Intelligent Load Shedding Research Articles

Double-Layered Droop Control-Based Frequency Restoration and Seamless Reconnection of Isolated Neighboring Microgrids for Power Sharing

This article describes a seamless reconnection topology for power sharing between distant rural community microgrids (CMGs), which is based on a double-layered droop-controlled (DLDC) frequency restoration scheme. Increased load demand, along with the intermittent nature of renewable energy sources, may result in a power deficit in isolated CMGs. In order to overcome this restriction, the connection of autonomous neighboring CMGs may be a viable alternative to intelligent load shedding. When dealing with active power fluctuation and setting a frequency set point becomes difficult in the absence of a grid frequency reference, this DLDC-based approach can resolve the issue. The DLDC adds a self-synchronized feature by parallel shifting of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$f - P$ </tex-math></inline-formula> slope to restore the operating frequency to its nominal value. The difference in frequency enables to shift the voltage axis accordingly through the change in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{d}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{q}$ </tex-math></inline-formula> reference of the terminal voltage for appropriate power sharing. The stability of the proposed controller has been analyzed by using a mathematical model considering communication delay in the distributed secondary controller. Finally, the efficacy of the proposed controller is shown via the use of unique processor-in-the-loop (PIL) experimental findings, in which OPAL-RT and PLECS RT boxes are used to build both the CMGs and a TI-based F28069M microprocessor is utilized as a controller.

Multi‐microgrid intelligent load shedding for optimal power management and coordinated control with energy storage systems

<scp>Multi‐microgrid</scp> intelligent load shedding for optimal power management and coordinated control with energy storage systems

Modeling and Optimization of a Community Microgrid Components

The modeling and optimization of a community microgrid situated in an urban area is presented in this paper. Such communities include places like housing estates, large hospital complexes, large residential complexes, and universities of higher learning. The case study used in this work is a housing estate situated in Cape Town, South Africa. Distributed energy resources used in the study are diesel generators, rooftop solar photovoltaic system, and the electrical load that is segmented into critical and non-critical type. The segmentation of the load allows an intelligent load shedding scheme in order to maintain the stability of the overall system. HOMER modeling software environment is used to model and optimize the community microgrid component sizes for technical and economic feasibility. An optional grid-connected mode as a backup energy system is evaluated against the grid-forming mode of the community microgrid system. Simulation results are obtained and discussed. Conclusion of decision-making about using a grid-forming microgrid system or grid-connected-PV is presented.

Blackout Avoidance through Intelligent Load Shedding in Modern Electrical Power Utility Network

During the last few decades many blackouts have occurred throughout the world. It seems that modern power systems are more vulnerable to major blackouts. Power system in Pakistan is no exception where blackouts affect the economy and hinder the development of the country. Pakistan Electric Power Company (PEPCO) is responsible for generation, transmission, and distribution of electric power in Pakistan. Major blackouts occur due to failure of the protection system of the power transmission network. The remedy for such collapses is disconnection of non-preferred load through Intelligent Load Shedding (ILS) technique. In this paper, the Intelligent Load Shedding is simulated in Electrical Transient Analysis Program (ETAP) software. The technique has been applied on 220kV transmission network of Quetta Electric Supply Company (QESCO), a power distribution company in Balochistan province of Pakistan. This paper focuses on preventing entire QESCO network from cascaded tripping and blackout during N-2 contingency situations. It has been established that implementation of Intelligent Load Shedding is not only helpful for protecting the transmission network of the distribution company, like QESCO, from blackout, but also protects smart grid from blackouts and other power collapses.

Blackout Avoidance through Intelligent Load Shedding in Modern Electrical Power Utility Network

During the last few decades many blackouts have occurred throughout the world. It seems that modern power systems are more vulnerable to major blackouts. Power system in Pakistan is no exception where blackouts affect the economy and hinder the development of the country. Pakistan Electric Power Company (PEPCO) is responsible for generation, transmission, and distribution of electric power in Pakistan. Major blackouts occur due to failure of the protection system of the power transmission network. The remedy for such collapses is disconnection of non-preferred load through Intelligent Load Shedding (ILS) technique. In this paper, the Intelligent Load Shedding is simulated in Electrical Transient Analysis Program (ETAP) software. The technique has been applied on 220kV transmission network of Quetta Electric Supply Company (QESCO), a power distribution company in Balochistan province of Pakistan. This paper focuses on preventing entire QESCO network from cascaded tripping and blackout during N-2 contingency situations. It has been established that implementation of Intelligent Load Shedding is not only helpful for protecting the transmission network of the distribution company, like QESCO, from blackout, but also protects smart grid from blackouts and other power collapses.

Frequency Stability for an Island Power System: Developing an Intelligent Preventive-Corrective Control Mechanism for an Offshore Location

This article develops an intelligent underfrequency security control mechanism for offshore island power systems, for which frequency stability is a major concern. The security control mechanism is divided into two main categories: preventive control and corrective control. The developed preventive?corrective control system involves modules for forecasting the frequency nadir, the rate of change of frequency, intelligent load shedding, and protection strategies. The forecasts assist in the rescheduling of diesel generators, wind power curtailment, or intelligent underfrequency load shedding (UFLS). An actual island power system is considered to elucidate the feasibility of the proposed control system. The results of this study provide system operators with a valuable reference for preventive dispatch and the planning of load shedding.

Optimal Load Shedding for Maximizing Satisfaction in an Islanded Microgrid

A microgrid (MG) is a discrete energy system that can operate either in parallel with or independently from a main power grid. It is designed to enhance reliability, carbon emission reduction, diversification of energy sources, and cost reduction. When a power fault occurs in a grid, an MG operates in an islanded manner from the grid and protects its power generations and loads from disturbance by means of intelligent load shedding. A load shedding is a control procedure that results in autonomous decrease of the power demands of loads in an MG. In this study, we propose a load shedding algorithm for the optimization problem to maximize the satisfaction of system components. The proposed algorithm preferentially assigns the power to the subdemand with a high preference to maximize the satisfaction of power consumers. In addition, the algorithm assigns the power to maximize the power sale and minimize the power surplus for satisfaction of power suppliers. To verify the performance of our algorithm, we implement a multi-agent system (MAS) on top of a conventional development framework and assess the algorithm’s adaptability, satisfaction metric, and running time.

Intelligent Under Frequency and Under Voltage Load Shedding Method Based on the Active Participation of Smart Appliances

Under frequency load shedding (UFLS) and under voltage load shedding (UVLS) are effective methods to maintain the power balance of and prevent frequency or voltage collapse of power systems. With the construction of wide area measurement systems, the development of demand response technologies and the application of smart appliances, a new direction for load shedding method emerges under the background of smart grid. In this paper, an intelligent UFLS/UVLS method based on the active participation of smart appliances is proposed. First, this paper takes refrigerators and water heaters as research objects, establishes their practical models and proposes a suitable control method for intelligent load shedding. Then an intelligent UFLS/UVLS method is proposed and simulated in IEEE 39-bus system. Simulation results prove that this strategy can work well to suppress the frequency and voltage fall or even collapse, and reduce the amount of load shedding and economic losses.

A hybrid method for optimal load shedding and improving voltage stability

Abstract In this paper, a hybrid method is proposed for reducing the amount of load shedding and voltage collapse. The hybrid method is the combination of Genetic Algorithm (GA) and Neural Network (NN). The GA is used by two stages, one is to frame the optimization model and other stage is to generate data set for developing the NN based intelligent load shedding model. The appropriate buses for load shedding are selected based on the sensitivity of minimum eigenvalue of load flow Jacobian with respect to the load shed. The proposed method is implemented in MATLAB working platform and the performance is tested with 6 bus and IEEE 14 bus bench mark system. The result of the proposed hybrid method is compared with the GA based optimization algorithm. The comparison shows that, the proposed method ensures voltage stability with minimum loading shedding.

Optimal Load Shedding Strategy for Selçuk University Power System with Distributed Generation

Traditionally under frequency relays and PLCs (programmable logic controller) are used for load shedding. Recently, these methods have been combined with smart power management systems to shed load automatically. These combined systems are the best methods. However, shedding exact amount of load is almost impossible, because it usually ends up with excessive or inadequate load shedding at feeders where it becomes necessary to sustain system stability. Disconnecting a certain amount of loads at a feeder is defined as load shedding. In case of emergency, faster and optimal load relief can be obtained with an intelligent load shedding system. This paper demonstrates an intelligent load shedding strategy in electrical system of Selçuk University Medical Faculty consisting different type and size of loads and being supplied by a distributed generator. Generators which supply with Selçuk University Medical Faculty can’t meet energy requirement when there is a disturbance in power system. In case of 1 MW Solar power plant to be building at University Campus supply to Medical Faculty, the difference between power generation and demand will decrease. In this case, load shedding becomes necessary to improve reliability of power supply and sustain system stability. Loads are sorted by importance priority and optimal load shedding method is applied. The fuzzy logic is employed for optimal load shedding solution. Strategy is applied on Medical Faculty loads which have different importance level.

New design of intelligent load shedding algorithm based on critical line overloads to reduce network cascading failure risks

This paper presents a new algorithm for intelligent load shedding based on critical line overloads. This method can increase the efficiency for determining critical lines and sensitive loads. Hence, when critical lines expose an overload, the system will run an intelligent load shedding, which considerably curtails the sensitive loads of critical transmission lines. This can fully reduce the harmful risks of power system cascading failures that impose extensive losses to the economy of a country. For testing the accuracy and applicability of this technique, the IEEE 39-bus test system is applied as a standard case study.

The Existing Investigation and Prospect of Under-Frequency and Under-Voltage Load Shedding in Power Systems

Under-frequency load shedding (UFLS) and under-voltage load shedding (UVLS) as the last defense of the power system to maintain its stability are of great significance, especially for the current development of large-scale interconnected power system. At first, this paper presents the existing methods of load shedding and analyses their drawbacks. Then, a brief overview of the application of wide area measurement system (WAMS) in UFLS and UVLS is provided. Finally, a novel intelligent load shedding scheme which realizes load adjustment instead of load shedding based on the characteristics of smart grid and smart home is proposed.

Intelligent Load Shedding Using TCP/IP for Smart Grids

Computerized power management system with fast and optimal communication network overcomes all major discrepancies of undue or inadequate load relief that were present in old conventional systems. This paper presents the basic perception and methodology of modern and true intelligent load shedding scheme in micro grids topology by employing TCP/IP protocol for fast and intelligent switching. The network understudy performs load management and power distribution intelligently in a unified network. Generated power is efficiently distributed among local loads through fast communication system of server in the form of source and clients in the form of loads through TCP/IP. The efficient use of information between server and clients enables to astutely control the load shedding in a power system of micro grids system. The processing time of above stated system comes out to be 10 ms faster than others which ensure very less delay as compared to conventional methods. The Micro Grids system operating through TCP/IP control has been implemented in MATLAB/SIMULINK and results have been verified.

Configuring Trees of Classifiers in Distributed Multimedia Stream Mining Systems

Multimedia stream mining applications require the identification of several different attributes in data content, and hence rely on a set of cascaded statistical classifiers to filter and process the data dynamically. In this paper, we introduce a novel methodology for configuring such cascaded classifier topologies, specifically binary classifier trees, in resource-constrained, distributed stream mining systems. Instead of traditional load shedding, our approach configures classifiers with optimized operating points after jointly considering the misclassification cost of each end-to-end class of interest in the tree, the resource constraints for every classifier, and the confidence level of each data object that is classified. The proposed approach allows for both intelligent load shedding as well as data replication based on available resources dynamically. We evaluate the algorithm on a sports video concept detection application and identify huge cost savings over load shedding alone. Additionally, we propose several distributed algorithms that enable each classifier in the tree to reconfigure itself based on local information exchange. We analyze the associated tradeoffs between convergence time, information overhead, and the cost efficiency of results achieved by each classifier for each of these algorithms.

Intelligent Load Shedding

This article demonstrates the need for a modern load-shedding system and introduces the new technology of intelligent load shedding (ILS) that goes beyond a contingency-based load-shedding scheme. A case study of the application of an ILS scheme in a large industrial facility is provided.

Voltage Stability Control of Electrical Network Using Intelligent Load Shedding Strategy Based on Fuzzy Logic

As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.

Resource Constrained Stream Mining With Classifier Tree Topologies

Stream mining applications require the identification of several different attributes in data content and hence rely on a distributed set of cascaded statistical classifiers to filter and process the data dynamically. In this letter, we introduce a novel methodology for configuring cascaded classifier topologies, specifically binary classifier trees, with optimized operating points after jointly considering the misclassification cost of each end-to-end class of interest in the tree, the resource constraints for every classifier, and the confidence level of each data object that is classified. By configuring multiple operating points per classifier, we enable not only intelligent load shedding when resources are scarce but also intelligent replication of low confidence data across multiple edges when excess resources are available. Using a classifier tree constructed from support vector machine-based sports image classifiers, we verify huge cost savings and discuss how different classifier placements and costs can influence the gains obtained by various algorithms.

Using artificial neural networks for load shedding to alleviate overloaded lines

Previous work by the authors (see Proc. First Internat. Forum on Appls. of Neural Nets to Power Systs., Seattle, p.205-9, 1991) has shown the viability of using artificial neural networks (ANNs) for the early detection and control of overloaded lines. This paper focuses on the development of an artificial neural network based scheme for intelligent load shedding. The load shedding scheme consists of localized detectors that consider parameters of the power system during an emergency. The research was developed using the IEEE 30 bus test system which incorporates a design of net import and export regions. The approach is implemented in the import area of the system. The purpose of the scheme is to detect overloaded lines and make intelligent decisions about where within the topology of the system the load should be dropped and how much load to shed. The proposed scheme is designed to avoid unintentional separation of the system by fast, proactive, and adaptive control.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>