Despite the affordability and popularity of doubly fed induction generator (DFIG) among the variable-speed wind turbines, it cannot follow the inertia response caused by the load perturbations and the imposed frequency fluctuations in the power system. Considering the growing participation of wind power generation, DFIG with no virtual inertia control cannot play a functional role in the frequency stability of traditional power systems. At the outset, a new inertia control strategy is proposed for DFIG to participate in system frequency control via absorption or disposal of kinetic energy based on active power control. Then after that, interline power flow controller (IPFC) known as an adaptable and complex compensator is introduced to simultaneously regulate and control the power flow of multiple lines during the large penetration of DFIGs. To enhance the damping capability of IPFC, this paper has suggested a novel optimal adaptive neuro-fuzzy (OANF). The frequency and tie-line power deviations as two prominent stability benchmarks have been considered and analysed to appraise the damping capability of the suggested controller in the affected interconnected power system. The dynamic stability problem has been formulated based on multi-objective grey wolf optimizer to optimally tune OANF-based IPFC towards simultaneous suppression of the abovementioned benchmarks. The accurate fuzzy membership functions and rules of OANF-based IPFC have been extracted during the severe perturbation in two interconnected reconstructed power systems. Eventually, the simulation results extracted from both the three-area and five-area interconnected power systems have primarily validated the inertia control-based DFIG and subsidiarily OANF–IPFC to effectively suppress the low-frequency oscillations.

An innovative OANF–IPFC based on MOGWO to enhance participation of DFIG-based wind turbine in interconnected reconstructed power system

With the improvement of the permeability of wind and photovoltaic (PV) energy, it has become one of the key problems to maintain the small-signal stability of the power system Therefore, this paper analyzes the small-signal stability in a power system integrated with wind and solar energy First, a mathematical model for small-signal stability analysis of power systems including the wind farm and PV station is established And the characteristic roots of the New England power system integrated with wind energy and PV energy are obtained to study their small-signal stability In addition, the validity of the theory is verified by the voltage drop of different nodes, which proves that power system integrated with wind-solar renewable energy participating in the frequency regulation can restore the system to the rated frequency in the shortest time and, at the same time, can enhance the robustness of each unit

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Small-Signal Stability Analysis for Power System Frequency Regulation with Renewable Energy Participation

With the increasing penetration rate of Power Electronic Converter (PEC) based technologies, the electrical power systems are facing the problem of transient stability since the PEC based technologies do not contribute to the system inertia, and the proportion of synchronous generators (i.e., the source of inertia) is in decreasing rate. In addition, PEC based technologies’ components have poor inherent damping. It is very important to analyze the system characteristics of a power system to minimize the potential instabilities during the contingencies. This paper presents the parametric sensitivity analysis of the rotor angle stability indicators for the 39-bus New England power system. The indicators of rotor angle stability analysis such as critical fault clearing time (CCT), Eigenvalue points, damping ratio, frequency deviation, voltage deviation, and generator’s speed deviation are identified and analyzed for three case scenarios; each scenario has six sub-cases with different inertia constants. The results show that the CCTs for each component will be reduced if the inertia reduces at any section of a multi-machine power system. Although the applied three scenarios with six sub-cases are identified to be stable in this analysis, the decreasing inertia constant has significant impact on the power system dynamics.

Parametric Sensitivity Analysis of Rotor Angle Stability Indicators

Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed.

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Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

Sustainable renewable energies are now increasing abruptly and received considerable attention worldwide. Sun and wind power are the two most common form of renewable energy resources. Solar irradiance and wind speed are fluctuating unconditionally, which creates a major challenge in grid integration. In this paper, grid integrated battery energy storage station-based hybrid photovoltaic and wind power generating hybrid power plant has been designed to examine the behavior of the system stability and the impacts on the system for different fault conditions. It contains PV, BESS, WT, DFIG, MPPT, PID, converters and controllers. Maximum peak power technique incremental conductance algorithm is used to extract the maximum power output from photovoltaic cells. BESS is used to produced constant output power from PV array at fluctuating irradiance. PID controller is used to wield duty cycles for battery charge and discharge controller. Wind turbine with doubly-fed induction generator (DFIG) is used. The simulation studies are carried out with MATLAB/Simulink. This paper shows a smooth and stable execution of BESS based hybrid PV-WT power system under different operating conditions and obtained nearly constant output power. PV and WT affected the transient stability of the system for a very short period.

Stability Analysis of Grid Integrated BESS Based Hybrid Photovoltaic (PV) and Wind Power Generation

Small Signal Stability Analysis of Grid Connected Renewable Energy Resources with the Effect of Uncertain Wind Power Penetration

The mapping of damping ratios and damping factors by Sine-Cosine Algorithm (SCA) is significant in the analysis of low frequency oscillations generated in an integrated network having multiple conventional and renewable energy sources. Multiple random models with unknown search spaces and uncertain conditions and constraints, which incorporate the fluctuation of solutions towards or outwards at the initial stage for solving real-time problems can be analyzed by a revamped sine-cosine algorithm (RSCA) model. In this paper, the SCA has been revamped to explore the stability threshold for a stable system under dynamic nonlinear operating conditions. It is achieved with the infusion of suitable mathematical functions for optimizing the parameters of Power System Stabilizers (PSSs) and Doubly Fed Induction Generator (DFIG) system-based oscillation dampers to enhance the Small Signal Stability of power systems through effective damping of low-frequency oscillations (LFOs). These LFOs weaken the effective power generation and demand management cycle in conventional power systems when the system faces conditions like intermittent renewable energy sources, overloading conditions, impulsive faults etc. The small-signal and transient stability studies for various disturbances and different operating conditions are investigated, and the performance of the proposed RSCA for optimized parameter tuning of system stabilizers and oscillation dampers are analyzed on the modified benchmarking systems with wind generators using MATLAB Ⓡ simulations. The efficiency and robustness of the proposed algorithm has been verified under selective critical operating conditions, line outages, and load uncertainties to prove that the low frequency modes are damped with an elevated positive damping ratio and rapid settling time with reduced oscillations. The application of system stabilizers and oscillation dampers optimized through the proposed RSCA shows a reduced settling time in the LFOs created and improved damping ratio of 0.22 for an increase in 20% loading and 50% of wind power generation in the case study of Two Area Four Machine System.

Revamped Sine Cosine Algorithm Centered Optimization of System Stabilizers and Oscillation Dampers for Wind Penetrated Power System

The coordinated and efficient operation of Solar PV system combined with battery storage systems makes a standalone DC Community Grid stable and reliable. The accurate power sharing between the distributed renewable energy sources of a DC community grid according to the available source and load demand is managed through droop control algorithm and droop resistance adaptable to the variations in the sources (Uncertainties in Solar Power). This paper presents an adaptive droop control algorithm developed based on the existing source converted as the reference current for operating the converters to meet the demand. The changes in the output potential of each converter is controlled and is maintained constant throughout the operation of DC community grid and makes it stable. The proposed control algorithm is implemented to the system individually to make it a communication less control. The adaptive droop control algorithm relies on the local measurement data from each converter like, output voltage, current, rated load current and DC Bus voltage. The control strategy is applied to a simple DC microgrid representing a local community grid with solar PV as the source and battery as the support system on standalone mode of operation developed using MATLAB-Simulink® and is validated for three different power sharing scenarios.

S. Grace Sadhana

Papers

Small Signal Stability Analysis of Grid Connected Renewable Energy Resources with the Effect of Uncertain Wind Power Penetration

Revamped Sine Cosine Algorithm Centered Optimization of System Stabilizers and Oscillation Dampers for Wind Penetrated Power System

Energy Management Strategy for a Standalone Solar PV based DC Community Grid