Under-frequency Load Shedding Scheme Research Articles

Robust optimal design of UFLS schemes in island power systems

Since settings of conventional underfrequency load shedding (UFLS) schemes cannot be adjusted in real-time, this paper proposes a novel robust optimal design method of the UFLS scheme for an island power system (IPS) that once fixed, gives an adequate performance in all possible operating conditions in the IPS. The core of the novel robust optimal design method is the implementation of a synthetic data generation algorithm that covers all the feasible generator operating points, which are further classified into a set of large number (but computationally manageable) representative generation dispatches using clustering techniques. A real-world Spanish island will be used to illustrate the method, where the UFLS robust design will be tested and compared with non-robust UFLS designs tuned using generation dispatches of an actual day of operation provided by both standard and frequency-constrained unit commitment algorithms. Results will show that the proposed robust design avoids frequency constraints violations in contingencies and obtains better frequency metrics.

Under-frequency load shedding setting method of new energy sending-end system based on improved IMQ-GWO algorithm

Aiming at the problems of low qualification rate, poor stability, and insufficient timeliness of the existing under-frequency load shedding implementation scheme at the new energy sending end, this paper proposes an under-frequency load shedding setting method for the new energy sending end system based on the improved IMQ-GWO algorithm. Firstly, considering the fluctuation of the trend of the line of the sending end system relative to the load curve of the whole network, the index system of the implementation scheme based on the under-frequency load shedding is established. Secondly, the objective function is established for the index system of the under-frequency load shedding scheme, and the under-frequency load shedding setting model is established considering the static constraints and transient constraints of the system. Then, the grey wolf optimization algorithm (GWO) is updated by using the characteristics of the IMQ function. At the same time, the individual position is adaptively updated based on the Sigmoid exponential function to better search and optimize the solution space of the problem. Finally, based on the modified IEEE39 node, the empirical analysis is carried out, and the improved IMQ-GWO algorithm proposed in this paper is used to solve the under-frequency load shedding setting model. It is proved that the proposed method is superior to other methods in terms of execution qualification rate, stability, and application timeliness.

Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection

Under-frequency load shedding (UFLS) schemes are the latest safety measures applied for safeguarding the integrity of the grid against abrupt frequency imbalances. The overall inertia of electrical power systems is expected to decrease with an increased penetration of renewable energy as well as elements connected through power electronic interfaces. However, voltage source converter-based high voltage direct current (VSC-HVDC) links can provide virtual inertia through a control loop that allows for a reaction to occur at certain frequency fluctuations. This paper evaluates a UFLS scheme that considers the injection of virtual inertia through a VSC-HVDC link. A genetic algorithm (GA) is used to determine the location of the UFLS relays, the activation threshold of each stage, the delay time and the percentage of load shedding at each stage. It was found that the virtual inertia causes the nadir to delay and sometimes reach a greater depth. Furthermore, the implemented GA approximates the frequency response to the limits set with the constraints, reducing the load shedding but achieving a steeper nadir and a lower steady-state frequency level than traditional UFLS. The simulations were performed using the IEEE 39-bus test system.

A RoCoF-constrained underfrequency load shedding scheme with static voltage stability-based zoning approach

The modern power system is proliferating in terms of size, capacity, and nature of integrated components. Such expansion engendered an increasing risk of system strength and security, posing a more significant operational challenge to power system operators (PSO). The frequency dynamics of the system under numerous possible contingencies serve as a metric to evaluate how efficiently the grid is being controlled. There are a couple of defensive mechanisms in case of inadvertent contingency events, namely - inertial response, governor control, underfrequency load shedding, and dispatch control. Inertial response and governor control institute the primary line of defense to arrest the frequency variation and Rate of Change of Frequency (RoCoF) and are triggered automatically from the dispatched machines. However, the final defense mechanism - load shedding (LS)– is designed and often controlled by the operators. There are numerous methodologies of how LS can be designed and implemented in a power system, many of which rely on some manipulation of historical operational data. Although it has been a widespread practice for PSOs to divide the grid into several zones for higher operation and control advantage, there has been very little research on how LS mechanisms can make use of the zonal allocation to tend to the local grid needs for more secure and reliable network performance. To this extent, this paper proposes a static voltage stability-based zoning mechanism using Fisher-Jenks natural breaks algorithm. The zoning scheme uses the reactive power margin of buses to cluster them into several zones. Subsequently, unique underfrequency load shedding (UFLS) schemes are devised for each zone stemming from the frequency response characteristics of that zone, particularly RoCoF. The proposed RoCoF-constrained zonal UFLS scheme is tested on IEEE Standard 39 bus network. The zonal scheme not only shows significant improvement in frequency response in individual zones over conventional UFLS schemes but also achieves that with less load shedding throughout the grid.

A Binary Archimedes Optimization Algorithm and Weighted Sum Method for UFLS in Islanded Distribution Systems Considering the Stability Index and Load Priority

This study proposes an under-frequency load-shedding (UFLS) scheme based on a binary Archimedes Optimization Algorithm (BAOA) and the Weighted Sum Method (WSM) to maintain the stability of an islanded distribution system. These methods consider stability indices and load priorities to ensure effective load shedding during frequency deviations. The BAOA determines the optimal load shedding based on the stability index and power mismatch that minimizes the impact on critical loads while maintaining system stability in an islanded distribution system. The WSM determines the rank of the load to be shed based on four criteria: the load priority, the load category, the stability index, and the load size. Each load is assigned a weight based on its priority. These weight variables determine the order in which loads are shed during frequency deviations. The effectiveness of the proposed UFLS was tested on an 11 kV Malaysian distribution network with two mini hydro distributed generation systems. A comparative study was conducted based on five result outputs, including the number of loads shed, the size of the loads shed, the frequency undershoot, the frequency overshoot, and the time taken to achieve a stable frequency in three cases: base load, peak load, and peak load with photovoltaics (PV). The proposed UFLS showed the best results for 11 of 15 outputs (73.3%) for islanding events and 9 of 15 outputs (60%) for overloading events. The voltage profile and stability index, also, were improved after the proposed UFLS was applied.

A Continuous Multistage Load Shedding Algorithm for Industrial Processes Based on Metaheuristic Optimization

At complex industrial sites, the high number of large consumers that make the technological process chain requires direct supply from the main high-voltage grid. Often, for operational flexibility and redundancy, the main external supply is complemented with small local generation units. When a contingency occurs in the grid and the main supply is cut off, the local generators are used to keep in operation the critical consumers until the safe shutdown of the entire process can be achieved. In these scenarios, in order to keep the balance between local generation and consumption, the classic approach is to use under-frequency load-shedding schemes. This paper proposes a new load-shedding algorithm that uses particle swarm optimization and forecasted load data to provide a low-cost alternative to under-frequency methods. The algorithm is built using the requirements and input data provided by a real industrial site from Romania. The results show that local generation and critical consumption can be kept in stable operation for the time interval required for the safe shutdown of the running processes.

Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors

The reactive nature of traditional under-frequency load shedding schemes can lead to delayed response and unnecessary loss of load. This work presents a proactive framework for power system frequency stability. Bayesian filters and synchrophasors are leveraged to produce predictions after disturbances are detected. By being able to estimate the future state of frequency corrective actions can be taken before the system reaches a critical condition. This proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease in the amount of compensation utilized. The framework is tested via Matlab simulations based on Kundur’s Two-Area System, and the IEEE 14-Bus System. Performance metrics are provided and evaluated against other contemporary solutions found in literature. During testing this framework outperformed other solutions by drastically reducing the amount of load dropped during compensation.

A logistic regression approach for improved safety of the under-frequency load shedding scheme owing to feeder machine inertia

Under Frequency Load Shedding (UFLS) is the last resource to maintain the power system frequency after contingences. Load shedding can be performed by conventional, adaptive, computational or wide area monitoring techniques. The most common is a conventional UFLS. Load shedding is accomplished when predetermined frequency thresholds are reached. Although the conventional methods are simple, easily implemented and dependable, they may operate improperly. In the Brazilian electric power system, several actions of the UFLS scheme were found to be improper owing to the dynamics of induction motors and distribution generation during the main source outage of distribution feeders. In this way, when the main source is out of service, machine inertia maintains the frequency for some electric cycles, leading the frequency relay to undue tripping. In this paper, the negative sequence voltage and the rate of change of frequency are handled by a logistic regression method to identify the events of improper action. The proposed method was evaluated through the modified IEEE 9-bus test system, and several cases have been tested. The proposed method reached a level of performance higher than 99% of correct operation, and it needs a small training set.

Adaptation of Battery Energy Storage System on Under-Frequency Load Shedding Scheme Design

The reliable operation of power systems is crucial for ensuring uninterrupted power supply to consumers. However, any deficiency in power generation can lead to frequency deviation, disrupting the entire power system. To address this challenge, an active power source with a fast response, such as a Battery Energy Storage System (BESS), can prove to be a highly effective countermeasure. The BESS has gained immense popularity for its diverse applications, including load leveling, frequency and voltage support during loss of generation, improving transient and dynamic stability, and enhancing power quality. This has made the BESS an invaluable contribution to power system restructuring. One of the most important applications of the BESS is in Load Frequency Control, where a proportional-integral (PI) controller is employed to modify the power output of the BESS, resulting in further optimization of the system. In this work, a two-area hydro-thermal interconnected system is considered, and simulations are performed in MATLAB to analyze the impact of the BESS with and without a PI Controller. The results demonstrate a significant reduction in the load shedding amount, and the under-frequency load shedding (UFLS) scheme is made even more effective, ensuring the reliable and uninterrupted operation of the power system.

Underfrequency Load Shedding Scheme for Islanded Microgrids Considering Objective and Subjective Weight of Loads

With the rapid development of microgrids, the types of users and loads in microgrids are increasing. Comprehensively reflecting the value of loads in load shedding decisions is one of the main challenges for the intelligent control of an islanded microgrid. However, the existing load shedding schemes ignore the user’s subjective preference for multiple attributes of loads, which are insufficient for reflecting the comprehensive value of loads. To address the aforementioned problem, an underfrequency load shedding (UFLS) scheme based on the comprehensive weight of loads is proposed. This scheme evaluates the multiple attributes of loads and the user’s preference for load attributes based on the entropy method with high adaptability (EMHA) and the analytical hierarchy process (AHP) to obtain the objective and subjective weights of loads. Then, the comprehensive weight of loads is calculated based on the relative entropy to determine the sequence of load shedding. Furthermore, the optimal objective function of the comprehensive cost of load shedding is constructed, and gray wolf optimization (GWO) is used to solve the objective function and obtain the optimal load shedding scheme. Ultimately, the effectiveness of the proposed scheme is verified based on a modified standard IEEE 37-bus system.

A Data-Driven Under Frequency Load Shedding Scheme in Power Systems

This paper presents a measurement-based under-frequency load shedding scheme that considers time delays, measurement uncertainties, and communication network faults. Using a moving first-degree polynomial function, an iterative approach to estimate the frequency nadir and the associated frequency nadir time is proposed. Then, a novel method to simultaneously estimate the power imbalance and the system inertia constant is developed. According to an analytical basis, a base system is selected from a set of pre-defined base systems to guarantee accurate power imbalance estimation. Finally, a mathematical index is investigated to calculate a threshold for the generation-load power imbalance beyond which loads should be shed. Further, a systematic approach for specifying the amount of load to be shed in each transmission bus of the system is proposed. The effectiveness of the proposed methodologies is examined on both simulated and actual measured data from 9 historical power system disturbances in a national power grid.

Underfrequency Load Shedding Strategy With an Adaptive Variation Capability for Multi-Microgrids

Multi-microgrids (MMGs) suffer from power shortages due to the loss of utility grid support when an unintentional transition occurs. This imposes a transient shock on the system voltage and frequency. To maintain the frequency stability and power balance of an islanded MMG, this paper presents an underfrequency load shedding (UFLS) strategy with adaptive variation. A comprehensive load evaluation method based on a composite least squares support vector machine (CLS-SVM) is proposed to ensure uninterrupted power for critical loads. This method considers the comprehensive evaluation influence factors (CEIFs) of loads. Then, a least squares support vector machine (LS-SVM) provides the load shedding determination factors, transforming the problem of determining critical loads into a 0-1 planning problem. A method with adaptive variation is proposed to solve the UFLS model. The effectiveness of the proposed strategy is verified for an MMG model based on a modified IEEE 33-bus system. The test results show that: 1) the average accuracy of the proposed method is 21.05% higher than that based on LS-SVM; 2) compared with UFLS strategies based on the load level alone and on an intelligent algorithm, the frequency fluctuation range of the proposed strategy is 12.50% and 19.23% lower, respectively, and the frequency recovery time is 3.90% and 5.73% shorter, respectively; 3) compared with PSO, GOA and GA, the standard deviation of the iterative mean of the proposed algorithm decreases by 36.22%, 53.42%, and 34.00%, respectively. The proposed strategy can reduce the frequency fluctuation range and frequency recovery time while maintaining strong adaptability.

Chance-constrained allocation of UFLS candidate feeders under high penetration of distributed generation

Under-Frequency Load Shedding (UFLS) schemes are the last resort to contain a frequency drop in the grid by disconnecting part of the demand. The allocation methods for selecting feeders that would contribute to the UFLS scheme have traditionally relied on the fact that electric demand followed fairly regular patterns, and could be forecast with high accuracy. However, recent integration of Distributed Generation (DG) increases the uncertainty in net consumption of feeders which, in turn, requires a reformulation of UFLS-allocation methods to account for this uncertainty. In this paper, a chance-constrained methodology for selecting feeders is proposed, with mathematical guarantees for the disconnection of the required amount of load with a certain pre-defined probability. The correlation in net-load forecasts among feeders is explicitly considered, given that uncertainty in DG power output is driven by meteorological conditions with high correlation across the network. Furthermore, this method is applicable either to systems with conventional UFLS schemes (where relays measure local frequency and trip if this magnitude falls below a certain threshold), or adaptive UFLS schemes (where relays are triggered by control signals sent in the few instants following a contingency). Relevant case studies demonstrate the applicability of the proposed method, and the need for explicit consideration of uncertainty in the UFLS-allocation process.

Improved Harmony Search Algorithm to Compute the Underfrequency Load Shedding Parameters

The power system continuously deals with frequency fluctuations. When a power disturbance occurs, the transmission system operators rely on the underfrequency load shedding (UFLS) scheme to address severe underfrequency (UF) events to maintain the frequency at the permissible level and prevent blackouts. Defining settings of a conventional UFLS scheme is a very complex problem due to the nonlinear nature of the frequency response, and the size of the problem is vast because of the number of UF-relays spread on the power system. The under or over total load disconnection produced by the wrong setting of the UF-relays can create secondary frequency events or even a total blackout. This paper introduces a novel method to compute an optimally parametrized conventional UFLS scheme in specific given operating conditions by formulating it as a constrained problem and using the Improved Harmony Search (IHS) algorithm to solve it. Since there is no previous knowledge of using IHS to solve the UFLS scheme, a numerical parameter sensitivity analysis (PSA) is developed to tune the parameter of the IHS algorithm. The IEEE 39-bus system was modelled in DIgSILENT® PowerFactory™ and used as a test system. The optimally parametrized conventional UFLS methodology presented in this paper reveals superior results against the conventional UFLS scheme, and the suitability of using the IHS algorithm is confirmed.

Impact of Low Inertia and High Distributed Generation on the Effectiveness of Under Frequency Load Shedding Schemes

The Under-Frequency Load Shedding (UFLS) scheme is an emergency measure in place to prevent system collapse in the event of a large generation deficit relative to demand at any moment in time. However, the effectiveness of traditional UFLS schemes may be compromised as network power flows change due to the growth of distributed generation (DG) and a reduction in system inertia. This study has shown some of the issues affecting the UFLS protection system with rising installed capacities of DG in the Great Britain power system. Simulation results show how the effectiveness of the scheme is challenged with current and future expected DG installed capacities and the risk of over shedding demand due to the scheme’s current settings is evaluated. Many proposed improvements to traditional load shedding schemes are based on upgrades to network monitoring and communication systems, which are not yet fully available. This study evaluates more readily available solutions, including relocation of under-frequency relays and reducing the time delay of the scheme, which may provide interim improvements to the UFLS scheme, based on a case study in GB.

Adaptive under‐frequency load shedding scheme for power systems with high wind power penetration considering operating regions

With the ever-increasing penetration of wind power into power systems, wind turbine generators (WTGs) are required to provide frequency regulation services to maintain the system frequency stability. For variable-speed WTGs, the adaptability of dissimilar frequency control strategies to different operating regions is distinct, which impacts the system frequency response. However, existing under-frequency load shedding (UFLS) schemes do not take that impact into account, causing improper load shedding after a loss of generation. To this end, this paper proposes an adaptive UFLS scheme for power systems with high wind power penetration considering operating regions. Based on the WTG operating characteristics in different operating regions, the appropriate frequency control strategy for each operating region is elaborated. The simplified frequency response model of the power system considering WTGs participating in frequency regulation is then established. According to the WTG active power response characteristics in different operating regions, the impact of WTGs participating in frequency regulation on UFLS is analysed. Accordingly, the method of accurately estimating the magnitude of the power deficiency and calculating the amount of load to be shed is proposed. Finally, the feasibility and effectiveness of the proposed UFLS scheme are verified through simulations on the IEEE 39-bus test system.

Adaptive Underfrequency Load Shedding And Voltage Stability In The Power System

Abstract Underfrequency load shedding is a common technique for maintaining the stability of the power system by removing the overload in a certain part of the system after a disturbance. The purpose of underfrequency load shedding is to balance output and load when a particular event causes a significant frequency drop in the power system. In conventional underfrequency load shedding schemes, the frequency thresholds of frequency relays are constant, this way it is difficult and sometimes impossible to control the frequency in various disturbances in the system. In this paper, an adaptive underfrequency load shedding (AUFLS) algorithm that is independent of communication between relays is presented. The relays are tuned to reduce loads taking into account local parameters such as voltage and frequency to prevent the occurrence of a cascade failure that can ultimately lead to the breakdown of the entire power system. In this paper, the rate of change of frequency (ROCOF) is obtained by applying the Hilbert-Huang transformation. Numerical simulations conducted on the New England 39 bus test system in the DIgSILENT PowerFactory and MATLAB software packages confirm the effectiveness of the proposed approach.

Adaptive Under-Frequency Load Shedding Control Strategy of Power Systems With Wind Turbines and UHVDC Participating in Frequency Regulation

Represented by wind turbines and ultra high-voltage DC (UHVDC), the power-electronic interfaced power sources participate in fast frequency control, which has a significant impact on the power system frequency. However, the conventional under-frequency load shedding (UFLS) scheme doesn’t take into account the impact above, resulting in unreasonable load shedding after a large loss of generation. To this end, this article proposes an adaptive UFLS control strategy of power systems with wind turbines and UHVDC participating in frequency regulation. Firstly, based on the virtual inertia control model and the primary frequency control model of wind turbines and UHVDC, the study establishes the simplified frequency response model of the power system considering the participation of wind turbines and UHVDC in frequency regulation. Furthermore, the impact of the active power response characteristics of wind turbines and UHVDC participating in frequency regulation on the magnitude of the active power deficiency is comprehensively analyzed. Thus the precise estimation of the magnitude of the power deficiency can be achieved, which provides technical guidance for multi-stage UFLS. Finally, simulation results demonstrate that the proposed UFLS strategy is capable of reflecting the power system frequency more objectively after a large loss of generation event. In addition, the proposed UFLS strategy outperforms the conventional UFLS strategy in terms of shedding less amount of load when the same desired effect of frequency recovery is achieved.

A New Method to Determine the Optimal Location and Amount of Shed Load in Multi-Stage Under Frequency Load Shedding Using DIgSILENT

Under-frequency load shedding (UFLS) appears to be an effective approach to preventing cascading outages that includes various methods. In recent years, much research has been done in the field of dynamic schemes. However, these schemes are less commonly used due to their disadvantages such as the inability to calculate the optimal shed load amount, the need to additional relays or communication infrastructures, etc. In contrast, static UFLS schemes are more common due to their simplicity, efficiency, fast implementation, as well as the unnecessity of additional equipment. However, how to determine the load shedding (LS) location and amount in static methods seems to be still challenging. Furthermore, conventional methods have a major drawback because of over shedding. In order to solve this problem, in this paper, a new static method is proposed to determine the location and amount of optimal LS based on co-simulation of DIgSILENT and MATLAB software. The system dynamics is simulated in DIgSILENT and optimization using imperialist competitive algorithm (ICA) runs in MATLAB. This co-simulation makes it possible to take advantage of both pieces of software. The results of the simulation on the IEEE 39-Bustest system in several scenarios clearly demonstrate the efficiency of the proposed method.

Dynamically adaptive method for under frequency load shedding protection scheme reconfiguration

The increased integration of the new generation technologies into the electric power system (EPS) which are mainly inverter-based changes its characteristics. The main issue that arises is the appearance of faster frequency dynamics that are caused by production connected through inverters. This leads to the need for changing conventional under-frequency load shedding (UFLS) schemes because, in cases of high dynamics of frequency change, conventional UFLS algorithms are not able to stop initial frequency drop and prevent power system collapse. This paper proposes reconfiguration method for conventional strategies transforming their response from static and inflexible to a dynamic and adaptive one. The focus of the paper is the proposed method for dynamical change of UFLS stage thresholds to minimize the number of activated UFLS stages during a particular disturbance event and therefore enable more efficient response of the system to further disturbances. The method effectiveness was demonstrated on a multi-machine power system model consisting of various generation technologies.