Synchrophasor Associated Adaptive Control Strategy for Under Frequency Protection and Load Shedding in Smart Grid

In recent years several catastrophic power systems blackouts have occurred worldwide. Various reasons have been declared for these failures. Economical limitations due to power system restructuring restrictions, inadvertent operation of protective relays and inefficient design of conventional load shedding schemes are of the most important reasons causing these blackouts. In fact, due to both economical and technological restrictions, it is not possible to completely prevent these blackouts. However, with the aid of some protection and control strategies, frequency and intensity of these blackouts may be reduced. One of the important protection strategies used for this purpose is a class of protection schemes known as ‘System Protection Schemes’ or ‘Wide Area Protection Schemes’. One of the most commonly used types of system protection schemes, generally accepted after the north-eastern blackout of 1965, is Under Frequency Load Shedding (UFLS) scheme. Conventional under frequency load shedding scheme is designed to retrieve the balance of generation and consumption following a disturbance. In the conventional load shedding method frequency settings, time delay settings and the amount of load to be shed in each step are constant values. The loads to be shed by this scheme are also constant load feeders and are not selected adaptively. Using this constant non-adaptive load shedding algorithm is not the most efficient scheme for all power system disturbances. In some combinational disturbances, events causing frequency to drop are followed by other events causing voltage drop. In these cases, since loads are voltage dependent, total system load is reduced and system frequency might not decrease so much to activate UFLS relays. However, the system could eventually collapse due to voltage instability. In many such cases the system would survive if the load shedding relays operate adaptively and appropriately. For example if for large disturbances, higher frequency settings and lower time delays are used adaptively, a faster load shedding response is obtained and as a result system collapses may be prevented. In this paper a new UFLS algorithm is proposed. The purpose of this algorithm is to adaptively adjust speed of load shedding based on the magnitude of disturbance. In this method rate of frequency decline is used as a criterion to determine intensity of disturbance. Thereby, for large disturbances higher frequency settings and lower time delays are used. Application of the proposed algorithm to the simulated model of Khorasan network in Iran confirms its satisfactory performance. As the results of simulations show, several voltage collapse instabilities may be prevented by using the proposed adaptive UFLS method.

Under frequency load shedding is implemented to restore power system frequency stability if system frequency drops below the operational set point during major disturbance such as lost of generation. Different countries/utility companies have their own philosophies in implementing the under frequency load shedding scheme. Generally, it is based on country/utility requirements, e.g. the overall power system network and the country's demographic. This paper presents the principles and implementation of the under frequency load shedding (UFLS) and presented using simulations of 56 test bus-system. The performance of the developed schemes under various conditions of disturbance were compared and analyzed. All the simulation works were performed using Siemens PTI software PSS®E.

The paper describes the formulation and application of an Optimal Power Flow (OPF)-driven Under Frequency Load Shedding (UFLS) scheme in low-inertia power grids hosting large-scale battery energy storage systems. Thanks to the accurate prediction of the system dynamics subsequent to a large contingency, the adopted OPF-UFLS is capable of minimizing the amount of load to be shed while ensuring a safe trajectory of the system frequency and preventing nodal voltages and branch currents to violate their feasible limits. The performance of the method is assessed by using numerical simulations of a fully-modeled IEEE 39-bus low-inertia power grid with two configurations. Furthermore, the obtained results are compared with those of the UFLS strategy recommended by European Network of Transmission System Operators (ENTSO-E).

Power system blackouts have become a serious problem for electric utilities especially in recent years. Different forms of system instability have emerged in recent blackouts, such as voltage instability and frequency instability. To counteract each form of system instability, special algorithms have been designed in the protection system, e.g. Under Frequency Load Shedding (UFLS) and Under Voltage Load Shedding (UVLS) schemes. One of the major weaknesses of these algorithms is that combination of different forms of instability is not considered in their design, while any one form of instability may not occur in its pure form. This is particularly true in highly stressed systems and for cascading events. This paper presents an adaptive algorithm to combine UVLS and UFLS schemes. The purpose of this method is to enhance the flexibility of under frequency relays and increase the security of power system during large disturbances by improving system voltage stability margins. In the proposed algorithm, loads with greater voltage decay are shed sooner. In this way, locations of load shedding become dependent to the location of disturbance and voltage stability margins of the system are enhanced. Indeed, load shedding is performed faster for severe events accompanying large voltage or frequency declines. Using this load shedding method, faster reactions could be obtained for major system failures. This way, system blackouts could be better controlled. Performance of the proposed method is compared with the conventional UFLS method. In this paper, dynamic model of the Khorasan HV network of Iran national grid is used for simulation. This network includes 75 high voltage 400 kV and 132 kV buses with about 2700 MW of generation. Performance of the schemes has been evaluated using dynamic simulations as well as the P-V curves, and reactive power margins for a number of events. Simulation results show that conventional UFLS algorithm will not necessarily result in acceptable voltage stability margins for the system following a disturbance. Meanwhile, the proposed algorithm improves voltage stability margins. The proposed algorithm is suitable for saving system stability after occurrence of major system disturbances.

The traditional load shedding schemes––––under frequency load shedding (UFLS) and under voltage load shedding (UVLS), are designed independently and they constitute the last line of defense against frequency and voltage instability. However, the traditional load shedding schemes are not capable of dealing with combined instabilities. Moreover, a new Adaptive load shedding under load shedding method was proposed based on wide area measurement information just because the traditional load shedding schemes was not optimization algorithm. The main purpose of the method goal is to set up an emergency load shedding strategy, considering the recovery system of frequency stability at the same time, improved the voltage stability. This process has two steps, first of all, when considering the system disturbance amplitude and classifying the degree of interference according to system disturbance, Furthermore, the voltage sensitivity analysis was considered to determine the shedding location and corresponding shedding value. Finally, this algorithm was applied in IEEE 10-generator 39-bus test system. The implementation emergency of traditional and new shedding load two methods Under the system by different levels of power disturbances, comparing and analysand the feasibility and effectiveness of the new project. The results showed that the new method avoiding shedding over, more shedding part of the reactive power load, and then improving the system voltage, also avoiding damage to the voltage stability in the process of the system restore.

This paper presents a data-driven methodology for estimating under frequency load shedding (UFLS) in small power systems. UFLS plays a vital role in maintaining system stability by shedding load when the frequency drops below a specified threshold following loss of generation. Using a dynamic system frequency response (SFR) model we generate different values of UFLS (i.e., labels) predicated on a set of carefully selected operating conditions (i.e., features). Machine learning (ML) algorithms are then applied to learn the relationship between chosen features and the UFLS labels. A novel regression tree and the Tobit model are suggested for this purpose and we show how the resulting non-linear model can be directly incorporated into a mixed integer linear programming (MILP) problem. The trained model can be used to estimate UFLS in security-constrained operational planning problems, improving frequency response, optimizing reserve allocation, and reducing costs. The methodology is applied to the La Palma island power system, demonstrating its accuracy and effectiveness. The results confirm that the amount of UFLS can be estimated with the mean absolute error (MAE) as small as 0.179 MW for the whole process, with a model that is representable as a MILP for use in scheduling problems such as unit commitment among others.

This paper explains a fast acting Under Frequency Load Shedding and restoration scheme. This load shedding technique has an added advantage of selecting the amount of load which is to be dropped at a particular frequency threshold. The amount of load dropping is selected based on the rate of change of the frequency. Automatic restoration of loads is discussed with engaging a command signal from the system control centre. On/Off control of the power factor correction capacitor is also explained based on the magnitude of its terminal voltage. A three phase voltage vector Phase Lock Loop (PLL) is developed in EMTDC/PSCAD environment to measure the frequency of the power system. The PLL is tuned together with a filter to smooth the frequency measurement. This PLL measures the frequency online and based on phase angle deviation. Therefore it has a fast initial response. A load shedding factor is selected based on the rate of change of frequency between the specified thresholds. According to the load shedding factor the amount of load is selected. Load shedding and automatic load restoration operations are triggered accordingly when the frequency passes its relevant thresholds. The proposed distributed load shedding and restoration control technique was tested for IEEE 12 bus system at two different grid substations. The simulation results confirmed the fast, proper and smooth operations of the proposed technique.

With the increasing incorporation of Renewable Energy Sources (RESs) like solar Photovoltaic (PV) systems, maintaining frequency stability has turned out to be a significant challenge owing to decreased system inertia. Despite numerous developments in Load Frequency Control (LFC), existing solutions largely overlooked the issue of Under Frequency Load Shedding (UFLS) relay failure during rapid frequency decline, which led to widespread blackouts. To address this critical gap, a novel intelligent control framework integrating the Fuzzy Doubleton Parabolic Inference System (FDPIS) and the Proportional Quad-Alpine Integral Derivative (PQAID) controller for UFLS relay failure mitigation and enhanced LFC in Solar-PV systems is proposed. Primarily, the Direct Current (DC) power from the solar module is fed into the DC-DC boost converter and Maximum Power Smoothstep Point Tracking (MPSPT) algorithm. A capacitor bank failure is detected using FDPIS, and voltage stabilization is ensured through a Savitzky-Golay Dynamic Polynomial-Z Voltage Restorer (SGDP-ZVR). To predict electrical load demand accurately, a hybrid Deep Learning (DL) model, Deep Dualplus Softshrink Pan–Long Short Term Inverse Parzen Memory (2DSP-LSTIPM), is employed, delivering a high accuracy of 98.98 % with a Root Mean Squared Error (RMSE) of 0.002. When demand exceeds thresholds, transmission overload is mitigated using an Inductive Snubber Cubic Circuits–STATCOM (IS2C-STATCOM). The frequency deviation is identified via FDPIS, followed by the Rate Of Change Of Frequency (ROCOF) analysis. If a UFLS relay failure is detected, then the PQAID controller is activated to ensure stable operation. The proposed PQAID achieves a peak time of 1.91 ms, significantly outperforming traditional PID, PI, and PD controllers in transient and overshoot metrics. Simulation results on the HEDGW dataset assess the proposed approach’s robustness and low time complexity. The system demonstrates superior relay fault detection (fuzzification/defuzzification times of 452ms/463ms) and faster rule generation (597 ms) compared to conventional fuzzy systems. Overall, the proposed methodology provides a comprehensive, real-time, and scalable solution for enhancing frequency stability, relay fault mitigation, and load management in solar PV-based smart grids. • Integrates FDPIS and PQAID for real-time UFLS relay failure detection and mitigation in solar PV systems. • Proposes novel 2DSP-LSTIPM deep learning model achieving 98.98 % demand prediction accuracy with RMSE of 0.002. • Introduces SGDP-ZVR for voltage stabilization during capacitor bank faults using Savitzky-Golay filtering. • Deploys IS2C-STATCOM for efficient transmission overload control with fast reactive power regulation. • Enables seamless SCADA/EMS integration via OPC-UA protocol for smart grid compatibility and deployment.

Modified centralized ROCOF based load shedding scheme in an islanded distribution network

An electrical network constantly faces unforeseen events such as faults on lines, loss of generation, etc. Under Frequency Load Shedding (UFLS) and Generator Tripping are traditional methods used to stabilise a network when a transient fault occurs. These methods will prevent any network instability by shedding load or tripping the most critical generator at a calcultated time when required. By executing these methods, the network can be stabilised in terms of balancing the generation and the load of a power system. A hybrid control scheme is proposed where the traditional methods are combined to reduce the stress levels exerted on the network and to minimize the load to be shed.

The most severe consequences for the power system occur during system accidents with the occurrence of a large deficit in the generated active power and a deep decrease in frequency. To prevent and limit the frequency avalanche, a complex of automatic frequency reduction limitation (AFRL) is used, namely its main component is under frequency load shedding (UFLS). The UFLS device is one of the emergency control (EC) devices, which is not provided as a separate component in some of the leading computer systems. In this paper, it is developed a component that implements the functions of under frequency load shedding in the power system. The introduced study briefly discusses the modeling of UFLS processes in the PSCAD/EMTDC software and testing the operation of the component developed by the authors.

Enhancing power system stability with adaptive under frequency load shedding using synchrophasor measurements and empirical mode decomposition

Against the backdrop of continuously increasing renewable energy penetration, the large-scale integration of wind power has significantly altered the output characteristics of generation units. The growing volatility of wind power output exacerbates the complexity of frequency regulation, potentially rendering traditional under frequency load shedding (UFLS) strategies inadequate. Investigating methods that leverage the frequency regulation capabilities of doubly-fed induction generators (DFIGs) and coordinated demand-side load clusters to participate in UFLS holds significant research value for enhancing power system frequency stability, reducing load curtailment, and improving power supply reliability. Therefore, this paper proposes an optimized UFLS strategy considering large-scale wind power integration. The frequency response models of wind turbines and thermostatically controlled loads (TCLs) in grid frequency regulation are analyzed, and the configuration principles for implementing UFLS in power systems are elaborated. A simulation model incorporating both wind turbines and TCLs in frequency regulation is developed, and UFLS simulations are conducted based on the operational conditions of a regional power grid. The results demonstrate that the participation of wind power and TCLs in frequency regulation not only ensures grid security but also significantly reduces load curtailment.

This paper discusses why voltage as well as frequency load shedding may be necessary to prevent major system blackouts. This paper explores the nature of recent power system blackouts and explains why voltage collapse is the leading edge indicator of impending power system problems. It also discusses the design and security issues that need to be addressed in the design of an undervoltage load shedding (UVLS) scheme and why relying on underfrequency load shedding (UFLS) may be "too little, too late." The paper addresses the current level of UVLS on utility systems as well as current NERC (North American Electric Reliability Council) pronouncements on the subject

Wind energy is becoming a major source of generation in many countries because of its zero fuel cost and no air pollution. Due to the integration of large-scale wind power in conventional grids, synchronous generators are being economically replaced. Modern wind turbine generators (WTGs) are based on power electronic interfaces. Hence, unlike synchronous generators, they do not usually provide inertia and governor response. Therefore, from a power system security point of view, wind penetration can be limited by frequency response criteria. Up to now, several methodologies have been proposed to estimate the maximum wind penetration level. However, none of them suggest how a system operator could be immediately informed about a secured wind penetration limit as soon as a generation profile is known. Therefore, a tool to estimate the maximum wind penetration level by maintaining an adequate frequency response is proposed in this thesis. The proposed tool is able to instantly provide the highest margin of wind power that could be dispatched at a particular load condition without violating frequency response constraints. In some power systems, the combined generation capacity of wind and distributed photovoltaic (PV) sources is close to reaching the level of average demands (e.g. South Australia). Under high availability of wind and PV, a few synchronous machines may be required to be committed for frequency regulation and hence the system can be viewed as a low inertia grid. Such a grid could be potentially at risk of experiencing an excessive rate of change of frequency (ROCOF) after a contingency. A high ROCOF may initiate tripping of other synchronous generators. As a result, network frequency response may become more vulnerable and the system may be subject to significant under frequency load shedding (UFLS) or even at risk of a blackout. Furthermore, some existing distributed PV units may have a default under frequency protection setting, which is higher than the UFLS threshold. Hence, a contingency may cause a subsequent trip of those PV units. It may result in an unacceptable low frequency, triggering further load shedding. To explore the above issues, the effects of cascading contingencies triggered by high ROCOF and PV tripping on the frequency response of a low inertia grid are investigated in this thesis. Remedial measures using synchronous condenser and WTG frequency support to prevent the cascading contingencies are also suggested. Any mismatch between load and generation is intended to be balanced by contingency reserve, which is also known as contingency Frequency Control Ancillary Services (FCAS) requirement. Load frequency relief (LFR), which represents the effect of frequency dependent loads on power system frequency excursion, is crucial for correctly evaluating contingency FCAS requirement during a generation dispatch to ensure an adequate frequency response. Conventionally, the LFR is considered as a fixed quantity during the estimation of frequency response and FCAS requirement. However, recent experience in the Australian power system suggests that such an assumption may lead to an inaccurate outcome. To explore the above issue, the LFR is investigated based on field measurement data. Data were captured from different locations in the Southern states of Australia. An approach is developed to identify the predominating factors affecting the LFR. A technique is then proposed to appropriately determine the LFR and contingency FCAS requirement at any operating conditions. Along with frequency response, short-circuit performance is another vital index regarding power system security. Modern WTGs have limited fault current contributions, which may cause unacceptable short-circuit ratios at the grid connection point of those wind power plants. Traditionally, frequency response and short-circuit performance are individually improved. However, both of them are simultaneously affected by high wind penetration. Hence, a common approach to concurrently enhance both indices is essential. Therefore, an idea of operating some of the retired synchronous generators in the synchronous condenser mode, which is termed as ‘post-retirement scheme’, is introduced in this thesis. Such a second use of the retired synchronous generators can jointly improve frequency response and short-circuit strength during high wind penetration. A methodology is proposed to determine when and how much post-retirement scheme should be deployed for ensuring adequate security performances in a wind dominated power system.