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With the rapid development of distribution networks and increasing demand for electricity, the pressure of power supply for medium- and low-voltage distribution networks (M&LVDNs) is increasingly significant, especially considering the large scale of customers at the low-voltage (LV) level. In this paper, an outage sequence optimization method for low-voltage distribution networks (LVDNs) that considers the importance of users is proposed. The method aims to develop an optimal outage sequence strategy for LV customers in case of medium-voltage (MV) failure events. First, a multi-dimensional importance indicator system for LV users is constructed, and the customers are ranked using a modified Analytic Hierarchy Process–Entropy Weight (AHP-EW) method to determine their priorities during outages. Then, an elastic net regression-based method is used to identify the topology of the LV network. Finally, an outage sequence optimization model based on the user importance is proposed to reduce the load-shedding level. Extensive case studies are conducted in the modified LV distribution network. The results show that the proposed method results in fewer outage losses throughout the restoration periods than traditional methods and effectively improves the reliability of the power supply to LV users. [ABSTRACT FROM AUTHOR]

In large buildings, effective load shedding and shifting and providing the maximum power through solar renewable sources remain challenges because of users' unpredictable load consumption. Conventionally, load shifting, load shedding, and load covering are majorly dependent on user inputs. The lack of user interest in participating in demand responses for effective load shifting and covering remains a problem. Effective load covering through renewables and user-friendly load shedding and shifting with maximized user participation are challenging and demand high-resolution user load consumption information, which are not possible without sophisticated communication and digital twins. In this research work, a novel fuzzy-logic-based cascaded decentralized load-controlling mechanism has been developed that manages the residential building load through load-shifting, load-covering, and load-shedding schemes without any communication protocols and digitization between residential units. The decentralized controller aims to effectively utilize the centralized resources of power generation with the effective automated participation of users. The quantification of the load shifting, covering, and shedding performed during peak hours was well covered under the load-covering scheme, and the results showed that flexibility capacities of 1617 kW were achieved for load covering, 294 kW for load shedding, and 166.34 kW through shifting. A total load of 60 kW, which was reduced during shedding and shifting, was well covered during load covering through renewables. [ABSTRACT FROM AUTHOR]

Modern power systems are growing in complexity due to the installation of large generators, long transmission lines, the addition of inertialess renewable energy resources (RESs) with zero inertia, etc., which can all severely degrade the system frequency stability. This can lead to under-/over-frequency load shedding, damage to turbine blades, and affect frequency-sensitive loads. In this study, we propose a methodology to improve the two critical frequency stability indices, i.e., the frequency nadir and the rate of change of frequency (RoCoF), by formulating an optimization problem. The size and placement location of battery energy storage systems (BESSs) are considered to be the constraints for the proposed optimization problem. Thereafter, the optimization problem is solved using the three metaheuristic optimization algorithms: the particle swarm optimization, firefly, and bat algorithm. The best performing algorithm is then selected to find the optimal sizing and placement location of the BESSs. The analyses are all performed on the IEEE 9-bus and IEEE 39-bus test systems. Several scenarios which consider multiple generator outages, increased/decreased loading conditions, and the addition of RESs are also considered for both test systems in this study. The obtained results show that under all scenarios, the proposed method can enhance system frequency compared to the existing method and without BESSs. The proposed method can be easily upscaled for a larger electrical network for obtaining the optimized BESS size and location for the improvement of the system frequency stability. [ABSTRACT FROM AUTHOR]

There is currently a rising interest in reusing and repurposing offshore facilities through decommissioning; however, major challenges arise, such as size, weight, sea depth, planned use, and location. This article aims to discuss the philosophy that needs to be adopted for field redevelopment, particularly when existing platforms must be preserved and integrated into new greenfield facilities. The article also discusses the concept of weight shedding during the decommissioning of offshore facilities to either extend the life of existing platforms or provide clear space for new equipment to be installed by removing unnecessary components and structures. The above aspects of decommissioning are investigated through the redevelopment of a case study of a mature offshore oil field located in shallow water. The study indicated that weight shedding presents a favourable method for decommissioning offshore installations and can effectively lower expenses, minimise environmental consequences, and optimise the use of resources. [ABSTRACT FROM AUTHOR]

Electric power generation is quickly transitioning toward nontraditional inverter-based resources (IBRs). Prevalent devices today are solar PV, wind generators, and battery energy storage systems (BESS) based on electrochemical packs. These IBRs are interconnected throughout the power system via power electronics inverter bridges, which have sophisticated controls. This paper studies the impacts and benefits resulting from the integration of grid forming (GFM) inverters and energy storage on the stability of power systems via replicating real events of loss of generation units that resulted in large load shedding events. First, the authors tuned the power system dynamic model in Power System Simulator for Engineering (PSSE) to replicate the event records and, upon integrating the IBRs, analyzed the system dynamic responses of the BESS. This was conducted for both GFM and grid following (GFL) modes. Additionally, models for Grid Forming Static Synchronous Compensator (GFM STATCOM), were also created and simulated to allow for quantifying the benefits of this technology and a techno-economic analysis compared with GFM BESSs. The results presented in this paper demonstrate the need for industry standardization in the application of GFM inverters to unleash their benefits to the bulk electric grid. The results also demonstrate that the GFM STATCOM is a very capable system that can augment the bulk system inertia, effectively reducing the occurrence of load shedding events. [ABSTRACT FROM AUTHOR]

To achieve an energy sector independent from fossil fuels, a significant increase in the penetration of variable renewable energy sources, such as solar and wind power, is imperative. However, these sources lack the inertia provided by conventional thermo-electric power stations, which is essential for maintaining grid frequency stability. In this study, a grid resembling Madeira Island's power generation mix was modeled using the Matlab/Simulink platform. The model included solar, wind, hydro, and thermo-electric generation to accurately represent the energy landscape of Madeira Island. Three scenarios were examined: one reflecting the current power generation on Madeira Island, a future scenario with a substantial rise in the percentage of photovoltaic (PV) generation, and the same future scenario but incorporating a battery energy storage system (BESS). Various analyses were conducted to assess the impact on frequency stability during a ground fault and rapid load/generation changes. In the future scenario without a BESS, the thermoelectric power plant generator desynchronized, leading to system collapse in several simulations. However, with the addition of a BESS, a significant improvement in frequency stability was observed. The thermoelectric power plant generator could return to a steady state after each disturbance. Furthermore, both the maximum frequency deviation and the absolute value of the Rate of Change of Frequency (ROCOF) were reduced, indicating enhanced system performance and stability. [ABSTRACT FROM AUTHOR]

This article addresses a comprehensive analysis of power electrical systems, employing a combined approach of genetic algorithms and mathematical optimization through nonlinear programming with discontinuous derivatives (DNLP) in GAMS. The primary objective is to minimize economic losses and associated costs faced by the network operator following disruptive events. The analysis is divided into two fundamental aspects. Firstly, it addresses the topological reconfiguration of the network, involving the addition of lines and distributed energy resources such as distributed generation. To determine the optimal topological reconfiguration, a genetic algorithm was developed and implemented. This approach aims to restore electrical service to the maximum load within the system. Secondly, an optimal energy dispatch was performed for each generator, considering the variation in load throughout the day. The system's load curve is taken into account to determine the optimal energy distribution. Thus, the problem of economic losses is approached from two perspectives: the minimization of costs due to nonsupplied electrical energy and the determination of efficient energy dispatch for each generator after network reconfiguration. For the analysis and case studies, simulations were conducted on the IEEE 9- and 30-node test systems. The results demonstrate the effectiveness of the proposed solution, evaluated in terms of reduced load shedding and economic losses. [ABSTRACT FROM AUTHOR]

A power shortage is a common case prevailing in today's power scenario. Load shedding occurs when the demand power is greater than the generation power; then, the excessive load is cut to avoid power shortage. Usually, load shedding will make use of complex circuitry and systems along with expensive materials. This necessitates the need for a simple and efficient solution that meets all the requirements. The intelligent system is created with the help of microcontrollers achieving real-time load shedding. The power limit in the system is obtained from the utility company. The measured value in the system is obtained from the sensor and the value is compared to the power limit. If it is within the limit, no action is taken. When the limit exceeds the calculated value, the power supply is cut off. Graded load shedding is achieved through the above-mentioned method. Through this graded load shedding method, the need for changing the existing infrastructure is removed and the existing system is made useful for a longer period of time. As this proposed design uses the simplest of components and technologies, the financial and technical capital that is required to make this is lower when compared to the existing technologies. [ABSTRACT FROM AUTHOR]

Active islanding detection techniques majorly affect power quality due to injected harmonic signals, whereas passive methods have a large non-detection zone (NDZ). This article presents a new method based on the resultant sequential impedance component (RSIC) as a new approach to island detection with zero NDZs. The abrupt variable in the conventional impedance approach was replaced by the RSIC of the inverter in this method. When the measured value exceeds the threshold range, islanding is detected by monitoring the variations in the RSIC at the point of common coupling (PCC). For proper power utilization in the identified islands, a priority-based load-shedding strategy is also recommended and implemented in this article. Its efficacy was verified in a wide range of real-world settings. It offers superior stability in various non-islanding (NIS) scenarios to prevent accidental tripping. The proposed method advantages include a cheap cost, the simplicity of implementation, independence from the number and type of distributed generation (DG) units connected, and no power quality effects. Compared to other methods reported in the literature, the obtained detection times illustrate that the proposed method is superior. [ABSTRACT FROM AUTHOR]

Over time, distribution systems have progressed from small-scale systems to complex networks, requiring modernization to adapt to these increasing levels of active loads and devices. It is essential to manage the capacity of distribution networks to support all these new technologies. This work, therefore, presents a method for evaluating the impact of optimal allocation and sizing of DGs and load shedding for response demand programs on distribution networks to improve the reliability and financial performance of electric power systems. The proposed optimization tool uses the Greedy Randomized Adaptive Search Procedure and Tabu Search algorithms. The combined optimization of DG allocation simultaneously with load shedding, reliability indices, load transference, and the possibility of islanded operation significantly improves the quality of the planning proposals obtained by the developed method. The results demonstrate the efficiency and robustness of the proposed method, improving the voltage profile by up to 2.02%, relieving the network capacity, and increasing the load restoration capability and reliability. Statistical analysis is also carried out to highlight the performance of the proposed methodology. [ABSTRACT FROM AUTHOR]

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

Ice disasters, such as ice storms, can cause serious damage to power systems. To understand ice disasters' influences on power systems, this paper introduces a resilience evaluation frame for transmission and distribution systems during ice disasters. First, we built a vulnerability model for transmission and distribution systems under ice disaster weather. Then, we established an optimal load power shedding model for transmission and distribution systems. After this, according to the vulnerability model and the optimal power load power shedding model, we generated the fault scenario set of a system in the influence of an ice disaster. According to the curve of system resilience, we propose two resilience evaluation indices of transmission and distribution systems under ice disaster weather. Finally, we verified the efficacy and rationalization of the established resilience evaluation framework with an example in which a transmission and distribution system is coupled with a six-bus transmission system and two distribution systems. This study highlights the necessity of resilience assessment of transmission and distribution systems during ice disasters. [ABSTRACT FROM AUTHOR]

Aiming at the influence of wind power and load uncertainty on the transient stability of a power system under low carbon mode, this paper first proposes a collaborative preventive and emergency control model of transient stability by distribution preserving graph representation learning (DPG). Second, the uncertainty set of wind power output and load demand is studied, and the mathematical form of the two-stage robust transient stability collaborative control model is proposed. Then, the latest artificial intelligence technology is embedded into the global optimization algorithm of the model so as to further improve the solving efficiency of the algorithm. Finally, based on the developed improved two-stage robust optimization framework, an effective collaborative control method for transient stability is developed. The transient stability prediction and control system developed in this project is not only conducive to large-scale wind power grid connection but also expected to make academic contributions to development of power system transient stability and practical simulation verification. [ABSTRACT FROM AUTHOR]

Load shedding control is an emergency control measure to maintain the frequency stability of the power system. Most of the existing load shedding methods use the extensive form of directly cutting off the outlet of the substation, featuring low control accuracy and high control cost. A network reconfiguration technique can adjust the topology of the distribution network and offers more optimization space for load shedding control. Therefore, this paper proposes a reconfiguration–load shedding coordination optimization scheme to reduce the power loss caused by load shedding control. In the proposed method, a load shedding mathematical optimization model based on distribution network reconfiguration is first established. The tie switches and segment switches in the distribution network are used to perform the reconfiguration of the distribution network, and the load switches are adopted to realize the load shedding. To improve the solving efficiency of the model, a solving strategy that combined a minimum spanning tree algorithm with an improved genetic algorithm is trailed to address the nonlinear and nonconvex terms. The application of the proposed method and model are finally verified via the IEEE 33 bus system, and the advantages in reducing the loss cost and the number of outage users are accordingly proven. [ABSTRACT FROM AUTHOR]

The renewed interest for power generation using renewables due to global trends provides an opportunity to rethink the approach to address the old yet existing load shedding problem. In the literature, limited studies are available that address the load shedding problem using a hybrid renewable energy system. This paper aims to fill this gap by proposing a techno-economic optimisation of a hybrid renewable energy system to mitigate the effect of load shedding at the distribution level. The proposed system in this work is configured using a photovoltaic array, wind turbines, an energy storage unit (of batteries), and a diesel generator system. The proposed system is equipped with a rule-based energy management scheme to ensure efficient utilisation and scheduling of the sources. The sizes of the photovoltaic array, wind turbine unit, and the batteries are optimised via the grasshopper optimisation algorithm based on the multi-criterion decision that includes loss of power supply probability, levelised cost of electricity, and payback period. The results for the actual case study in Quetta, Pakistan, show that the optimum sizes of the photovoltaic array, wind turbines, and the batteries are 35.75 kW, 10 kW, and 28.8 kWh, respectively. The sizes are based on the minimum values of levelised cost of electricity (6.64 cents/kWh), loss of power supply probability (0.0092), and payback period (7.4 years). These results are compared with conventional methods (generators, uninterruptible power supply, and a combined system of generator and uninterruptible power supply system) commonly used to deal with the load shedding problem. The results show that the renewable based hybrid system is a reliable and cost-effective option to address grid intermittency problem. [ABSTRACT FROM AUTHOR]

In order to analyze the influence of uncertainty and an operation strategy on the reliability of a standalone microgrid, a reliability evaluation method based on a sequential Monte Carlo (SMC) simulation was developed. Here, the duty cycles of a microturbine (MT), the stochastic performance of photovoltaics (PV), and wind turbine generators (WTG) were considered. Moreover, the time-varying load with random fluctuation was modeled. In this method, the available capacity of an energy storage system (ESS) was also comprehensively considered by the SMC simulation. Then, the reliability evaluation framework was established from the perspectives of probability, frequency, and duration, and reliability evaluation algorithms under different operation strategies were formulated. Lastly, the influence of WTG and PV penetration and equipment capacity on the reliability was evaluated in the test system. The results showed that the complementary characteristics of wind and solar and the enhancement of the equipment capacity can both improve the reliability; but, with the increase in the penetration rate of WTG and PV, more ESS capacity is needed to cope with the randomness of WTG and PV. In addition, load shedding minimization strategies can minimize the probability and the number of reductions and achieve optimal reliability, which can provide a reference for the formulation of microgrid operation strategies. [ABSTRACT FROM AUTHOR]

The contribution current of an inverter-interfaced distributed generator unit during a fault is one of the significant challenges for two modes: grid-connected and isolated AC microgrid. For this challenge, this article is aimed to study two methods of fault current calculation for two modes: grid-connected and isolated microgrids. These methods include a virtual equivalent impedance and a proposed method. The proposed method is a new technique for calculating the fault current contribution depending on the droop control of inverter-interfaced DG. The proposed method can control the contribution short-circuit current of DG within its limit (2 p.u.) where it is dependent on the voltage value of the DG bus to calculate the short circuit current of DG by using the control criterion. Static security risk and load shedding are calculated after fault clearance using an operation scenario in which the distribution system will be divided into small subsystems and is then grid-connected and isolated due to the removal of the faulted bus by protection devices. The proposed technique is applied to a standard IEEE 33-bus distribution network with five DGs. The results show that the contribution current of inverter-interfaced DG during the fault has more effects than the fault current of the nearest faulted bus to the DG bus. The proposed technique improves the calculated fault current value by about 30% for the grid-connected microgrid and by about 50% for the isolated microgrid from its value of the virtual impedance method. The static security risk is improved after load shedding. The static security risk improved by about 0.025%. [ABSTRACT FROM AUTHOR]

Despite the significant slowdown of economic activity in South Africa by virtue of the COVID-19 outbreak, load shedding or scheduled power outages remained at a high level. The trend of rising load-shedding hours has persisted throughout most of the year 2022. Operational issues within the South African power utility inflamed the unpredictable nature of generation capacity, resulting in unscheduled outages at several generating units, mostly due to multiple breakdowns. To forestall substantial spikes in energy costs, an increasing number of enterprises and homeowners have started to gradually adopt renewable energy technologies to sustain their operational demand. Therefore, there is an increase in the exploration and investment of battery energy storage systems (BESS) to exploit South Africa's high solar photovoltaic (PV) energy and help alleviate production losses related to load-shedding-induced downtime. As a result, the current work presents a comprehensive and consequential review conducted on the BESS specifically for solar PV application and in the South African context. The research investigations carried out on BESS for PV application are crucially examined, drawing attention to their capacities, shortcomings, constraints, and prospects for advancement. This investigation probed several areas of interest where the BESS-PV scheme is adopted, viz., choice of battery technology, mitigating miscellaneous power quality problems, optimal power system control, peak load shaving, South African BESS market and status of some Real BESS-PV projects. The techno-economic case scenario has been proposed in the current research and results yield that lithium-ion batteries are more viable than Lead–acid batteries. [ABSTRACT FROM AUTHOR]

With the steep rise in the development of smart grids and the current advancement in developing measuring infrastructure, short term power consumption forecasting has recently gained increasing attention. In fact, the prediction of future power loads turns out to be a key issue to avoid energy wastage and to build effective power management strategies. Furthermore, energy consumption information can be considered historical time series data that are required to extract all meaningful knowledge and then forecast the future consumption. In this work, we aim to model and to compare three different machine learning algorithms in making a time series power forecast. The proposed models are the Long Short-Term Memory (LSTM), the Gated Recurrent Unit (GRU) and the Drop-GRU. We are going to use the power consumption data as our time series dataset and make predictions accordingly. The LSTM neural network has been favored in this work to predict the future load consumption and prevent consumption peaks. To provide a comprehensive evaluation of this method, we have performed several experiments using real data power consumption in some French cities. Experimental results on various time horizons show that the LSTM model produces a better result than the GRU and the Drop-GRU forecasting methods. There are fewer prediction errors and its precision is finer. Therefore, these predictions based on the LSTM method will allow us to make decisions in advance and trigger load shedding in cases where consumption exceeds the authorized threshold. This will have a significant impact on planning the power quality and the maintenance of power equipment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study investigates the potential application of Stateflow (SF) to design an energy management strategy (EMS) for a renewable-based hybrid energy system (HES). The SF is an extended finite state machine; it provides a platform to design, model, and execute complex event-driven systems using an interactive graphical environment. The HES comprises photovoltaics (PV), energy storage units (ESU) and a diesel generator (Gen), integrated with the power grid that experiences a regular load shedding condition (scheduled power outages). The EMS optimizes the energy production and utilization during both modes of HES operation, i.e., grid-connected mode and the islanded mode. For islanded operation mode, a resilient power delivery is ensured when the system is subjected to intermittent renewable supply and grid vulnerability. The contributions of this paper are twofold: first is to propose an integrated framework of HES to address the problem of load shedding, and second is to design and implement a resilient EMS in the SF environment. The validation of the proposed EMS demonstrates its feasibility to serve the load for various operating scenarios. The latter include operations under seasonal variation, abnormal weather conditions, and different load shedding patterns. The simulation results reveal that the proposed EMS not only ensures uninterrupted power supply during load shedding but also reduces grid burden by maximizing the use of PV energy. In addition, the SF-based adopted methodology is envisaged to be a useful alternative to the popular design method using the conventional software tools, particularly for event-driven systems. [ABSTRACT FROM AUTHOR]

The large capacity transmission of power over long distance and the rapid development of renewable energy increase the probability of unexpected emergencies such as overload and under-voltage. To tackle these emergencies and defend future disturbances, the corrective switching is implemented as an online control and a multi-objective scheme-making approach is proposed. A multi-objective 0-1 integer optimization model is established to cover a set of contradictory objectives from the aspects of economics, security and reliability. A two-phase optimization approach is proposed to ensure computation efficiency and coordinate the trade-off between these objectives: in the first phase, a feasible set silting method is utilized to quickly search for a set of candidate corrective switching schemes; in the second phase, the technique for order preference by similarity to an ideal solution (TOPSIS) method is applied to the candidate set to coordinate the contradictory objectives and determine the ultimate engineering scheme. Two case studies are conducted to verify the proposed approach in overload and under-voltage scenarios. The results are discussed to show the strengths when the performance indices of economics, security and reliability are considered. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The microgrid system is an answer to the necessity of increasing renewable energy penetration and also works as a bridge for the future smart grid. Considering the microgrid system applied to commercial building equipped with photovoltaic sources, the usage of a DC microgrid architecture can improve the efficiency of the system, while ensuring robustness and reducing the overall energy cost. Given the power grid stress and the intermittency of the DC microgrid power production, backup power provision and load shedding operations may occur to stabilize the DC bus voltage. Based on the knapsack problem formulation, this paper presents a realistic optimization approach to shedding a building's appliances, considering the priority of each appliance, and also considering a minimum amount of load that must be attended. The problem is solved by mixed integer linear programming and the CPLEX solver. The proposed architecture ensures critical load supply and voltage stabilization through the real-time operation of the operational algorithm allowing the load shedding optimization approach to be applied without compromising the robustness of the system. The results obtained by simulation prove that the DC microgrid is able to supply the building power network by applying the load shedding optimization program to overcome, mainly, the renewable energy intermittency. [ABSTRACT FROM AUTHOR]

The transition of the German electricity system towards a renewable, nuclear free and increasingly fluctuating power generation raises concerns about supply security. A possible contribution to solve this issue might lie in demand response or load shedding measures. The goal of our work is to monetarily quantify the consequences of power interruptions. The focus lies on power interruption costs in 51 economic sectors. Two input-output models are proposed to estimate the Value of Lost Load for each sector. The first does not take inter-linkages of the sectors and possible cascading effects on interruption costs into account. The second model is a new and innovative approach which is based on the Ghosh Input-Output model and which accounts for these effects. We assume that the first model is adequate to assess shorter power interruptions, whereas the second model might be more appropriate when estimating costs of longer interruptions. [ABSTRACT FROM AUTHOR]

Electricity consumption in the world is constantly increasing, making our lives become more and more dependent on electricity. There are several new paradigms proposed in the field of power grids. In Japan, especially after the Great East Japan Earthquake in March 2011, the new power grid paradigms are expected to be more resilient to survive several difficulties during disasters. In this paper, we focus on microgrids and propose priority-based hierarchical operational management for multiagent-based microgrids. The proposed management is a new multiagent-based load shedding scheme and multiagent-based hierarchical architecture to realize such resilient microgrids. We developed a prototype system and performed an evaluation of the proposed management using the developed system. The result of the evaluation shows the effectiveness of our proposal in power shortage situations, such as disasters. [ABSTRACT FROM AUTHOR]

A microgrid is an eco-friendly power system because renewable sources are used as main power sources. In the islanded operation mode of a microgrid, maintaining the balance between power supply and power demand is a very important problem. In the case of surplus supply, decreased generation output and/or charge of distributed storages can be applied to solve the imbalance between power supply and demand. In the case of supply shortages, increased generation output and/or discharge of distributed storages can be applied. Especially in the case of critical supply shortages, load shedding should be applied. In a distributed load-shedding approach, microgrid components need to make decisions autonomously. For autonomous microgrid operation, a multi-agent system has been investigated. In this paper, a distributed load-shedding system for agent-based autonomous operation of a microgrid is designed. The designed system is implemented and tested to show the functionality and feasibility of the proposed system. [ABSTRACT FROM AUTHOR]

Line overload is one of the important causal factors of cascading failures and blackouts in power systems. An optimization method for protection and control measures to mitigate line overloads is proposed in this study. The method consists of two main parts, i.e., the modeling process and the solving process. In the modeling process, an optimization model including overload protection and emergency control measures is developed using PFT (Power Flow Tracing). In the solving process, a multi-stage optimization method using IBSO (Improved Brain Storm Optimization algorithm) is proposed to obtain the final result. The aim of this study is to form a coordinated protection and control strategy that reduces the power on the overloaded line within the safety limits and minimizes the load loss of the power system. The simulation results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Electric power systems are subject to failures, due to both deliberate and fortuitous events. This paper addresses the first case in which a disruptive agent aims at maximizing the damage to the network (expressed through the total cost of operation), while the system operator takes the necessary measures to mitigate the effects of this attack. The interaction between these two agents is modeled by means of a bi-level optimization problem. On one hand, the disruptive agent is positioned in the upper-level optimization problem and must decide which elements to render out of service (lines and generators), given a limited destructive budget. On the other hand, the system operator, located in a lower-level optimization problem, reacts to the attack by deploying mitigation measures in order to minimize cost overruns in system operation. Based on the aforementioned dynamic, this paper proposes a novel approach to maximize the resiliency of the power system under intentional attacks through the implementation of distributed energy resources (DERs), namely, distributed generation (DG) and demand response (DR). Three metrics are proposed to assess resilience by assigning DERs in islands generated by the destruction of lines and generators. The results obtained in a didactic 5-bus test system and the IEEE RTS-24 bus test system demonstrate the applicability and effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper presents a novel incentive-based load shedding management scheme within a microgrid environment equipped with the required IoT infrastructure. The proposed mechanism works on the principles of reverse combinatorial auction. We consider a region of multiple consumers who are willing to curtail their load in the peak hours in order to gain some incentives later. Using the properties of combinatorial auctions, the participants can bid in packages or combinations in order to maximize their and overall social welfare of the system. The winner determination problem of the proposed combinatorial auction, determined using particle swarm optimization algorithm and hybrid genetic algorithm, is also presented in this paper. The performance evaluation and stability test of the proposed scheme are simulated using MATLAB and presented in this paper. The results indicate that combinatorial auctions are an excellent choice for load shedding management where a maximum of 50 users participate. [ABSTRACT FROM AUTHOR]

Under-frequency load shedding (UFLS) is a classic and a commonly accepted measure used to mitigate the frequency disturbances in case of loss-of-generation incidents in AC power grids. Triggering of UFLS is classically done at frequency thresholds when system frequency collapse is already close to happening. The renewed interest for synchronous condensers due to the global trends on massive commissioning of non-synchronous renewable power generation leading to reduction of system inertia gives an opportunity to rethink the approach used to trigger load-shedding activation. This question is especially relevant for the Baltic states facing a desynchronization from Russian power grid and a necessity to operate in an isolated island mode. The main goal of this paper is to introduce a predictive load shedding (LS) method without usage of either frequency or ROCOF measurements based on the monitoring of active power injections of synchronous condensers and to prove the efficiency of the concept through several sets of case study simulations. The paper shows that the proposed approach can provide a greatly improved frequency stability of the power system. The results are analyzed and discussed, the way forward for the practical implementation of the concept is sketched. [ABSTRACT FROM AUTHOR]

This research represents a conceptual shift in the process of introducing flexibility into power system frequency stability-related protection. The existing underfrequency load shedding (UFLS) solution, although robust and fast, has often proved to be incapable of adjusting to different operating conditions. It triggers upon detection of frequency threshold violations, and functions by interrupting the electricity supply to a certain number of consumers, both of which values are decided upon beforehand. Consequently, it often does not comply with its main purpose, i.e., bringing frequency decay to a halt. Instead, the power imbalance is often reversed, resulting in equally undesirable frequency overshoots. Researchers have sought a solution to this shortcoming either by increasing the amount of available information (by means of wide-area communication) or through complex changes to all involved protection relays. In this research, we retain the existing concept of UFLS that performs so well for fast-occurring frequency events. The flexible rebalancing of power is achieved by a small and specialized group of intelligent electronic devices (IEDs) with machine learning functionalities. These IEDs interrupt consumers only when the need to do so is detected with a high degree of certainty. Their small number assures the fine-tuning of power rebalancing and, at the same time, poses no serious threat to system stability in cases of malfunction. [ABSTRACT FROM AUTHOR]

In many developing countries, electricity outages occur frequently with consequences for sustainable development. Moreover, within a country, region or city, the distribution of outages and their resultant impacts often vary from one locality to another. However, due to data constraints, local-scale variations in outage experiences have seldom been examined in African countries. In this study, a spatial approach is used to estimate and compare exposure to electricity load shedding outages across communities in the city of Accra, Ghana. Geographic Information System and statistics from the 2015 rolling blackouts are used to quantify neighborhood-level load shedding experiences and examine for spatial patterns. The results show that annual load shedding exposure varied greatly, ranging from 1117 to 3244 h. The exposure values exhibit statistically significant spatial clustering (Moran's I = 0.3329, p < 0.01). Several neighborhoods classified as load shedding hot or cold spots, clusters and outliers are also identified. Using a spatial approach to quantify load shedding exposure was helpful for overcoming the limitations of lack of fine-grained, micro-level outage data that is often necessary for such an analysis. This approach can therefore be used in other data-constrained cities and regions. The significant global spatial autocorrelation of load-shedding exposure values also suggests influence by underlying spatial processes in shaping the distribution of load shedding experiences. The resultant exposure maps provide vital information on spatial disparities in load shedding implementation, which can be used to influence decisions and policies towards all-inclusive and sustainable electrification. [ABSTRACT FROM AUTHOR]

Smart microgrids (SMGs) may face energy rationing due to unavailability of energy resources. Demand response (DR) in SMGs is useful not only in emergencies, since load cuts might be planned with a reduction in consumption but also in normal operation. SMG energy resources include storage systems, dispatchable units, and resources with uncertainty, such as residential demand, renewable generation, electric vehicle traffic, and electricity markets. An aggregator can optimize the scheduling of these resources, however, load demand can completely curtail until being neglected to increase the profits. The DR function (DRF) is developed as a constraint of minimum size to supply the demand and contributes solving of the 0-1 knapsack problem (KP), which involves a combinatorial optimization. The 0-1 KP stores limited energy capacity and is successful in disconnecting loads. Both constraints, the 0-1 KP and DRF, are compared in the ranking index, load reduction percentage, and execution time. Both functions turn out to be very similar according to the performance of these indicators, unlike the ranking index, in which the DRF has better performance. The DRF reduces to 25% the minimum demand to avoid non-optimal situations, such as non-supplying the demand and has potential benefits, such as the elimination of finite combinations and easy implementation. [ABSTRACT FROM AUTHOR]

In this paper, an efficient under frequency control and the energy management of a distributed energy resources (DERs)-based microgrid is presented. The microgrid is composed of a photovoltaic (PV), double-fed induction generator (DFIG)-based wind and diesel generator with critical and non-critical loads. The system model and the control strategy are developed in a real time digital simulator (RTDS). The coordination and power management of the DERs in both grid-connected and islanded operation modes are implemented. During power imbalances and frequency fluctuations caused by fault or islanding, an advanced automatic load shedding control is implemented to regulate and maintain the microgrid frequency at its rated value. One distinct feature implemented for the load shedding operation is that highly unbalanced critical loads are connected to the microgrid. The diesel generator provides the required inertia in the islanded mode to maintain the microgrid rated frequency by operating in the isochronous mode. The International Council on Large Electric Systems (CIGRE) medium voltage (MV) test bench system is used to implement the DERs and their controller. The proposed control approach has potential applications for the complete operation of microgrids by properly controlling the power, voltage and frequency in both grid-connected and island modes. The real time digital simulator results verify the effectiveness and superiority of the proposed control scheme in grid connected, island and fault conditions. [ABSTRACT FROM AUTHOR]

Fatigue crack propagation in near-threshold regime was studied in the 304L austenitic stainless steel in two microstructural states: as-received (AR) with finer microstructure and low susceptibility to the transformation-induced plasticity (TRIP) effect, and solution-annealed (SA) with coarser microstructure and higher susceptibility to TRIP. At the load ratio R = 0.1 the threshold was higher in the SA state than in the AR state due to coarser grains and possibly the TRIP effect. In order to clarify the role of crack closure, experiments at R = 0.7 were done. The threshold in the SA state was still higher by 1 MPa·m 0.5 . This effect was identified as crack tip shielding induced by phase transformation, an example of a non-closure shielding effect. Higher resistance to crack growth in the SA state was attributed to promoted martensitic transformation in non-favorable oriented grain families rather than thicker martensite layers in the crack path area. The conclusions were verified by experiments at R = 0.7 and temperature 150 °C > M s which did not reveal any notable difference in thresholds. However, the threshold values were affected by the load-shedding gradient C = -dΔK/da, which had to be equalized in both experimental setups inside and outside the furnace.

This paper addresses the integrated planning problem of a power network and the charging infrastructure of electric vehicles (EVs) for enhancing power system resilience under various extreme weather scenarios. The planning methodology determines the optimal joint expansion decisions while modeling the benchmark system operation under the n − k resilience criterion. The proposed coordinated planning framework is a robust two-stage/tri-level mixed-integer optimization model. The proposed robust joint planning model includes the construction plan in the first level, identifying the worst-case scenario in the second level, and optimizing the operation cost and load shedding in the final level. To solve this model, a duality-based column and constraint generation (D-CCG) algorithm is developed. Using case studies, both the robust sole transmission planning and joint planning models are demonstrated on the IEEE 30-bus and IEEE 118-bus power systems. Numerical simulations of the benchmark systems validate the effectiveness of the developed framework and the efficiency of the proposed solution approach. Simulation results show the superiority of the proposed robust integrated planning over the sole transmission planning model. [ABSTRACT FROM AUTHOR]

Renewable energy incorporation in many countries takes different forms. In many developed countries, grid-tied solar photovoltaic (PV) installations are widely coupled with lucrative Feed-in-Tariffs (FiT). However, conventional grid-tied solutions are not readily viable in many developing countries mainly due to intermittent grids with load shedding and, in some cases, lack of net-metering or FiT. Load shedding refers to an intentional electrical power shutdown by the utility company where electricity delivery is stopped for non-overlapping periods of time over different parts of the distribution region. This results in a non-continuous availability of the utility grid for many consumers over the course of a day. In this work, the key challenges in the integration of solar energy explicitly in residential power back-up units are reviewed and system hardware level requirements to allow optimized solar PV utilization in such intermittent grid environments are analyzed. Further, based upon the low-cost sensing and real-time monitoring scheme, an online optimization framework enabling efficient solar incorporation in existing systems to achieve minimum grid dependence in intermittent grid environments is also provided. This work is particularly targeted for over 1.5 billion residents of semi-electrified regions in South Asia and Africa with the weak and intermittent grid. [ABSTRACT FROM AUTHOR]

The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluctuations. A Benders’ decomposition algorithm is developed to solve the proposed two-stage model. Finally, extensive numerical studies are conducted with Garver’s 6-bus system, a modified IEEE RTS79 system and IEEE 118-bus system, and the computational results demonstrate the effectiveness and practicability of the proposed method. [ABSTRACT FROM AUTHOR]

Load shedding processes are widespread in hydropower stations, which has great influence on the safe and stable operation of the hydro–turbine governing system. In order to study the dynamic characteristics of the hydro–turbine governing system during the load shedding process, a novel nonlinear mathematical model of the hydro–turbine governing system is established considering the hydro–turbine system, the generator system and the governor system. In particular, a novel nonlinear mathematical model of the six hydro–turbine transfer coefficients is presented based on the definitions and hydro–turbine internal characteristics. After that, from the viewpoint of nonlinear dynamics and the practical engineering, the dynamic characteristics of the hydro–turbine governing system are investigated utilizing bifurcation diagrams, time series, Poincare maps, power spectrums and phase planes. Some meaningful results are found. The advantages of the novel nonlinear mathematical model are illustrated and commented in detail in comparison with the previous model. Finally, these models and analysis results will provide some theoretical references for the operation of hydropower stations in the load shedding transient. [ABSTRACT FROM AUTHOR]