Small Signal Stability Enhancement Research Articles

Power system stabilizers tuning for probabilistic small-signal stability enhancement using particle swarm optimization and unscented transformation

Power system stabilizers tuning for probabilistic small-signal stability enhancement using particle swarm optimization and unscented transformation

Small-Signal Stability Enhancement With Circulating Reactive Power in Parallel Modular Multilevel Converters

Small-Signal Stability Enhancement With Circulating Reactive Power in Parallel Modular Multilevel Converters

Small-signal stability enhancement of islanded microgrids via domain-enriched optimization

A domain-enriched optimization algorithm is developed to enhance the dynamic resilience of islanded microgrids, with a specific emphasis on improving small-signal stability. A novel eigenvalue-oriented objective function and accompanying constraints are designed to optimize the controller parameters for the power-electronic interfaces of distributed energy resources (DERs), which are critically important to the system’s dynamic resilience. To solve the resulting non-smooth and non-convex optimization problem, we introduce an auxiliary loss term based on microgrid domain knowledge, which takes the form of a multivariate polynomial in the optimization variables. We refer to our proposed method as Domain-Enriched Navigation (DEN), which combines the gradient of this domain-enriched loss term as a navigation strategy with an evolutionary algorithm. By incorporating the navigated update, we successfully address initialization sensitivity and slow convergence commonly observed in ordinary evolutionary algorithms. Numerical tests on typical islanded microgrids validate the effectiveness of our approach in enhancing the small-signal stability. Our results demonstrate a notable improvement of over 1 dB in the objective function, along with much faster computation than state-of-the-art alternatives.

Power System Small Signal Stability Enhancement Using Fuzzy Based STATCOM

Power System Small Signal Stability Enhancement Using Fuzzy Based STATCOM

An FRLQG Controller-Based Small-Signal Stability Enhancement of Hybrid Microgrid Using the BCSSO Algorithm

The development of a network termed microgrid (MG) has been motivated owing to augmentation in renewable energy source (RES) infiltration along with the utilization of enhanced power electronic technologies. Recently, more popularity has been gained by the hybrid MG (HMG). Maintaining the power system’s (PS) small-signal stability (SSS) is highly complicated during the energy enhancement of RES. The enhancement of the SSS has been focused on by numerous existing methodologies; however, the optimal solution was not obtained by those methodologies. A new controller with the assistance of bell-curved squirrel search optimization (BCSSO) is proposed to address the aforementioned issue. Initially, for PSs such as photovoltaic (PV), wind turbines, along with fuel cells, a mathematical model is ascertained. Then, in this, the converter design has been developed. The PV’s maximum power flow is recognized by maximum power point tracking (MPPT) in the bidirectional switched buck-boost converter (BSBBC), which is utilized in this research, and by utilizing the fuzzy ruled linear quadratic Gaussian (FRLQG), the converters are controlled to assure safe operation along with soft dynamics. By employing the BCSSO, the parameters are modified in this controller which in turn ameliorates the SSS. The experiential evaluation of the proposed system’s performance is analogized with the existing methodologies. Consequently, the outcomes confirmed that a better performance was attained by the proposed methodology than the prevailing works.

Modified PSO tuned two stage lead lag STATCOM control action for small signal stability enhancement of variable wind integrated power system

In this work Modified PSO (MPSO) is proposed to tune two stage lead lag control action based on STATCOM for enhancing small signal stability of an intermittent wind source penetrated power system. The Modified PSO has been compared with standard PSO and fractional PSO to tune controller parameters of STATCOM based control action. Multi machine system subjected to sudden and intermittent wind variations have been considered in this work. Subject to this wind penetration the lead lag control action with only PSO and two stage lead lag control action with fractional PSO and modified PSO has been implemented to damp the system oscillations pertaining to initial operating condition. It was found that subject to intermittent nature of wind penetration the rotor angle small signal stability is being hampered and subject to this when the modified PSO tuned two stage lead lag STATCOM control action is applied, it damps the oscillations heavily and the results have been compared with only PSO and fractional PSO control algorithms.

Intelligent Coordinated Control of PID-SMES and AVR based on Hybrid PSO-DE for Small Signal Stability Enhancement

Dynamic disturbances in the electric power system occur due to changes in the load that can change important parameter values, this results in loss of synchronization in multi-machine power systems, so a controller in the power system is needed to maintain a stable condition during dynamic disturbances. In this final project, a Proportional Integral Differential (PID)-Superconducting Magnetic Energy Storage (SMES) controller is useful for supplying or absorbing active power when there is a load change so that the frequency can be maintained continuously, and an Automatic Voltage Regulator (AVR) is in charge of regulating the voltage on the system. The PID controller in SMES is useful for setting the output parameters of SMES. Hybrid Differential Evolution - Particle Swarm Optimization (DE-PSO) optimization method is used to optimize the oscillation damping process. The results indicate that the use of PID SMES and AVR optimized using the DE-PSO hybrid algorithm has a better response. In the Suralaya generator unit, the overshoot is -0.0001395 pu, and the settling time is 12.4 seconds by using the optimal controller. Meanwhile, when it is not using the additional controller, the overshoot is -0.0004228 pu, and the settling time is more than 16 seconds.

Nonlinear Power System Stabilizer Design for Small Signal Stability Enhancement

Nonlinear Power System Stabilizer Design for Small Signal Stability Enhancement

A new optimal static synchronous series compensator‐governorcontrol action for small signal stability enhancement of random renewable penetrated hydro‐dominated power system

AbstractSubject to intermittent nature of renewable sources, small signal stability (SSS) is going to be a challenging task for power system operators. Also as per current deregulated market, stress is imposed on optimal usage of present resources like mechanical governors. In this work a new coordinated optimal damping control action of fractional static synchronous series compensator (SSSC) and governor is proposed to the critical condition of power system for SSS enhancement considering sudden and random variation in solar photovoltaic (SPV) and wind sources with different operating condition of hydro generations and change in reference voltage. Both SSSC and governor coordinate to damp system oscillations to improve stability. A new hybrid differential evolution (DE) with whale optimization algorithm (WOA) is proposed to tune the gains of SSSC and governor in proposed controller. A multi objective function incorporating speed and real power deviation has been taken for optimization problem. It has been observed that varying operating condition of hydro generator along with variations in SPV and wind sources instigate low frequency oscillation and proposed control action has better damping efficacy in comparison to only SSSC and governor. Also, the proposed multi‐objective DE‐WOA control law performs better than only DE and WOA algorithm.

Small signal stability enhancement of a large scale power system using a bio-inspired whale optimization algorithm

A whale optimization algorithm (WOA)-based power system stabilizer (PSS) design methodology on modified single machine infinite bus (MSMIB) and multi-machine systems to enhance the small-signal stability (SSS) of the power system is presented. The PSS design methodology is implemented using an eigenvalue (EV)-based objective function. The performance of the WOA is tested with several CEC14 and CEC17 test functions to investigate its potential in optimizing the complex mathematical equations. The New England 10-generator 39-bus system and the MSMIB system operating at various loading conditions are considered as the test systems to examine the proposed method. Extensive simulation results are obtained which validate the effectiveness of the proposed WOA method when compared with other algorithms.

Investigation and damping of electromechanical oscillations for grid integrated micro grid by a novel coordinated governor-fractional power system stabilizer

ABSTRACT Electro mechanical low frequency oscillation generated in a micro-grid (MG) when subjected to uncertain disturbances, and stochastic renewable penetration is more aggravated especially when connected to grid. This needs more investigation for the smooth operation of power system and employment of power electronics-based costly control may not be economic for a MG. Also in the current scenario of deregulated market, more stress is imposed on the optimal use of present resources like mechanical torque control provided by turbine governors. In this work, a synchronous generator(SG)-based grid connected MG with Solar Photo Voltaic (SPV) and wind integration has been investigated for low frequency oscillation pertaining to small signal stability enhancement. A new simple governor (Gov)-Power system stabilizer (PSS), which is GOV-PSS controller has been proposed here with proportional integral derivative (PID), lead-lag and fractional lead-lag PSS actions, which coordinates the governor and PSS for oscillation damping and can be easily implemented. The gains of proposed controller are tuned by a new hybrid differential evolution with improved gray wolf optimizer with a multi objective function. The SPV, wind generations, and reference voltages are randomly varied giving rise to critical oscillatory instability, and proposed optimal controller is implemented to damp these oscillations. The excitation gains are also tuned for all generators subject to each condition such that the tuning of PSS would not adversely influence terminal voltage control. Time and frequency response of the system have been analyzed with 9-bus and 33-bus MG structures employing three generators of 1.32 MVA, 0.91 MVA, and 0.67 MVA. Solar and wind penetrations are executed with the bus connected to 1.32 MVA for 9-bus system and with all generators for 33-bus system. The oscillations due to renewable penetrations are found to be enhanced with reduced synchronous generation contribution. It is observed that properly tuned governor and PSS coordinate each other to enhance stability in proposed controller much effectively in contrast to only governor and PSS actions considered individually. Also turbine governors need not be blocked to damp inter area oscillatory mode, rather their efficacy is much enhanced with proposed control action, and this can be implemented to any SG-based generation including gas, steam, and hydro power-based plants.

Damping sensitivity analysis and optimized battery controller for small-signal stability enhancement in wind penetrated networks

Alarming greenhouse gaseous emissions is one of the key factors for meeting future energy demand from sustainable eco-friendly resources like wind and solar. These resources use power electronic converters for the interconnection with the grid resulting in their zero/low inertia response. This can lead to non-deterministic damping of low-frequency oscillations in the power system. Moreover, this may impose Small-Signal Stability (SSS) challenges for the secure operation & control of power systems. A two-stage method is proposed in this paper to enhance the damping of multiple critical modes in large interconnected networks with high penetration of wind turbine generators (WTGs). Damping Ratio Sensitivity Index (DRSI) at a candidate location is the summation of sensitivities of damping ratios (DRs) of critical electromechanical modes (EMs) against inertia. But, the sensitivities of DRs of various EMs w.r.t inertia at a specific candidate location can be equal and opposite. This can lead to their mutual cancellation and hence DRSI may not be sufficient to identify the impact of WTGs in networks with multiple critical EMs. Thus, stage-1 of the proposed method introduces an improved Weighted Damping Sensitivity Ratio (WDSR) for identifying the locations for integrating WTGs with beneficial impacts on SSS. It assigns weight to the sensitivity factors of DRs and hence annihilates the problem with their amalgamation which exists in the case of DRSI. The modified WDSR performs the sequential computation of DR sensitivity analysis. This ensures that the variations in the DR sensitivities of critical modes against inertia due to WTG integration are not ignored. A multiband Optimized Battery Damping Controller (OBDC) is proposed in stage-2 for improving the damping of critical inter-area (IA) modes in networks with high WTG penetration. The location of the battery energy storage system (BESS) is determined based on a stability index. The proposed multiband controller is implemented using a single BESS and is optimally tuned for the most vulnerable operating scenarios identified for the critical modes. The performance of the proposed two-stage method is evaluated using the modified IEEE 68 bus system for a wide range of operating conditions and it is observed that damping of all the critical modes has improved to more than 5% in each operating scenario.

Small-Signal Stability Enhancement Approach for VSC-HVDC System Under Weak AC Grid Conditions Based on Single-Input Single-Output Transfer Function Model

The voltage source converter (VSC) system has stability issue under weak AC grid conditions. In this paper, the multi-input multi-output (MIMO) transfer function model of VSC system in frequency-domain is derived. Then, the individual channel analysis and design (ICAD) approach is employed to develop the equivalent single-input single-output (SISO) feedback control model for stability analysis. On that basis, the stability of VSC system and the coupling interaction intensity among the multiple control loops, including the active power control (APC), reactive power control (RPC) and phase-locked-loop (PLL) are investigated. The results show that larger PLL bandwidth increases the coupling degree of active power control (APC) and reactive power control (RPC) closed loops, resulting in the instability of the system under weak AC grid conditions. Finally, a derivative feedback compensation (DFC) approach is proposed to enhance the stability margin for VSC system connected to weak AC grid. The results based on MATLAB-based theoretical analysis and electromagnetic transient (EMT) simulations show that the proposed DFC approach can effectively suppress the instability of VSC system due to the close coupling of APC and RPC closed loops caused by the large PLL bandwidth, thus effectively improve the stability margin of the system.

Enhancement of small signal stability in inverter‐dominated microgrid with optimal internal model controller

Enhancement of small signal stability in <scp>inverter‐dominated</scp> microgrid with optimal internal model controller

Small Signal Stability Enhancement of a Multimachine Power System Using Probabilistic Tuning PSS Based in Wide Area Monitoring Data

Small Signal Stability Enhancement of a Multimachine Power System Using Probabilistic Tuning PSS Based in Wide Area Monitoring Data

Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review

Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review

Optimal Allocation of Renewable Energy Hybrid Distributed Generations for Small-Signal Stability Enhancement

This paper solves the allocation planning problem of integrating large scale renewable energy hybrid distributed generations and capacitor banks into the distribution systems. Extraordinarily, the integration of renewable energy hybrid distributed generations such as solar photovoltaic, wind, and biomass takes into consideration the impact assessment of variable generations from PV and wind on the distribution networks’ long term dynamic voltage and small-signal stabilities. Unlike other renewable distributed generations, the variability of power from solar PV and wind generations causes small-signal instabilities if they are sub-optimally allocated in the distribution network. Hence, the variables related to small-signal stability are included and constrained in the model, unlike what is obtainable in the current works on the planning of optimal allocation of renewable distributed generations. Thus, the model is motivated to maximize the penetration of renewable powers by minimizing the net present value of total cost, which includes investment, maintenance, energy, and emission costs. Consequently, the optimization problem is formulated as a stochastic mixed integer linear program, which ensures limited convergence to optimality. Numerical results of the proposed model demonstrate a significant reduction in electricity and emission costs, enhancement of system dynamic voltage and small-signal stabilities, as well as improvement in welfare costs and environmental goodness.

Enhancement of Small Signal Stability of SMIB System with Robust Power System Stabilizer

As power system experiences low frequency oscillations due to disturbances, these low frequency oscillations are related to the small signal stability of a power system. The phenomenon of stability of synchronous machine under small perturbations is explored by examining the case of an SMIB system. The analysis of SMIB gives physical insight into the problem of low frequency oscillations. The SMIB system is predominant in local mode low frequency oscillations. These oscillations may sustain and grow to cause system separation if no adequate damping is available. The damping is provided by adding Power System Stabilizer for Synchronous Machine. In addition, as power system is nonlinear in nature, application of robust control techniques is mandatory to face the challenge of dynamic conditions. Hence, this work aims to design robust Power System Stabilizer for Synchronous Machine in order to damp the rotor speed deviations.

A Sequential Approach for Small Signal Stability Enhancement With Optimizing Generation Cost

A small signal stability enhancement method is proposed based on optimal power flow model, where small signal stability (SSS) is considered as additional constraint. For handling the discontinuity and high nonlinearity of SSS constraint, a sequential approach is proposed to decompose the original optimization problem into a sequence of sub-problems. For every sub-problem, SSS constraint (i.e., critical eigenvalues) is linearized locally within bounded region. To ensure the effectiveness of eigenvalue sensitivity, a trust region strategy is used for dynamically updating the region size in solving sub-problem sequence. For preventing constrained eigenvalues from varying between critical and uncritical modes in the solving process, an active set strategy is adopted to construct the constraint set and control the solving process. A set of candidate operating points, with different generation cost and minimum damping ratio, is extracted from solution of the sub-problem sequence, which allows to make trade-off between economic efficiency and stability level for system operation. Three test systems are used to validate the effectiveness and applicability of the proposed method.

Enhancement of small signal stability of power system using UPFC based damping controller with novel optimized fuzzy PID controller

Enhancement of small signal stability of power system using UPFC based damping controller with novel optimized fuzzy PID controller