photovoltaic (PV) and bio-diesel engine (BDE) based distributed generation (DG) units are considered to capture a complete dynamic response of the hybrid MG. Trajectories and distribution of damping ratios and oscillatory frequencies of the critical modes were thoroughly investigated through Monte Carlo simulation considering wind speed and solar irradiance uncertainties. From the probabilistic study, it was observed that the presence of RES variations results in a dynamic change of power-sharing strategies and introduce an adverse effect on small signal stability. Uncertain condition of wind speed brings more deterioration in system damping than solar irradiation variation. From time domain simulation, it was confirmed that at higher wind speed, damping on the critical modes reduced. As a consequence, the hybrid MG experienced more oscillatory conditions and even lead to unstable situation at high wind speed conditions. While with solar irradiance change, the investigated MG system can maintain its stable operation.
This paper develops a comprehensive small-signal model of hybrid renewable-energy-based microgrid (MG) in an attempt to perceive oscillatory stability performance and capture the potential interaction between low-frequency critical modes within the MG. Trajectories of sensitive modes due to controller gain variations were evaluated in order to determine the stability boundaries. It was noticeable that various power-sharing schemes significantly influenced the small-signal stability of MG. Moreover, modal interaction emerged due to the proximity of RES-based DG units and non-linear dynamic behaviour of the sensitive modes. The interaction may result in a more oscillatory situation which potentially leads to instability of MG. The low-frequency critical modes obtained from eigenvalues analysis were then verified with the help of nonlinear time domain simulations. The presented work contributes to enhance the design and tuning of controller gain and proposes appropriate power-sharing scheme within MG.
Modern power systems consist of power electronics devices, which are used in renewable energy (RE) conversion. However, these devices, associated controllers, and uncertainty in RE output could bring new challenges to power system stability, especially oscillatory stability. Hence, the integration of battery energy storage systems (BESSs) is being developed to minimise the uncertainty and variability in renewables. Furthermore, to tackle the complex dynamics and inertia‐less characteristics of wind and PV plants additional controllers such as power oscillation damping (POD) control and virtual inertia scheme are sought. However, the primary challenges associated with the wide‐area oscillation damping controller are signal transmission delay, loss of communication signal, data drops, and others. This paper proposes a bat algorithm (BA) based resilient wide‐area multi‐mode controller (MMC) for enhancing oscillatory stability margin with high penetration of renewable power generations (RPGs) and BESSs. The Java 500 kV Indonesian grid is used to evaluate the performance of the resilient wide‐area MMC. From the results, it is found that the proposed controller effectively damp the critical mode of oscillation in the system even under communication failure as well as certain damping controller failures.
Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.
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