Determination of Effective Load Shedding Schemes in Electric Power Plants

The ability of power system to survive the transition from preloading state to the gradual increase in load and thereafter reach an acceptable operational condition is an indication of transient stability of the system. The study analyzed load shedding scheme through the use of empirical measurement tools and load-flow simulation techniques. It was geared towards determining effective load shedding strategies to reduce unnecessary overload in order to achieve dynamic stability of the electric power network in the Export Free Trade Zone, Calabar, Nigeria. From the tests and the measurements taken, it was observed that the real and reactive powers from the generator and the mechanical power from the turbine engine were stable when the load shedding controller was switched on, as compared to when it was off. The engine speed, the bus-bar frequency and the output voltage of the generator stabilized within a shorter time (about 8 seconds) when the controller was switched on than when it was on the off condition. Also, there were noticeable fluctuations in the speed of the remaining two generators. It became stable at about 12 seconds after the loss. The variations were 0.3 per cent of the nominal speed value. The excitation voltage fluctuated from 1.2 (pu) to 4.5 (pu) when the bus voltage dipped as a result of additional load. It then came down and stabilized at 1.8 (pu) after few swings. This confirmed that the stability of power system is much enhanced when load shedding controllers are effectively configured on the network.

Optimal integration of solar home systems and appliance scheduling for residential homes under severe national load shedding

In developing countries like South Africa,users experienced more than 1030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid.Residential homes that cannot afford to take actions to mitigate the challenges of load shedding are severely inconvenienced as they have to reschedule their demand involuntarily.This study presents optimal strategies to guide households in determining suitable scheduling and sizing solutions for solar home systems to mitigate the inconvenience experienced by residents due to load shedding.To start with,we predict the load shedding stages that are used as input for the optimal strategies by using the K-Nearest Neighbour(KNN)algorithm.Based on an accurate forecast of the future load shedding patterns,we formulate the residents’inconvenience and the loss of power supply probability during load shedding as the objective function.When solving the multi-objective optimisation problem,four different strategies to fight against load shedding are identified,namely(1)optimal home appliance scheduling(HAS)under load shedding;(2)optimal HAS supported by solar panels;(3)optimal HAS supported by batteries,and(4)optimal HAS supported by the solar home system with both solar panels and batteries.Among these strategies,appliance scheduling with an optimally sized 9.6 kWh battery and a 2.74 kWp panel array of five 550 Wp panels,eliminates the loss of power supply probability and reduces the inconvenience by 92%when tested under the South African load shedding cases in 2023.

Energy Efficiency in Periods of Load Shedding and Detrimental Effects of Energy Dependence in the City of Maroua, Cameroon

During the years 2021 and 2022, the city of Maroua experienced repeated power blackouts. However, this locality has significant photovoltaic energy potential. Nevertheless, the evaluation of the electrical performance showed the dependence of the population on these fluctuations, which could be bypassed or suppressed. In most cases, the blackout occurs during high energy demand. In this paper, a method for evaluating electrical efficiency is proposed and its credibility has been demonstrated on the one hand, and on the other hand, a renewable energy production system is proposed. The Homer software has made possible the analysis of the proposed system and its impact on the environment has also been carried out. The techno-economic study of the system has proved that a solar photovoltaic farm associated with an energy storage system, with a capacity of 47 MW, can meet the energy demand of the town of Maroua. This alternative is profitable for this locality which lives in a precarious situation and a continuous need.

Smart Meters and Under-Frequency Load Shedding

In some countries, there exists a risk of power deficit in the EPS （electrical power system）. This is a very serious problem and there are various solutions to deal with it. A power deficit in the EPS leads to frequency decrease in the power system. A dedicated automation to load shedding is used to maintain proper EPS operation. For some time, it has applied a mechanism called demand-side response, which in case of an emergency situation allows for a ＂more civilized＂ rationing of electricity to customers, with their consent. Such programs require that the utilities pay the customers for their agreement. The author proposes a new solution, intermediate between strict ALS （acting relieving automation） and demand-side response programs, where the companies have to send information about the price of energy or control signals to households.

Identification of Critical Lines in Power System Based on Optimal Load Shedding

Based on risk theory, considering the probability of an accident and the severity of the sequence, combining N-1 and N-2 security check, this paper puts forward a new risk index, which uses the amount of optimal load shedding as the severity of an accident consequence to identify the critical lines in power system. Taking IEEE24-RTS as an example, the simulation results verify the correctness and effectiveness of the proposed index.

Load Shedding Application within a Microgrid to Assure Its Dynamic Performance during Its Transition to the Islanded Mode of Operation

This article presents the simulation results and analysis related to the response of the generators within a microgrid towards an accidental overload condition that will require some load shedding action. A microgrid overload can occur due to various reasons ranging from poor load schedule, inadequate switching of circuits within the microgrid, outage of one or more generators inside the microgrid, illegal load connections by some low voltage consumers, etc. It was observed that among the main factors that determine the survival of the microgrid during its transition from the grid connected mode to the islanded mode of operation are the size and type of the load connected (passive or dynamic load) as well as the length of time during which the unexpected load is connected. Models of a speed and voltage regulators of a diesel generator, and important for coping with the overload conditions are provided in the paper. The novelty of the work lies in the load shedding simulation and analysis of the specific generators studied herein, regarding that in many countries the microgrid technology is seen as an important alternative towards the ever increasing load demand and also to assist the system during periods of blackout.

Load Shedding Strategy Based on Combined Feed-Forward Plus Feedback Control over Data Streams

In data stream management systems (DSMSs), how to maintain the quality of queries is a difficult problem because both the processing cost and data arrival rates are highly unpredictable. When the system is overloaded, quality degrades significantly and thus load shedding becomes necessary. Unlike processing overloading in the general way which is only by a feedback control (FB) loop to obtain a good and stable performance over data streams, a feedback plus feed-forward control (FFC) strategy is introduced in DSMSs, which have a good quality of service (QoS) in the aspects of miss ratio and processing delay. In this paper, a quality adaptation framework is proposed, in which the control-theory-based techniques are leveraged to adjust the application behavior with the considerations of the current system status. Compared to previous solutions, the FFC strategy achieves a good quality with a waste of fewer resources.

Regional Coordination for under Frequency Load Shedding

Frequency deviation can be used as an indicator of imbalance between supply and demand. When generation is insufficient, it can cause frequency decline in a power system operation. Implementing under frequency load shedding (UFLS) is one of the common methods to overcome this problem. This paper proposes a novel approach for adaptive load shedding. The concept is an extension of shared and targeted load shedding using reserve margin. The optimal system configuration is then selected from those candidates to fulfill operational objectives. Operational constraints related to system parameters, threshold frequency, total of load shed and control area including line capacity are considered. An example using four sub-areas connected to an external system shows that the proposed regional coordination as an adaptive UFLS is feasible.

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.

Multi Objective Load Shedding Framework

In this paper, a multi-objective load shedding framework on the power system is presented. The frame work is useable in any kind of smart power systems;the word of smart here refers to the availability of data transmission infrastructure (like PLC or power line carrier) in the system, in order to carry the system data to the load shedding framework. This is an open framework that means it can optimize load shedding problem by considering unlimited number of objective functions, in other word, the number of objectives can be as much as the operator decides, finally in the end of frame work just one matrix breaker state is chosen in a way of having the most compatibility with the operator ideas which are determined by objectives importance percentage which are one input groups of the framework. A two-stage methodology is used for the optimal load shedding problem. In the first stage, Discrete Multi-objective Particle Swarm Optimization method is used to find a collection of the best states of load shedding (Pareto front). In the second stage, the fuzzy logic is used as a Pareto front inference engine. Fuzzy selection algorithm (FSA) is designed in a way that it can infer according to the operator’s opinion without the expert interference that means rule base is formed automatically by fuzzy algorithm. FSA is consisted of two parts. Membership functions and rules base are formed automatically in the first part, the former in accordance with the costs of Pareto front particles and the latter in correspondence with importance percentage of objectives which are entered to FSA by operator;in other word, decision matrix is formed automatically in the algorithm according to the cost of Pareto front particles and importance percentage of objectives. In the Second part, Mamdani inference engine scrutinizes the Pareto front particles by the use of formed membership functions and rules base to know if they are compatible to operator’s opinion or not. Getting this approach, cost functions of each particle are considered as the inputs of (FSA), then a fuzzy combined fitness (FCF) is allocated to each Pareto front particle by Mamdani inference engine. In other word, FCF shows how much the particle is compatible to the operator’s opinion. Finding minimum FCF, final inference is done. The proposed method is tested on 30-bus, and 118-bus IEEE systems by considering two or three objective functions and the results are presented.

Optimum Load Shedding in Power System Strategies with Voltage Stability Indicators

An optimal load shedding strategy for power systems with optimum location and quantity of load to be shed is presented in this paper. The problem of load shedding for avoiding the existence of voltage instability in power systems is taken as a remedial action during emergency state in transmission and distribution sector.Optimum location of loads to be shed is found together with their optimum required quantity. L-Indicator index is in used for this purpose with a modified new technique. Applications to be standard 6 bus Ward-Hale test system and IEEE – 14 bus system are presented to validate the applicability of the proposed technique to any system of any size.

Utilizing Stability Index Tracing for Precise Load Buses Identification in Load Shedding Problem

This paper proposes a new approach for suitable load buses identification via stability index tracing in performing corrective load shedding. The proposed identification technique is called the Fast Voltage Stability Index Load Tracing (FVSI-LT). By implementing a power tracing algorithm, a group of major contributors on the stress experienced by a power system is able to be precisely identified by a system operator (SO) based on the traced values of FVSI. To be precise, the traced FVSI via FVSI-LT can be used to form a ranking list indicating the priority of buses committed for shedding purpose. After designing a Fuzzy Inference System (FIS) for deciding the allowable load powers to be shed and performing experiment on IEEE 57-Bus reliability test system (RTS), it is revealed that the ranking list provided by FVSI-LT results to the most consistent improvement in terms of voltage stability and losses minimization.

Load Profile Analysis for Mitigating Load-Shedding in Central Africa: Case of Kinshasa

Load shedding is a major problem in Central Africa, with negative consequences for both society and the economy. However, load profile analysis can help to alleviate this problem by providing valuable information about consumer demand. This information can be used by power utilities to forecast and reduce power cuts effectively. In this study, the direct method was used to create load profiles for residential feeders in Kinshasa. The results showed that load shedding on weekends results in significant financial losses and changes in people’s behavior. In November 2022 alone, load shedding was responsible for $ 23,4 08,984 and $ 2 80,9 07,808 for all year in losses. The study also found that the SAIDI index for the southern direction of the Kinshasa distribution network was 122.49 hours per feeder, on average. This means that each feeder experienced an average of 5 days of load shedding in November 2022. The SAIFI index was 20 interruptions per feeder, on average, and the CAIDI index was 6 hours, on average, before power was restored. This study also proposes ten strategies for the reduction of load shedding in the Kinshasa and central Africa power distribution network and for the improvement of its reliability, namely: Improved load forecasting, Improvement of the grid infrastructure, Scheduling of load shedding, Demand management programs, Energy efficiency initiatives, Distributed Generation, Automation and Monitoring of the Grid, Education and engagement of the consumer, Policy and regulatory assistance, and Updated load profile analysis.

Adaptive Under-Frequency Load Shedding

Under-frequency load shedding （UFLS） is used in the power industry to rescue systems facing extreme disturbances to avoid system collapse. Traditionally, many computations are repeated to seek the proper power system settings such that the UFLS provides the desired good performance for selected scenarios. An adaptive UFLS method based on the genetic algorithm was developed to automate the finding of optimal parameters to minimize the repetitive trial-error calculations. Simulations demonstrate that the method has better performance than previous schemes and reduces the time and effort of the repetitive simulations.

Load Shedding for Window Joins over Streams

We address several load shedding techniques over sliding window joins. We first construct a dual window architectural model including aux-windows and join-windows, and build statistics on aux-windows. With the statistics, we develop an effective load shedding strategy producing maximum subset join outputs. In order to accelerate the load shedding process, binary indexed trees have been utilized to reduce the cost on shedding evaluation. When streams have high arrival rates, we propose an approach incorporating front-shedding and rear-shedding, and find an optimal trade-off between them. As for the scenarios of variable speed ratio, we develop a plan reallocating CPU resources and dynamically resizing the windows. In addition, we prove that load shedding is not affected during the process of reallocation. Both synthetic and real data are used in our experiments, and the results show the promise of our strategies.

Load Shedding Control Strategy in Power Grid Emergency State Based on Deep Reinforcement Learning

In viewing the power grid for large-scale new energy integration and power electrification of power grid equipment,the impact of power system faults is increased,and the ability of anti-disturbance is decreased,which makes the power system fault clearance more dificult.In this paper,a load shedding control strategy based on artificial intelligence is proposed,this action strategy of load shedding,which is selected by deep reinforcement learning,can support autonomous voltage control.First,the power system operation data is used as the basic data to construct the network training dataset,and then a novel reward function for voltage is established.This value function,which conforms to the power grid operation characteristics,will act as the reward value for deep reinforcement learning,and the Deep Deterministic Policy Gradient algorithm(DDPG)algorithm,with the continuous action strategy,will be adopted.Finally,the deep reinforcement learning network is continuously trained,and the load shedding strategy concerning the grid voltage control problem will be obtained in the power system emergency control situation,and this strategy action is input into the Pypower module for simulation verification,thereby realizing the joint drive of data and model.According to the numerical simulation analysis,it shows that this method can effectively determine the accurate action selection of load shedding,and improve the stable operational ability of the power system.

Load shedding strategy coordinated with storage device and D-STATCOM to enhance the microgrid stability

Recently microgrids have drawn a potential attraction by fulfilling the environmental demands and the increasing energy demands of the end-users. It is necessary to focus on various protection and control aspects of a microgrid. During the transition between the grid-following and grid-forming modes, the voltage and the frequency instability due to the power mismatch condition becomes the major point of concern. Therefore, the paper executes a frequency-active power and voltage-reactive power drooping control strategy for the precise power-sharing among the distributed power generators. Furthermore, to handle the power deficit scenarios and to maintain the system stability, a system independent and priority-based adaptive three-stage load shedding strategy is proposed. The sensitivity of the strategy depends on the system inertia and is computed according to the varying absolute rate-of-change-of-frequency. The strategy incorporates the operation of battery storage system and distributed static compensator (D-STATCOM) in the microgrid, to provide a reliable power supply to the customers for a considerable time instead of a sudden load shedding. The effectiveness of the proposed strategies is investigated on a scaled-down modified IEEE 13-bus microgrid system on the podium of MATLAB 2015b through the time-domain simulation.

Load Shedding and Restoration for Intentional Island with Renewable Distributed Generation

Due to the high penetration of renewable distributed generation(RDG),many issues have become conspicuous during the intentional island operation such as the power mismatch of load shedding during the transition process and the power imbalance during the restoration process.In this paper,a phase measurement unit(PMU)based online load shedding strategy and a conservation voltage reduction(CVR)based multi-period restoration strategy are proposed for the intentional island with RDG.The proposed load shedding strategy,which is driven by the blackout event,consists of the load shedding optimization and correction table.Before the occurrence of the large-scale blackout,the load shedding optimization is solved periodically to obtain the optimal load shedding plan,which meets the dynamic and steady constraints.When the blackout occurs,the correction table updated in real time based on the PMU data is used to modify the load shedding plan to eliminate the power mismatch caused by the fluctuation of RDG.After the system transits to the intentional island seamlessly,multi-period restoration plans are generated to optimize the restoration performance while maintaining power balance until the main grid is repaired.Besides,CVR technology is implemented to restore more loads by regulating load demand.The proposed load shedding optimization and restoration optimization are linearized to mixed-integer quadratic constraint programming(MIQCP)models.The effectiveness of the proposed strategies is verified with the modified IEEE 33-node system on the real-time digital simulation(RTDS)platform.

Hierarchical under frequency load shedding scheme for inter-connected power systems

Severe disturbances in a power network can cause the system frequency to exceed the safe operating range.As the last defensive line for system emergency control,under frequency load shedding(UFLS)is an important method for preventing a wide range of frequency excursions.This paper proposes a hierarchical UFLS scheme of“centralized real-time decision-making and decentralized real-time control”for inter-connected systems.The centralized decision-layer of the scheme takes into account the importance of the load based on the equivalent transformation of kinetic energy(KE)and potential energy(PE)in the transient energy function(TEF),while the load PE is used to determine the load shedding amount(LSA)allocation in different loads after faults in real-time.At the same time,the influence of inertia loss is considered in the calculation of unbalanced power,and the decentralized control center is used to implement the one-stage UFLS process to compensate for the unbalanced power.Simulations are carried out on the modified New England 10-generator 39-bus system and 197-bus system in China to verify the performance of the proposed scheme.The results show that,compared with other LSA allocation indicators,the proposed alloca-tion indicators can achieve better fnadir and td.At the same time,compared with other multi-stage UFLS schemes,the proposed scheme can obtain the maximum fnadir with a smaller LSA in scenarios with high renewable energy sources(RES)penetration.

Load shedding scheme for an interconnected hydro-thermal hybrid system with SMES

The frequency of based on the load pattern the power system varies of the consumers. With continuous increase in the load, the frequency of the system keeps decreasing and may reach its minimum allowable limits. Further increase in the load will result in more frequency drop leading to the need of load shedding, if excess generation is not available to cater the need. This paper proposed a methodology in a hybrid thermal-hydro system for finding the required amount of load to be shed for setting the frequency of the system within its minimum allowable limits. The load shedding steps were obtained based on the rate of change of frequency with the increase in the load in both areas. The impact of superconducting magnetic energy storage （SMES） was obtained on load shedding scheme. The comparison of the results was presented on the two-area system.