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.

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.

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 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.

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.

Vulnerability Assessment of Distributed Load Shedding Algorithm for Active Distribution Power System Under Denial of Service Attack

In order to deal with frequency deviation andsupply-demand imbalance in active distribution power system, inthis paper a distributed under frequency load shedding (UFLS)strategy is proposed. Different from conventional centralizedUFLS schemes, no centralized master station gathering all thebuses’ information is required. Instead, each bus decides itsown load shedding amount by only relying on limited peer-topeer communication. However, such UFLS strategy may sufferfrom some unexpected cyber-attacks such as integrity attacksand denial of service (DoS) attack. The latter DoS attack aimsto degrade the system performance by jamming or breakingthe communication, which is of high probability to happen inpractical power system. To assess the vulnerability of proposeddistributed UFLS algorithm, the effect of DoS attack on distributed average consensus algorithm is theoretically derived,which indicates that the final consensus value can be estimatedby a given attack probability. It is also investigated that such DoSattack does harm to the load shedding amount and finally affectsthe system frequency performance in the active distributionpower system. Several case studies implemented on an IEEE33-bus active distribution power system are conducted to verifythe effectiveness of the theoretical findings and investigate thevulnerability of the considered power system.

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.

Cold dwell behaviour of Ti6Al alloy:Understanding load shedding using digital image correlation and dislocation based crystal plasticity simulations

Digital image correlation(DIC)and dislocation based crystal plasticity simulation were utilised to study cold dwell behaviour in a coarse grain Ti-6Al alloy at 3 different temperatures up to 230℃.Strains extracted from large volume grains were measured during creep by DIC and were used to calibrate the crystal plasticity model.The values of critical resolved shear stresses(CRSS)of the two main slip systems(basal and prismatic)were determined as a function of temperature.Stress along paths across the boundaries of four grain pairs,three“rogue”grain pairs and one“non-rogue”grain pair,were determined at different temperatures.Large load shedding was observed in one of the“rogue”grain pairs,where a stress increment during the creep period was found in the“hard”grain.A minor load shedding mechanism was observed in two non-typical“rogue”grain pairs,in which the plastic deformation is nonuniform inside the grains and geometrically necessary dislocations accumulate in the centre of the grains.At elevated temperatures,120℃was found to be the worst case scenario as the stress difference at the grain boundaries of these four grain pairs was found to be the largest among the three temperatures analysed.The origin of this critical temperature is debated in the literature and it is investigated for the first time in the present work by analysing the simultaneous effects of the geometrically necessary dislocations(GND)and the strain rate sensitivity(SRS)of the slip systems.The analysis shows that the combined effects of the peak SRS of both prismatic and basal slip systems at 80℃and of the increase of the spread of the GND distribution around the grain boundary at higher temperatures are the origin of the observed worst case scenario.

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.

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 hi^h accuracy.Then,the MINLP problem can he 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 trade off between approximation accuracy and computational efficiency,this paper proposes a model called 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 much better than conventional piecewise models.And DPWIJM^still enhances the approximation accuracy by usinj»the decoupled piecewise modeling.

Evolution of Sedimentation in a Headrace Canal for Hydroelectric Production Case of the Shongo Basin of the Inga Complex from February 2020 to May 2021 (Kongo Central Province/DR Congo)

The headrace of the Inga hydropower complex is experiencing siltation problems, reducing the exploitable draft and limiting the production capacity of the two main Inga hydropower plants during the low water period. During the 2019 low water period, several sediment slumps occurred in the Shongo basin, disrupting the production of hydroelectric power generated by the Inga 1 & 2 power plant, resulting in massive load shedding of power supply to downstream customers. The cardinal aim of this study is to determine the quantities of sediments deposited and those eroded, in order to know the evolution of sedimentation in the Shongo basin from February 2020 to May 2021. The results obtained show that the running index of the generating units is determinant and influences the sedimentation process in the Shongo basin. The cleaning of the Shongo basin in terms of the spatial distribution of sedimentation from February 2020 to May 2021 is plausible.

Role of Microgrids in the Smart Grid

Microgrids are local power systems that may or may not be connected to the distribution system and are typically controlled by the local operator.Interest in microgrids is rising and it is likely that the number of microgrids connected to distribution networks will increase.Currently,there is no consensus on how microgrids will interact with the distribution system―they have the potential to threaten stability,or to assist.However microgrids,with their emphasis on sophisticated control in order to manage their particular challenges,address many of the problems that will be required to overcome in realizing the smart grid.This paper examines some of the issues involved in connecting microgrids to the distribution networks,and illustrates how microgrids have a key role to play in the development of the smart grid.

Real-Time Operation of Microgrids

Microgrid (MG) systems effectively integrate a generation mix of solar, wind, and other renewable energy resources. The intermittent nature of renewable resources and the unpredictable weather conditions contribute largely to the unreliability of microgrid real-time operation. This paper investigates the behavior of microgrid for different intermittent scenarios of photovoltaic generation in real-time. Reactive power coordination control and load shedding mechanisms are used for reliable operation and are implemented using OPAL-RT simulator integrated with Matlab. In an islanded MG, load shedding can be an effective mechanism to maintain generation-load balance. The microgrid of the German Jordanian University (GJU) is used for illustration. The results show that reactive power coordination control not only stabilizes the MG operation in real-time but also reduces power losses on transmission lines. The results also show that the power losses at some substations are reduced by a range of 6% - 9.8%.