Load Shedding Approach Research Articles

Impact of Under Voltage Load Shedding Approach for Voltage Security Control in Power Quality Environment

Contingencies in power system are an ever-present problem for electrical engineers. They may cause the system to have low voltages due to active and reactive power deficiencies. Engineers shold consider the many solutions to approach this problem. The solution has to be appropriate to the contingency faced so as to be able to solve the issue without major damage to a power system. A drastic measure that can be used is by removing low voltage loads or ‘shedding’ the problematic loads. This method of Under Voltage Load Shedding is done by shedding or ‘islanding’ buses that have fallen to a predetermined minimum voltage for a predetermined time to prevent a cascade of blackouts in the widespread power system. The method to automate the process is by using two optimization techniques, Evolutionary Programming (EP) and Particle Swarm Optimization (PSO). This paper proposes a new hybrid algorithm, named Integrated Chaotic Swarm Based-Evolutionary Programming Optimization (ICSBEP) Technique for Voltage Security Control using Under Voltage Load Shedding (UVLS) approach. Voltage security is indicated by the reduction in voltage stability index, FVSI. In this study, EP, PSO and ICSBEP optimizations algorithms were developed and tested on a IEEE 30-bus reliability test system (RTS). Comparative studies were conducted to observe the advantages of the hybrid algorithm over traditional EP and PSO algorithms. The results obtained from the study can help manage the power quality of the system in ensuring that the customer receive secure electricity supply.

A Prioritised Automatic Switching Algorithm for Load Shedding Using Labview

Load shedding is employed at the Ghana Grid Company (GRIDCo) Tarkwa power substation to ensure a balance between power demand and available power. This involves taking off loads from the power transmission network when demand exceeds available power. Such loads are later reintroduced when available power is adequate to supply applied loads. The traditional technique of load shedding employed at the GRIDCo power substation in Tarkwa requires dropping electrical loads based on frequency variations. This may lead to dropping load of entire sections without consideration of essential loads. Research into prioritised load shedding algorithm using semi adaptive load shedding approach can continuously monitor and switch loads at the study area which is a transmission substation located in the Western Region of Ghana. Electrical Transient Analysis Program (ETAP) software version 2019 was used to simulate the single line system of the GRIDCo substation to determine the rate of change of frequency against varying loads. The implementation of the proposed technique was achieved with Laboratory Virtual Instrument Engineering Workbench (LabVIEW) software version 2019. Using typical load shedding data from the GRIDCo Tarkwa power substation, the proposed design was tested and found to be effective in carrying out load shedding.

Precise emergency load shedding approach for distributed network considering response time requirements

Emergency load shedding (ELS) is a vital measure for power systems to manage extreme events, ensuring the safety, stability, and economic operation of the grid. The integration of distributed energy resources and controllable devices in modern power systems has bolstered grid flexibility. Consequently, developing precise load shedding strategies to balance economic and security goals has emerged as a prominent subject in power system optimization. However, existing methods exhibit inadequacies, including overlooking practical operability, privacy concerns, and a lack of adaptability to response time requirements. To address these gaps, this paper introduces a precise ELS approach for distributed networks with a focus on response time needs. Contributions encompass designing load shedding processes for various response times, integrating demand response, and partitioning networks for optimized load shedding. Through validation using standard test cases, the proposed approach effectively utilizes response time and demand-side resources for precise ELS control in distribution networks. It accommodates different scenarios, offering a robust solution for rapid and accurate load shedding during emergencies.

Particle Swarm Optimization Trained Feedforward Neural Network for Under-Voltage Load Shedding

This paper suggests an under-voltage load shedding (UVLS) approach to avoid voltage collapse in stressed distribution systems. Prior to a blackout, a failing system reaches an emergency state, and UVLS is executed as the final option to prevent voltage collapse. Hence, this article introduces an optimal UVLS method using a feedforward artificial neural network (ANN) model trained with the particle swarm optimization (PSO) algorithm to obtain the optimal load shedding amount for a distribution system. PSO is used to obtain the best topology and optimum initial weights of the ANN model to enhance the precision of the ANN model. Thus, the dispute between the optimum fitting regression of the allocation of ANN nodes and computational time was disclosed, while the MSE of the ANN model was minimized. Moreover, the proposed method uses the stability index (SI) to identify the weak buses in the system following an emergency state. Different overload scenarios are examined on the IEEE 33-bus distribution network to validate the efficacy of the suggested UVLS scheme. A comparative study is performed to further assess the performance of the proposed technique. The comparison indicates that the recommended method is effective in terms of voltage stability and remaining load.

Coherency-Based Supervised Learning Approach for Determining Optimal Post-Disturbance System Separation Strategies

Controlled islanding is the last remedial action to prevent cascading outages or blackouts in power systems. Conventional methods presented for controlled islanding strategy determination, particularly those calculating load shedding values using optimization methods, are not fast enough in online applications for modern power systems. In this paper, a novel learning-based approach is introduced for online coherency-based controlled islanding in transmission systems. The proposed approach presents a prediction and optimization model, which is faster than conventional optimization-based models in two ways. Firstly, the proposed approach uses a classification model to predict the splitting scheme in a short time following the occurrence of a disturbance, and secondly in the proposed approach, a simpler optimization problem with fewer variables is solved to find the load shedding amount required in each area. In the proposed load shedding approach, some candidate system partitioning schemes are calculated beforehand and therefore, the load shedding optimization problem is simplified significantly compared to similar optimization-based approaches. Note that appropriate features, which are used in this paper as the input of the classifier, are acquired by processing post-disturbance phase angle variations, which are measured across the network. The proposed approach is simulated on the 16-machine, 68-bus system, and its accuracy and efficacy have been demonstrated.

Energy-Efficient Computation Offloading in Collaborative Edge Computing

Edge computing is an indispensable technology that overcomes delay limitations of cloud computing. In edge computing, computational resources are deployed at the network edge, and computational tasks and data of end terminals can be efficiently processed by edge nodes. Considering the computational resource limitations of edge nodes, collaborative edge computing integrates computational resources of edge nodes and provides more efficient computing services for end terminals. This article considers a computation offloading problem in collaborative edge computing networks, where computation offloading and resource allocation are optimized by means of a collaborative load shedding approach: a terminal can offload a computing task to an edge node, which either can process the task with its computing resource or further offload the task to other edge nodes. Long-term objectives and long-term constraints are considered, and Lyapunov optimization is applied to convert the original nonconvex computation offloading problem into a second problem that approximate the original problem and it is still nonconvex but has a special structure, which gives rise to a new distributed algorithm that optimally solves the second problem. Finally, the performance and provable bound of the distributed algorithm is theoretically analyzed. Numerical results demonstrate that the distributed algorithm can achieve a guaranteed long-term performance, and also demonstrate the improvement in performance achieved over the case of computation offloading without collaborating edge nodes.

Reinforcement‐learning‐based load shedding and intentional voltage manipulation approach in a microgrid considering load dynamics

In the case of a power mismatch in an island microgrid (MG), sharp variations occur in the frequency and voltages due to the low inertia and stochastic behaviour of distributed generation units and loads. Load shedding (LS) is the last corrective measure to achieve frequency regulation. A Q-learning-based under-frequency LS (QLLS) approach is proposed, in which the MG model is considered a grey box. Hence, the dependence of the proposed method on the grid model is minimized. The presented approach considers four main characteristics of the loads, including priority, dynamics, outage cost, and daily variations. In addition, to reduce the amount of the shed load, a supplementary intentional voltage manipulation (IVM) algorithm is presented that exploits the voltage dependency of loads as leverage to help frequency regulation. The proposed QLLS/IVM uses the observable MG states to find a corrective course of action to achieve frequency and voltage stability while keeping the under-frequency load shedding price as low as possible. The performance of the proposed QLLS/IVM approach is tested on the modified IEEE 37-node MG, and the results show feasibility, fast and optimal performance of the proposed algorithm.

Chaotic slime mould optimization algorithm for optimal load-shedding in distribution system

• Introduces Chaotic Slime Mould Algorithm (CSMA) as an optimal load shedding scheme of islanded DG integrated systems. • A fitness function comprising of maximum amount of remaining load and voltage stability margin (VSM) is adopted. • IEEE 33 bus and IEEE 69 bus distribution systems are used to assess the algorithm’s efficacy. • The proposed CSMA algorithm is compared with Slime mould algorithm (SMA) and Backtrack search algorithm (BSA). In addition, non-parametric statistical analysis have been conducted to adequately compare the algorithms. • In terms of fitness value, time consumption, and convergence characteristics, CSMA outperforms both BSA and SMA. In addition, CSMA ensures a better voltage profile and provides a solution with the least amount of load to be shed. The critical challenge for an efficient islanding operation of a distribution system having Distributed Generation (DG) is preserving the frequency and voltage stability. Contemporary load shedding schemes are inefficient and do not adequately assess the optimum amount of load to shed which results in either excessive or inadequate load shedding. Hence, this paper presents an optimal load shedding technique using Chaotic Slime Mould Algorithm (CSMA) with sinusoidal map in order to achieve greater efficiency. A constrained function with static voltage stability margin (VSM) index and total remaining load after load shedding was applied to accomplish the evaluation. A total of three islanding scenarios of IEEE 33 bus and IEEE 69 bus radial distribution systems were used as test systems to assess the efficacy of the proposed load shedding approach using MATLAB software. To identify performance enhancements, the developed method was compared to Backtrack Search Algorithm (BSA) and the original SMA. According to the results, CSMA outperforms both BSA and SMA in terms of remaining load and voltage stability margin index values in all the test systems.

A novel load shedding methodology to mitigate voltage instability in power system

Aim. A novel technique for detecting imminent voltage instability is proposed in this paper, accompanied by a novel load shedding approach to protect the system from voltage instability. Methodology. The proposed methodology utilizes the computation of nodal reactive power loss to voltage sensitivities with load increments in the system. Originality. The nodal reactive power loss to voltage sensitivity is a novel computation and is explored to detect the likelihood of voltage instability in this work. Results. If the system is experiencing an unprecedented load growth and if all the measures reach their limits, then load shedding is the last resort to safeguard the system against instability. The sudden change in nodal reactive power loss to voltage sensitivities is utilized to devise the quantity of load to be cut in the system. Practical value. The time-based simulations performed in New England 39 bus test system (NE-39 bus), the simulated results show that nodal reactive power loss to voltage sensitivities can be used as a trusted indicator for early diagnosing of menacing voltage instability and the timely implementation of load shedding developed from nodal reactive power loss to voltage sensitivities on the system ensures voltage stability.

Identification of Weak Buses for Optimal Load Shedding Using Differential Evolution

For the sustainability of power supply and operation systems, planners aim to deliver power at an optimum value to consumers, while maintaining stability in the system. The load-shedding approach has proven to be an effective means of achieving the desired stability. This paper presents a nodal analysis to establish critical bus identification in the power grid. A power simulation for load shedding was created using the power system analysis toolbox (PSAT) for identifying and isolating weak buses on the power system. A computational algorithm was developed using differential evolution (DE) for minimizing service interruptions and blackouts, and was tested against the conventional genetic algorithm (GA). The proposed algorithm was implemented on an IEEE 30-bus test system. The simulation results were analyzed before and after the application of DE. It was observed that after the application of DE, load shedding gives an efficient result of 10.6%, 8.7%, and 13.4% improvement at buses 26, 29, and 30, respectively, after being tested using a genetic algorithm (GA), with a result of 10.2%, 7.6% and 13.1% on the same respective buses. This work will further expand the reliability and availability of power systems toward a sustainable, steady power supply that is void of nodal or bus cutoffs.

Distributed Load Shedding considering the Multicriteria Decision-Making Based on the Application of the Analytic Hierarchy Process

This paper shows an analytic hierarchy process (AHP) algorithm-based approach for load shedding based on the coordination of the load importance factor (LIF), the reciprocal phase angle sensitivity (RPAS), and the voltage electrical distance (VED) to rank the load buses. This problem is important from a power system point of view, and the AHP method is able to support the decision-making process in a simple and intuitive way in a three-criterion environment. This satisfies the multicriteria decision-making to meet economic-technical aspects. The ranking and distributed shedding power at each demand load bus are based on this combined weight. The smaller overall weights of the load buses show the lesser importance of the load bus, the smaller reciprocal phase angle sensitivity, and the closer voltage electrical distance. Therefore, these load buses cut a larger amount of capacity, and vice versa. By considering the generator control, the load shedding consists of the primary and secondary control features of the generators to minimize the load shedding capacity and restore the system frequency value back to the allowable range. The efficiency of the suggested load-shedding scheme was verified via the comparison with the under-frequency load shedding (UFLS). The latter result is that the load shedding power of the suggested approach is 22.64% lower than the UFLS method. The case studies are experienced on the IEEE 9-generator; the 37-bus system has proven its effectiveness.

Reliability Evaluation of Bulk Power Systems Incorporating UPFC

Unified power flow controller (UPFC) is one of the most advanced flexible AC transmission system (FACTS) devices that can simultaneously and independently control both the real and reactive power flow in a transmission line. The utilization of UPFC can result in significant reliability benefits in modern power systems. This paper proposes a novel reliability network model for a UPFC, which incorporates the logical structure and the distinct operating modes of a UPFC. Two-state or three-state models have been used for UPFC by previous researchers. The proposed model divides the UPFC operating modes into four states, namely the UPFC up state, STATCOM state, SSSC state and UPFC down state, in order to improve the accuracy of the model by recognizing the practical operating states of a UPFC. The new model also incorporates an AC flow-based optimal load shedding approach to assess the impact of bus voltages and reactive power flow on UPFC in order to decide appropriate load curtailment in the reliability evaluation process. The performance of the proposed model is verified using a test system, and compared with different reliability models of UPFC. Various operating schemes, such as different placement locations of UPFC, and different capacities of UPFC are used to illustrate the advantages of the developed models, and to examine the impacts of UPFC on the system reliability.

Incorporating demand response in two-stage frequency emergency control

A decline in power system inertia challenges the frequency control, especially in a regional receiving-end power system. Conventionally, load shedding (LS) is the principal measure to recover the reduction in frequency. This paper proposes a two-stage frequency emergency control (EC) strategy to coordinate the LS and demand response (DR) techniques for frequency regulation to effectively and economically restore stable operation. The framework is divided into first-stage control (EC-I), second-stage control (EC-II), and coordination between EC-I and EC-II. EC-I deals with the condition when the system frequency markedly falls due to severe contingencies, with the LS approach adopted to alleviate the power-demand imbalance. Such control is devised to restore the system frequency above the set frequency index (fnadir,x) with the lowest cost. EC-II is performed based on EC-I to help the system promptly recover to a stable state. The LS and DR techniques are combined in EC-II to further reduce the control expenditure, and a control method for TCLs is proposed with less communication and computational burden to realize the power reduction. To minimize the overall control expenditure, a coordination process is designed with the coordination between EC-I and EC-II, which is reflected in the determination of the value of fnadir,x, as this parameter considerably influences expenditures in both EC-I and EC-II. The proposed framework is implemented in an IEEE 39-bus system, with simulation results demonstrating the effectiveness and economy of the strategy.

Linear Programming Based Approach for Generation Rescheduling and Load Shedding to Alleviate Power System Overloads.(Dept.E)

Linear Programming Based Approach for Generation Rescheduling and Load Shedding to Alleviate Power System Overloads.(Dept.E)

State-Aware Load Shedding From Input Event Streams in Complex Event Processing

In complex event processing (CEP), load shedding is performed to maintain a given latency bound during overload situations when there is a limitation on resources. However, shedding load implies degradation in the quality of results (QoR). Therefore, it is crucial to perform load shedding in a way that has the lowest impact on QoR. Researchers, in the CEP domain, propose to drop either events or partial matches (PMs) in overload cases. They assign utilities to events or PMs by considering either the importance of events or the importance of PMs but not both together. In this article, we combine these approaches where we propose to assign a utility to an event by considering both the event importance and the importance of PMs. We propose two load shedding approaches for CEP systems. The first approach drops events from PMs, while the second approach drops events from windows. We adopt a probabilistic model that uses the type and position of an event in a window and the state of a PM to assign a utility to an event. We, also, propose an approach to predict a utility threshold that is used to drop the required amount of events to maintain a given latency bound. By extensive evaluations on two real-world datasets and several representative queries, we show that, in the majority of cases, our load shedding approach outperforms state-of-the-art load shedding approaches, w.r.t. QoR.

Decoupled piecewise linear power flow and its application to under voltage load shedding

Various optimizations in power systems based on the AC power flow model are inherently mixed-integer nonlinear programming (MINLP) problems. Piecewise linear power flow models can handle nonlinearities and meanwhile ensure a high accuracy. Then, the MINLP problem can be turned into a tractable mixed-integer linear programming (MILP) problem. However, piecewise linearization also introduces a heavy computational burden because of the incorporation of a large number of binary variables especially for large systems. To achieve a better tradeoff between approximation accuracy and computational efficiency, this paper proposes a model named decoupled piecewise linear power flow (DPWLPF) for transmission systems. The P-Q decoupling characteristic is used to ease the evaluation of the piecewise cosine functions in the power flow equations. Therefore, in optimizations, the coupling between variables is reduced. Moreover, an under voltage load shedding (UVLS) approach based on DPWLPF is presented. Case studies are conducted for benchmark systems. The results show that the DPWLPF facilitates the solution of optimal power flow (OPF) and UVLS problems than conventional piece-wise models. And DPWLPF still enhances the approximation accuracy by the decoupled piecewise modeling.

Heuristic Optimization for Microload Shedding in Generation Constrained Power Systems

While the causes of power system outages are often complex and multi-faceted, an apparent deficit in generation compared to a known demand for electricity could be more alarming. A sudden hike in demand at any given time may ultimately result in the total failure of an electricity network. In this paper, algorithms to efficiently allocate the available generation is investigated. Dynamic programming based algorithms are developed to achieve this constraint by uniquely controlling home appliances to reduce the overall demands for electricity by the consumers on the grid in context. To achieve this, heuristic optimization method (HOM) based on the consumers’ comfort and the benefits to the electricity utility is proposed. This is then validated by simulating microload management in generation constrained power systems. Three techniques; General Shedding (GS), Priority Based Shedding (PBS) and Excess Reuse Shedding (ERS) techniques were studied for effecting efficient microload shedding. The research is aimed at reducing the burden imposed on the consumers in a generation constrained power system by the traditional load shedding approach. Additionally, the reduction of the excess curtailment is a prime objective in this paper as it helps the utility companies to reduce wastage and ultimately reduce losses resulting from over shedding. Reducing the peak-to-average ratios (PAR) on the entire network in context as a critical factor in the determination of the efficiency of an electricity network is also investigated. In the long run, the PAR affects the price charged to the final consumer. Simulation results show the associated benefits that include effectiveness, deployability, and scalability of the proposed HOM to reduce these burdens.

Voltage and Frequency Recovery in an Islanded Inverter-Based Microgrid Considering Load Type and Power Factor

This paper introduces simple and complete under voltage-frequency load shedding schemes to determine proper load shedding amounts (LSAs) in an islanded inverter-based microgrids (IBMGs) considering power and power factor (PF) of various load types, such as constant power, constant current, and constant impedance loads. The proposed method employs a fast time-step simulation approach based on the complete state-space model of IBMG in order to obtain the transient and steady state responses of the system. The required power-voltage curves are obtained considering load PF and system topology. Ultimately, LSA is obtained according to the under voltage load shedding (LS) and under frequency LS values. To demonstrate the effectiveness of the proposed simple and complete LS methods, the corresponding performances are analyzed in a test islanded IBMG modeled in MATLAB. The simulation results show that unlike the other compared methods, the proposed LS approach can accurately determine less LSA while maintaining the power system stability.

A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach

Load management represents one of the main constraints when considering smart grids. In addition, load management is a significant challenge for power system security operations. The smart techniques in load management endow the system with the ability to restore its normal or stable operation after being subjected to any disturbances. When the load exceeds the generation, the system stability is affected, which leads to cascade outages and shutdown of the major parts of the power system, causing the frequency decay effect. Fast load shedding (LS) is the best way to avoid cascading outages and power system blackouts. This paper proposes an innovative, accurate, reliable and fast under-frequency load shedding (UFLS) technique based on the grasshopper optimization algorithm (GOA). LS is considered in this research as a constrained optimization problem. The objective function is to minimize the amount of load shed while maximizing the lowest swing frequency at all stages. To validate the proposed GOA-based UFLS, a comparison with adaptive, particle swarm optimization (PSO) and genetic algorithm (GA) UFLS is carried out for different disturbances. Two different case study systems are considered to test the accuracy and reliability of the proposed algorithm: the IEEE 9-bus and 39-bus systems. The proposed GOA and PSO are coded using the MATLAB environment. Different operating cases involving outage of multiple generators and increasing load are implemented to validate the proposed GOA. The DigSilent power factory software is used as a platform for simulating the power system under study when subjected to different disturbance levels. The results verify the accuracy and reliability of GOA in minimizing the amount of load shed and maximizing the lowest swing frequency while satisfying the constraints. Moreover, GOA achieves a faster solution than PSO and GA.

Corrective load shedding using fuzzy decision tree approach for real time voltage security enhancement of power system

The paper proposes a novel algorithm for optimal load shedding using fuzzy decision tree. In non-correctable emergency, the remedy is load shedding. The presented algorithm is computationally efficient and can be utilised for online voltage security enhancement. It is based on fuzzy decision tree. Due to the feature selection approach of decision trees the method is fast enough for online load shedding of power system. The scheme is based on the notion of the static voltage stability margin. The work presents the load shedding approach for all credible line outages. The result shows the fast and accurate conversion of 'insecure' cases to 'secure' cases for a credible contingency condition. The initial database is prepared by wide variations of loading conditions at all the load buses using traditional approach of continuation power flow method. The effectiveness of the proposed algorithm of load shedding is tested using IEEE-30 bus system.