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

Renewable generation has grown rapidly these years due to its advantages in low environmental impacts. Stand-alone microgrid with renewable generation and energy storage is a promising option in remote areas beyond the reach of an existing power grid. This paper proposes a multiobjective optimization model to co-optimize the sizes of renewable generation and energy storage in stand-alone microgrids, which minimizes the load shedding risk and the total investment cost. The load shedding degree is obtained by an optimal operation problem and measured by shortfall risk, considering the uncertainties of demand and renewable resources. To deal with the inaccurate empirical distribution, distributionally robust shortfall risk is further established under a Wasserstein-metric based ambiguity set, and an equivalent distributionally robust formulation is obtained. Then a conservative approximation is developed, and the resulting problem appears to be a bi-objective linear program. The Pareto frontier is proven to be piecewise linear, and the analytical expression of the Pareto frontier is derived. Case studies demonstrate the effectiveness and performance of the proposed method.

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.

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.

Aim. A novel technique for detecting imminent voltage instability is proposed in this paper, accompanied by a novel load shedding approach to protect the system from voltage instability. Methodology. The proposed methodology utilizes the computation of nodal reactive power loss to voltage sensitivities with load increments in the system. Originality. The nodal reactive power loss to voltage sensitivity is a novel computation and is explored to detect the likelihood of voltage instability in this work. Results. If the system is experiencing an unprecedented load growth and if all the measures reach their limits, then load shedding is the last resort to safeguard the system against instability. The sudden change in nodal reactive power loss to voltage sensitivities is utilized to devise the quantity of load to be cut in the system. Practical value. The time-based simulations performed in New England 39 bus test system (NE-39 bus), the simulated results show that nodal reactive power loss to voltage sensitivities can be used as a trusted indicator for early diagnosing of menacing voltage instability and the timely implementation of load shedding developed from nodal reactive power loss to voltage sensitivities on the system ensures voltage stability., Мета. У статті пропонується новий метод виявлення навислої нестабільності напруги, що супроводжується новим підходом до скидання навантаження для захисту системи від нестабільності напруги. Методологія. У запропонованій методиці використовується розрахунок вузлових втрат реактивної потужності залежно від чутливості до напруги при збільшенні навантаження у системі. Оригінальність. У цій роботі вузлові втрати реактивної потужності залежно від чутливості до напруги являють собою новий розрахунок і досліджуються визначення ймовірності нестабільності напруги. Результати. Якщо система відчуває безпрецедентне зростання навантаження і всі заходи досягають меж своїх можливостей, скидання навантаження є останнім засобом захисту від нестабільності. Раптова зміна вузлових втрат реактивної потужності, залежно від чутливості до напруги, використовується для визначення величини навантаження, яка повинна бути відсічена в системі. Практична цінність. Моделювання, засноване на часі, виконане в тестовій системі шини New England 39 (шина NE-39), та результати моделювання показують, що залежність вузлових втрат реактивної потужності від чутливості до напруги може використовуватися як надійний індикатор для ранньої діагностики загрозливої нестабільності напруги та своєчасного впровадження скидання навантаження, що виникає внаслідок втрати реактивної потужності у вузлах, до чутливості системи до напруги,а забезпечує стабільність напруги.

The optimal load shedding calculations of an enormous number of contingency states are the most challenging impediments for power system reliability assessment, especially in a large-scale system with multiple types of loads. To deal with that, this paper proposes a fast method that accelerates the calculation of optimal load shedding based on the shadow price. This method calculates the optimal load shedding of systems by shadow-price-based linear functions, rather than the time-consuming OPF algorithms. The hundred percentage criterion is used to look for the matching shadow price of states. Case studies are performed on the RTS-79 system. The results show that the proposed methodology can significantly simplify the solving process and reduce the calculation time.

This paper proposes a new load shedding method based on the application of a Dual Neural Network (NN). The combination of a Back-Propagation Neural Network (BPNN) and of Particle Swarm Optimization (PSO) aims to quickly predict and propose a load shedding strategy when a fault occurs in the microgrid (MG) system. The PSO algorithm has the ability to search and compare multiple points, so the proposed NN training method helps determine the link weights faster and stronger. As a result, the proposed method saves training time and achieves higher accuracy. The Analytic Hierarchy Process (AHP) algorithm is applied to rank the loads based on their importance factor. The results of the ratings of the loads serve as a basis for constructing the load shedding strategies of a NN combined with the PSO algorithm (ANN-PSO). The proposed load shedding method is tested on an IEEE 25-bus 8-generator MG power system. The simulation results show that the frequency recovery of the power system is positive. The proposed neural network adapts well to the simulated data of the system and achieves high performance in fault prediction.

Voltage instability takes on the form of a dramatic drop of transmission system voltages, which may lead to system disruption. During the past two decades it has become a major threat for the operation of many systems and, in the prevailing open access environment, it is a factor leading to limit power transfers. The objective of this paper is to present new method of under voltage protection with maximum utilization of system capabilities.

In this paper, an important application of Interconnected microgrids (IMGs) is presented in order to handle an emergency condition of individual microgrids (MGs), which causes an intolerable voltage magnitude or frequency deviation. In this method, the active and reactive powers are exchanged via an interlinking back-to-back converter (BTBC) and in accordance with voltage magnitude and/or frequency differences of individual MGs. In order to increase the IMG reliability and overcome the communication challenges, only local voltages and frequencies of both AC sides of the BTBC are used to determine the required active and reactive powers to be exchanged. A generalized droop control is employed to consider the impact of voltage magnitude and frequency differences on exchanging active and reactive powers separately for any type of interlinking lines. In this emergency power exchange method, a logical control is employed to detect the emergency condition, which results in the IMG formation, as well as to detect the normal condition and form the individual MGs operation again. The real-time results, obtained from OPAL-RT simulator, practically show advantages of the proposed method including voltage and frequency supports, postponing the load shedding, plug-and-play capability, good power sharing between the IMGs and method compatibility with the controls of individual MGs.

For a growing country such as South Africa, the energy demand outweighs the energy supply, thisresults in frequent power cuts. Equipment such as refrigerators are affected. To preserve foodproducts during these power cuts Phase Change Material (PCM) material can be used. This paperpresents the study of three eutectic salt water solutions investigated, 𝐾𝐶𝑙, 𝑀𝑔𝐶𝑙2 𝑎𝑛𝑑 𝑁𝑎𝐶𝑙. Thesesalts were chosen because of the high latent heat and their relatively low price. From experiments,it was confirmed that 𝐾𝐶𝑙, 𝑀𝑔𝐶𝑙2 𝑎𝑛𝑑 𝑁𝑎𝐶𝑙 had a phase change temperature of -11°C, ± -7°C and-22°C. 𝐾𝐶𝑙 was seen as the ideal solution, however segregation will decrease performance in thelong run. 𝑁𝑎𝐶𝑙 is ideal since it offers a lower phase change temperature resulting in a greater heattransfer in the compartment. The refrigerator freezer might not be able to completely freeze the𝑁𝑎𝐶𝑙 solution. For 𝑀𝑔𝐶𝑙2, the concentration of 25% might be incorrect, the study concluded thatanother concentration ratio will have to be evaluated.

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 °C. 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 °C 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 °C 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 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.

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.

Load shedding is an operating condition in which the electrical grid is temporarily disconnected from the load. The objective is to minimize the gap between available generation capacity and load demand while maintaining an equitable supply for all consumers. Load shedding is a prominent problem for many developing countries. To address this issue, this paper explores the potential of a hybrid energy system (HES) to provide uninterrupted power supply at the distribution feeder despite load shedding from electrical grid. The proposed HES in this work combines photovoltaic (PV) array, battery storage system (BSS) and diesel generator (DG). The HES is equipped with energy management scheme (EMS) that ensures continuous power supply, improves energy efficiency, and minimizes the electricity cost. To accomplish these tasks, the EMS operates the system in one of three modes: grid mode, renewable energy source mode and the diesel generator mode. Besides, the proposed methodology allows injecting surplus PV energy into the grid, thus maximizing PV utilization and improving power system’s reliability. The results of this study will assist policymakers to determine the prospect of renewable based hybrid system to supply sustainable power and eliminate the energy problems in the power deficit countries.

The rapidly drop of frequency in the microgrid (MG) system when it operates under island operation has caused frequency stability problems. In case, generators and renewable energy sources cannot s...

The load‐shedding scenario describes an unscheduled load reduction in a power plant so that it produces only the electricity that is needed by the plant itself. The reason for such a scenario is a collapse of power supply in the transmission network. In the subsequent restoration of the electrical supply, different options are distinguished. An essential part of each option is island operating or black start capable thermal power plants. The load‐shedding scenario is complex and multilayered. If process steam is also decoupled during the load shedding, high exhaust steam temperatures in the turbine stages can lead to plant shutdown. In addition, component damage can be expected in thick‐walled components due to high temperature and pressure amplitudes. Thus, it can be shown in this paper that the lifetime losses are highest at the high‐pressure preheater 6 and at the deheater and that the process heat coupling cannot be operated with constant mass flow under all circumstances. In order to investigate these issues, a detailed model of a lignite power plant has been created, which was developed in Modelica for simulating and comparing scenarios for a variety of applications. The model comprises the entire water‐steam cycle including turbines, preheaters and pumps, as well as a very detailed boiler model including the air supply, coal mills, heating surfaces, and piping. Furthermore, the power plants' control system has been implemented in a very precise way. In addition, the study involves a calculation of lifetime consumption for specific components to evaluate the effects. In summary, it can be stated that this study examines the thermodynamic aspects during a load‐shedding scenario for the first time. It focuses on processes within the power plant and thus differs significantly from other studies on this topic, which approach the issue from the electrical grid side.

In order to accommodate the uncertainty and variability of wind power, this paper proposes a scenario-based probabilistic model to assess the impact of intermittent wind power-based Renewable Energy Resources (RES) on the Transmission Network Expansion Planning (TNEP). The objectives comprise the evaluation of impacts considering the wind power penetration into connected and unconnected buses, as well as the optimization of reinforcements that must be made to avoid unwanted wind cutting operations and load shedding. The wind power uncertainties are represented through scenarios obtained from real historical series grouped by using the well-known k-means algorithm. The methodology performance is verified in a practical equivalent Brazilian southern system, modified to include a significant amount of wind energy. The obtained results show that the RES insertion impacts the TNEP task, changing the expansion decision.

This paper presents a novel technique for optimum load shedding in a power system based on under voltage considerations. A quadratic performance index based on voltage deviation has been adopted. T...

Novel COVID‐19 caused turmoil in every domain of life around the globe. To halt the further spread of virus, preventive measures such as social and physical distancing has led the temporal cessation of all education institutions in numerous countries. To minimize disruption of teaching and learning process during epidemic, the Higher Education Commission (HEC) of Pakistan directed universities transition to an online learning system. The research paper explores deeply the problems faced by students in the current online education system introduced by various universities. A survey research method was employed and the data were collected through convenience sampling. The link of the semi-structured questionnaire was shared with 550 students enrolled in public and private universities in Lahore, Pakistan. The study brought to light the diversified problems such as lack of internet facility, load shedding, financial issues, ear pain due to prolong use of hand free/Bluetooth and unreliable results in assessments.

Dissertação de Mestrado em Engenharia Eletrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia Com o aumento da utilização de veículos elétricos, juntamente com a expansão da geração de energias renováveis distribuídas a baixo custo e os avanços tecnológicos nos sistemas de armazenamento de energia, introduziram novas tecnologias e alteraram o paradigma para a conceção e administração da rede. Os benefícios da microredes vão desde o aumento da flexibilidade de carga para fazer face a picos de consumo, uma integração mais eficiente da geração renovável intermitente, a redução das perdas de T&D, a prestação de serviços auxiliares, bem como benefícios económicos e ambientais. Uma das principais características das microredes é que têm a capacidade de trabalhar de forma autónoma em relação à rede pública, utilizando recursos de produção local e armazenamento de energia. O aumento da frequência de catástrofes naturais levou a situações em que pequenas aldeias ficaram isoladas da rede de fornecimento de energia. A capacidade das microredes de trabalhar de forma autónoma apresenta uma solução viável para este problema. O objetivo deste projeto é desenvolver estratégias e algoritmos inovadores para a conceção e gestão de microredes elétricos com foco na resiliência para situações críticas e de catástrofes e também utilizar recursos para aumentar a sua relação custo-benefício. As soluções propostas serão simuladas, utilizando uma microrede a implementar no DEEC-UC como piloto. Como resultado do trabalho, o estudo apresenta um algoritmo que gere de forma eficaz as cargas de uma microrede de forma a garantir a sua resiliência, e uma arquitetura que permite que um sistema trifásico funcione como um sistema monofásico, quando a microrede é isolada da rede de fornecimento de energia. The increasing use of electric vehicles, together with the expansion of low-cost distributed renewable energy generation and technological advancements in energy storage systems, introduced new technologies and altered the paradigm for grid design and administration. Benefits of Microgrids range from increased load flexibility to cope with peak consumption, more efficient integration of intermittent renewable generation, reduced T&D losses, provision of ancillary services as well as economic and environmental benefits. One of the main characteristics of microgrids is that they have the ability to work autonomously in relation to the utility grid using local generation and energy storage resources. The increasing frequency of natural disasters have led to situations where small towns become isolated from the main utility grid. The microgrids’ ability to work autonomously from the utility grid present a viable solution to this problem. The objective of this project is to develop innovative strategies and algorithms for the design and management of electric microgrids with a focus on resiliency towards critical and disaster situations and also to use resources to increase its cost-effectiveness. The proposed solutions will be simulated, using a microgrid to be implemented at the DEEC-UC as a pilot. As a result of the work, the study presents an algorithm that efficiently manages the loads of a microgrid in order to ensure its resilience, and an architecture that allows a three-phase system to function as a single-phase system, when the microgrid is isolated from the utility grid.

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.

SIGNIFICANCE: Electrification is expected to decarbonise transportation and forms part of the agenda to delay climate change. Electric vehicle sales have ballooned and production of combustion engines will stop soon. In sub-Saharan Africa the transition is slow. Minibus taxis carry more than 70% of commuters and little is known about their electrification requirements. Electrical demand planning is better with vehicle-based data than with passenger-based data. Stationary times provide ample time for taxis to recharge from the grid and solar, but the latter requires substantial stationary battery capacity to negate grid-impacting fast charging. Taxi energy requirements are approximately 200 kWh/day on average.

Publicaciones en Ciencias y Tecnología, Vol 16, Nro 2, año 2022. La FIDVR representa una importante amenaza para la operación segura y confiable de los sistemas eléctricos de potencia con carga dominada por motores de inducción. En este trabajo se propone una estrategia de rechazo de carga basada en el tiempo de recuperación crítico (CRT) de la tensión para mitigar la FIDVR. El CRT permite identificar las barras más efectivas principalmente responsables de la FIDVR. Mientras que la desviación del CRT determina la cantidad de carga a desconectar en cada barra efectiva según la severidad de la FIDVR. Los resultados obtenidos mediante la simulación de la estrategia en el DPL de Power Factory DigSilent en el sistema 39 Bus New England demostraron que es capaz de identificar la ubicación y la cantidad de carga más efectiva para mitigar la FIDVR. Comparado con el esquema convencional UVLS la estrategia propuesta logra una recuperación rápida de la tensión y requiere de una menor cantidad de carga a desconectar. Se concluye que la estrategia de rechazo de carga propuesta responde adaptivamente a la severidad de la FIDVR para desconectar la mínima cantidad de carga con la finalidad de mejorar la estabilidad de tensión de corto plazo. // FIDVR represents a major threat to the safe and reliable operation of electrical power systems with load dominated induction motors. In this paper, a load shedding strategy based on the critical recovery time (CRT) of voltage is proposed to mitigate FIDVR. The CRT allows to identify the most effective load mainly responsible for the FIDVR. While the CRT deviation determines the amount of load to be disconnected in each effective bus according to the severity of the FIDVR. The results obtained by simulating the strategy in the Power Factory DigSilent DPL on the 39 Bus New England system showed that it is capable of identifying the most effective location and amount of load to mitigate FIDVR. Compared with the conventional UVLS scheme, the proposed strategy achieves a fast voltage recovery and requires a smaller amount of load to be disconnected. It is concluded that the proposed load shedding strategy responds adaptively to the severity of the FIDVR to disconnect the minimum amount of load in order to improve short-term voltage stability.

Recently, the increasing penetration of wind energy has provided various ways to operate the system at low cost and low pollution. On the other hand, the noticeable uncertainties caused by the forecast error of wind speed restrict the utilization of wind energy. Moreover, it brings unprecedented challenges to maintain system adequacy. One prevailing solution is to maintain sufficient spinning reserve of thermal units, which is not affordable. This paper analyses the relationship between the operation cost and wind power uncertainty using AC unit commitment in the frame of a short-term market. Conditional value-at-risk is established in a percentage of the worst-case estimations on wind power scenario under uncertainty to achieve adequate trade-offs between optimal solution and risk aversion. Operation cost of generation, load shedding cost and reserve cost are optimally established by multi-objective optimization. Finally, the simulation is performed on the test system and the obtained results are evaluated and compared to demonstrate the research effectiveness.

PurposeThis study examined the factors that influence households’ intention to adopt solar energy solutions in Zambia. This, in view of low adoption rates of solar energy solutions even in the wake of a widespread electricity power generation deficit across sub-Sahara Africa (SSA) has plagued the region with daily electricity load shedding lasting several hours at a time. Given the vast potential for solar energy generation in the region, solar energy solutions have become an attractive option to grid-based electricity, and many households have intentions of adopting these solutions.Design/methodology/approachThrough the lens of the theory of planned behaviour (TPB), the study surveyed adult household members in Zambia who contributed towards the household’s income. The participants were selected using the snowballing technique, which yielded a sample of 961 respondents. The results were analysed using structural equation modelling.FindingsThe results show that attitude, trust, benefits and subjective norms influence the intention to adopt solar energy solutions. Trust and benefits also influence the intention to adopt solar energy solutions indirectly through attitude. Therefore, measures aimed at increasing the adoption of solar energy solutions should focus on improving the attitude, perceived benefits, trust in the solutions and consider subjective norms.Originality/valueThe findings add to the understanding of the factors that influence the intention to adopt solar energy solutions in Zambia. Therefore, the findings can be used to inform measures aimed at improving solar energy uptake in Zambia. The study also reports on the previously unreported mediating role of attitude towards solar energy solution on the associations between perceived benefits and trust with solar energy solutions adoption intention.

This paper presents the optimal load‐shedding strategy of home energy management systems (HEMSs). The HEMS uses the dynamic programming (DP) method to plan the day ahead, schedule, and connects to smart plugs to perform load‐shedding. HEMS solves the shedding schedule of smart plugs considering the prediction of consumption of each smart plug and the consumer's demand response (DR) setting. In addition, the maximum DR capacity was determined by using golden section search (GSS). Some DR experiments were conducted by the proposed method in laboratory and these comprised three different DR durations. The results show that the estimated DR capacities and shedding schedules were feasible. Thus, it helps both the DR participants and aggregator to seize the optimum performance and benefits.

We develop a two-stage stochastic program for energy and reserve dispatch of a joint power and gas system with a high penetration of renewables. Data-driven distributionally robust chance constraints ensure that there is no load shedding and renewable spillage with high probability. We solve this problem efficiently using conditional value-at-risk approximations and linear decision rules. Out-of-sample experiments show that this model dominates the corresponding stochastic program without chance constraints that models the effects of load shedding and renewable spillage explicitly.

This paper proposes a new adaptive underfrequency load shedding scheme (UFLS) to avoid frequency instability in electrical power system during abnormal wide area disturbances. The developed scheme is based on online monitoring of the distance relay zone 3 decisions of some tie lines using (WAMS) and SCADA/EMS systems, to check rapidly and reliably the uncontrolled islanding conditions and, permit an automatic load shedding action to maintain frequency stability of power system. Simulation results on 400 kV Turkish transmission systems demonstrated the effectiveness of the proposed scheme compared to current frequency load shedding schemes which they cannot consider all possible circumstances because of their limited access to the power network data. Simulation results clearly indicate that large disturbances in power systems can be avoided and their propagation can also be stopped using the proposed scheme.

This paper investigates the dynamic stability of power systems due to disturbances of finite magnitude that last for some minutes. In this paper the effect of only active power deficits is investigated. A computer program is developed to discuss system frequency changes during such disturbances. The program implements a practical approach using an energy aproach and gives an insight to the following issues : (i) hydro spinning reserve is modelled as a function of frequency deviations, while thermal reserve is independent of frequency deviations. (ii) hydro and thermal spinning reserves are modelled as a function of frequency deviations. (iii) load shedding modelling in steps to trip loads as the frequency decreases. This approach is applied to the Egyptian power system using the load shedding scheme adopted in the system. Three case studies, each case is studied for twelve active power deficits ranging from 150 MW to 1800 MW during three loading conditions (minimum day, maximum day and maximum evening). The results represent three scenarios for system restoration, the first one neglects the effect of spinning reserve, while the second and third ones implement the utilization of spinning reserve as mentioned here above.

This paper analyzes the electrical parameters of areas that contain distributed generation facilities. It demonstrates the necessity of stricter requirements to the performance of energy system automated systems, especially in island operation. It is noted that implementing a special procedure for truncating the standard sequential analysis (Wald analysis) for automated decision-making is a time-consuming process. By ensuring the constancy of first- and second-kind errors at each step of the Wald analysis, one can generate adaptable settings. The paper uses evidence from an automated underfrequency load shedding unit to show that a modified sequential analysis algorithm performs twice as fast. The authors present guidelines on how to adopt this modified algorithm in existing or newly developed energy system automated systems.

This paper proposes a novel methodology for the optimization of load shedding based on voltage-dependent load model accounting stability constraints using Black Hole (BH) optimization technique under emergency conditions. Line voltage stability index relation is derived for the selection of load bus. Load buses for load shedding are identified on the basis of large sensitivity of minimum value of line voltage stability index with respect to the system load. The load shedding has been optimized subject to stability constraints using BH algorithm. Testing of the developed algorithm has been done using IEEE 14, 25 and 118 bus power systems. The optimized results of the proposed algorithm have been compared on the basis of statistical inference with results obtained using well-established optimization techniques. Simulation results authenticate that the proposed methodology mitigates a considerable amount of load shedding and the system can be prevented from blackouts.

Despite increased global energy supply, many households have insufficient access to energy in developing countries. Power utility companies, mostly parastatals, fail to cope with the burgeoning ene...

The rapid drop of frequency under the disturbance is a major threat to the safe and stable operation of a microgrid (MG) system. Emergency load shedding is the main measure to prevent continuous frequency drop and power outage. The existing load shedding strategies have poor adaptability to deal with the problem of MG load shedding under different disturbance situations, and it is difficult to ensure the safe and stable operation of an MG in different operating environments. To address this problem, this paper proposes a data-driven load shedding strategy. First, considering the importance of the load and the frequency recovery time of the system, a load shedding contribution indicator is designed that takes into account the load frequency adjustment effect and the load shedding priority. This contribution indicator is introduced as a load shedding criterion into the reward value function of dueling deep Q learning. Second, considering the suddenness and uncertainty of emergency load shedding, a MG emergency load shedding strategy (ELSS) based on dueling deep Q-learning is proposed. On this basis, the dueling deep Q learning algorithm is used to obtain the load shedding decision with the maximum cumulative reward. Finally, taking the MG load shedding cases in two different scenarios as examples, a simulation study is carried out on a modified IEEE-25 bus MG. The simulation results show that, compared with the model-driven implicit enumeration strategy (IES), the proposed ELSS has superiority in maintaining stable power supply for important loads and reducing load shedding decision-making time and frequency fluctuations.

The aim of this research work is to develop a load shedding methodology to improve the frequency response of low inertia grids by attaining satisfactory voltage stability. In recent times, wind energy integration has considerably increased in many power grids. Consequently, conventional synchronous machines are being replaced from dispatch. Unlike traditional synchronous machines, variable speed wind turbine generators usually do not take part in frequency regulation without supplementary control mechanism. During substantial wind penetration, a power system may have a small number of online synchronous machines. As a result, synchronous inertia and governor responsive reserve significantly reduce. Under such situation, a system has to rely on load shedding as a last line of defense to rescue the system frequency following a large contingency. However, the conventional Under-Frequency Load Shedding (UFLS) strategy may lead to larger frequency deviation and higher amount of load cut in certain cases. A new load shedding methodology is presented in this paper to overcome this challenge. Unlike conventional UFLS technique, higher proportion of load shedding is applied to relatively weaker buses in terms of voltage stability in the proposed mechanism. Based on reactive power margin, which is an index to specify voltage stability, a general expression to quantify load shedding is derived. Also, the adaptability of the proposed strategy to various load levels is ensured. Later on, performances of the developed strategy are explored in a low inertia wind dominated test network. Simulations are executed considering various penetration levels of wind power and for two severe contingencies – loss of 550 MW interconnection and loss of 650 MW interconnection. Investigations reveal that the proposed load shedding methodology ensures satisfactory frequency response in all simulation cases. Also, the developed technique yields less frequency deviation and load cut compared to the conventional UFLS mechanism. Therefore, the reported load shedding scheme is found to be more competent to concurrently maintain frequency and voltage stabilities in renewable dominated power systems.

Operator migration is a crucial concept to adapt event processing systems to dynamic changes. When the placement of a stateful operator changes, the operator state must be migrated to the new host. However, operator state size and time constraints can make it impossible to migrate the operator without severe Quality of Service (QoS) degradation. As a relief, we propose to perform state shedding in such a situation. The core idea of state shedding is to partition the operator state, assign a utility to each partial state, and use the utility and size of each partial state to identify the most useful partial states that can be migrated in a given time frame. Thus, state shedding can maintain a substantially higher QoS with a lower impact on query results than state-of-the-art solutions targeting consistent state at the old and new host. In this paper, we define this novel approach and in a simulation environment evaluate state shedding in migration scenarios with pattern-matching queries.

espanolLos sistemas de transmision y distribucion estan sujetos no solo a fallas naturales sino tambien a fallas causadas por ataques intencionales. Estos ultimos llevados a cabo por agentes maliciosos que tienen como objetivo maximizar el deslastre de carga del sistema. Los ataques intencionales son contrarrestados por la reaccion del operador del sistema que lleva a cabo estrategias para minimizar el dano causado por los ataques. Este articulo presenta un modelo de programacion binivel para mejorar la resiliencia de los sistemas de potencia con alta participacion de generacion distribuida (GD). El modelo describe la interaccion de un agente disruptivo que pretende maximizar el dano al sistema de potencia y el operador de red que recurre a diferentes estrategias para minimizar el dano. El modelo propuesto es no lineal entero mixto y se soluciona mediante un algoritmo genetico hibrido. Se pudo observar que a mayor participacion de la GD el impacto de los ataques era menor. La presencia de GD tambien tuvo influencia en las estrategias del atacante, el cual, en algunos casos, se desviaba de los ataques optimos a soluciones sub-optimas. Lo anterior permite concluir que la presencia de GD beneficia al sistema de potencia en terminos de menor deslastre de carga esperado ante ataques intencionales. EnglishElectric transmission and distribution systems are subject not only to natural occurring outages but also to intentional attacks. These lasts performed by malicious agents that aim at maximizing the load shedding of the system. Intentional attacks are counteracted by the reaction of the system operator which deploys strategies to minimize the damage caused by such attacks. This paper presents a bilevel modeling approach for enhancing resilience of power systems with high participation of distributed generation (DG). The model describes the interaction of a disruptive agent that aims at maximizing damage to a power system and the system operator that resorts to different strategies to minimize system damage. The proposed mixed integer nonlinear programming model is solved with a hybrid genetic algorithm. Results are presented on a benchmark power system showing the optimal responses of the system operator for a set of deliberate attacks. It was observed that the higher the participation of DG the lower the impact of the attacks was. The presence of DG also influenced the optimal strategies of the attacker which in some cases deviated from optimal attack plans to suboptimal solutions. This allows concluding that the presence of DG benefits the power system in terms of less expected load shedding under intentional attacks.

Voltage stability is one of the most important factors in maintaining reliable operation of power systems. When a disturbance occurs in the power system, it usually causes instabilities and sometimes leads to voltage collapse (VC). To avoid such problems, a novel approach called Vector Analysis (VA) is proposed that exploits a new instability detection index to provide wide area voltage stability for the power systems. The presented index is calculated based on measuring the active and reactive powers that flow through the bus which is connected to the generator bus. Moreover, when the proposed VA approach predicts VC, through disconnecting weak lines and based on network graph, zoning is carried out in the power system. After zoning, damaged and undamaged zones will be differentiated and damaged zones requires load shedding (LS) which is accomplished using ANFIS-TSK (AN-T) intelligent method. The presented approach is applied to the IEEE-39 bus test system. The obtained simulation results demonstrate acceptable performance of the presented approach compared with other suggested methods in terms of speed and accuracy.

Purpose Storage systems are deemed to be unable to provide revenue commensurate with the resources invested in them, thus discouraging their incorporation within power networks. In prosumer microgrids, storage systems can provide revenue from reduced grid consumption, energy arbitraging or when serving as back-up power. This study aims to examine stacking these revenue streams with the aim of making storage systems financially viable for inclusion in prosumer microgrids. Design/methodology/approach With the aim of reducing self-consumption and maximising revenue, the prosumer microgrid incorporating hybrid energy storage systems (HESS) and solar PV power is solved using the CPLEX solver of the Advanced Interactive Multidimensional Modeling Software (AIMMS). The financial analysis of the results is carried out to provide the payback periods of different system configurations of the prosumer microgrid. Findings The findings reveal that the payback period of the three HESS when minimising grid expenses during self-consumption alone and when compared with stacked revenue streams shows an improvement from 4.8–11.2 years to 2.4–6.6 years. With stacked HESS revenues, the supercapacitor-lithium ion battery HESS gave the shortest payback period of 2.31 years when solar PV power is at 75% penetration level. Originality/value Existing literature has considered revenue streams of storage systems at the electrical power transmission and distribution levels, but not for prosumer microgrids in particular. This study has captured these benefits and verified the profitability of stacking revenue from HESS to prosumer microgrids, using a case study.

Load shedding (LS) is implemented by distribution utilities (DUs) in addressing power supply insufficiency problems to avoid DU system damages. This is commonly implemented by the installation of LS relays in every DU feeder. However, in either scheduled or unscheduled supply disruptions, a huge amount of unnecessary de-loading is taking place in a feeder level LS implementation. In addition, the consumers connected to a de-loaded feeder are in total blackout, that is, consumers have no choice over which appliances to spare from being de-loaded. This study proposes an LS implementation that replaces feeder-level de-loading by a finer consumer-appliance-level de-loading and allows consumers to have some control over their de-loading. In this method, consumers can set an appliance priority level to their selected connected loads at a given time, to avoid a total blackout. Furthermore, to deal with the enormous data involved in this proposed method, both centralised and distributed optimisation approaches are employed to expedite the system processing response. Simulations are conducted to verify the proposed method's functionality. Lastly, economic analysis is done to assess the proposed method's viability.

The Internet-of-Things (IoT) has emerged as an alternative to communicate different pieces of technology to foster the distributed data collection. The measurement projects and the Real-time data processing are articulated to take advantage of this environment, fostering a sustainable data-driven decision making. The Data Stream Processing Strategy (DSPS) is a Stream Processing Engine focused on measurement projects, where each concept is previously agreed through a measurement framework. The Measurement Adapter (MA) is a component whose responsibility is to pair each metric’s definition from the measurement project with data sensors to transmit data (i.e., measures) with metadata (i.e., tags indicating the data meaning) together. The Gathering Function (GF) receives and derivates data for its processing from each MA, while it implements load-shedding (LS) techniques based on Metadata to avoid a processing collapse when all MAs informs jointly and frequently. Here, a Metadata and Z-score based load-shedding technique implemented locally in the MA is proposed. Thus, the load-shedding is located at the same data source to avoid data transmission and saving resources. Also, an incremental estimation of average, deviations, covariance, and correlations are implemented and employed to calculate the Z-scores and to data retain/discard selectively. Four simulations discrete were designed and performed to analyze the proposal. Results indicate that the local LS required only 24% of the original data transmissions, a minimum of 18.61 ms as the data lifespan, while it consumes 890.26 KB. As future work, other kinds of dependencies analysis will be analyzed to provide local alternatives to LS.

Due to the increase of load demand, the utility tends to utilize DG technology in recent years. The intentional islanding is an appropriate approach to enhance system performance such as reliabilit...

Cascading blackouts typically occur when nearly simultaneous outages occur in $k$ out of $N$ components in a power system, triggering subsequent failures that propagate through the network and cause significant load shedding. While large cascades are rare, their impact can be catastrophic, so quantifying their risk is important for grid planning and operation. A common assumption in previous approaches to quantifying such risk is that the $k$ initiating component outages are statistically independent events. However, when triggered by a common exogenous cause, initiating outages may actually be correlated. Here, copula analysis is used to quantify the impact of correlation of initiating outages on the risk of cascading failure. The method is demonstrated on two test cases; a 2383-bus model of the Polish grid under varying load conditions and a synthetic 10 000-bus model based on the geography of the Western US. The large size of the Western US test case required development of new approaches for bounding an estimate of the total number of $N-3$ blackout-causing contingencies. The results suggest that both risk of cascading failure, and the relative contribution of higher order contingencies, increase as a function of spatial correlation in component failures.

Pada operasi sistem tenaga listrik, pensuplaian tenaga listrik ke konsumen dikatakan baik apabila besarnya tegangan dan frekuensi yang diterima sesuai dengan yang ditentukan dan masih dalam batas toleransinya. Load shedding atau pelepasan beban pada penyulang dilakukan secara otomatis dengan menggunakan under frequency relay (UFR). Pada penelitian ini dibuat simulasi program komputer untuk menganalisis tahapan load shedding yang digunakan oleh PT. PLN (Persero) Sektor Barito sehingga dapat diketahui respon frekuensi akhir setelah dilakukan pelepasan beban dan selanjutnya mencoba memberikan usulan tahapan peleasan beban yang lain untuk mendapatkan respon frekuensi yang baik. Pada output dari simulasi program diperlihatkan untuk pembebanan maksimum 77,9 MW, frekuensi akhirnya adalah 50,61 Hz dan untuk pembebanan minimum 53 MW, frekuensi akhirnya sebesar 50,02 Hz dengan kondisi sistem kehilangan satu unit pembangkit (skenario pertama). Kemudian untuk kondisi sistem kehilangan dua unit pembangkit terbesarnya (skenario kedua), pada pembebanan maksimum 77,9 MW dan minimum 53 MW, frekuensi akhinya masing-masing sebesar 49,7 Hz dan 50,3 Hz.

A load shedding scheme is important in a power system, especially in a microgrid or an offshore standalone power system, in which spinning reserves may be small and renewable power generation is uncertain. This paper presents a novel method for determining the shed load and delay time at each stage for under-frequency load shedding (UFLS) relays in an offshore power system near Taiwan. The Taguchi method is used to design orthogonal experiments related to different scenarios. The shed loads and delay times in a scenario are obtained by particle swarm optimization-based multiobjective programming. In the studied power system, the proposed UFLS scheme ensures less load shedding and a faster frequency response than the traditional UFLS scheme.

When developing designs of mixing heat exchangers used in low-pressure regeneration system for turbines with power from 200 to 1200 MW of TPPs and NPPs, special attention is paid to protecting the turbine flow parts from dripping moisture. Many years of work of JSC "NPO CKTI" on the research, development and implementation of low-pressure heaters (LPH) have shown that their installation in the vacuum zone of the condensate path, as well as in the zone of relatively low overpressure, ensures the maximum cost-efficiency and reliability of the turbine plant regeneration systems. However, an insignificant difference in operating pressures in the LPH and the heating steam from steam turbine extractions, typical for connection options for heaters, requires the development of additional organizational and technical measures to prevent water from entering the turbine. For stationary operating modes, there are two stages of protection against rising levels in the apparatus, providing reliable removal of water through the emergency overflow system or by stopping condensate pumps. In cases of emergency load dump of a turbine unit, the process of increasing the level in the LPH is much faster, up to boiling the entire volume of condensate. The article discusses the possible conditions for the formation and penetration of droplet moisture into the flow part of the turbine. Analysis of well-known field and laboratory studies of the operation of LPH in the most unfavorable operating conditions (in particular, load shedding of a turbine unit) is carried out. A description of the process of boiling water in mixing LPH during turbine load shedding is given. A variant of methodology for estimating the time of swelling of the water level in mixing LPH is proposed. The presented theoretical justifications make it possible to estimate the time of formation and growth of bubbles in deaerated water. The physical process under study is characteristic of the operating conditions of mixing heaters of the low-pressure regeneration system of turbine units and is of interest from the point of view of substantiating the action speed of the system for turbine protection from moisture entering the turbine with a return steam flow.

The prior studies have investigated the influence of internal hydrogen on dwell-fatigue behavior of near-α titanium alloys primarily in the lamellar microstructural condition. In the current study, the effects of internal hydrogen, in the range 10–230 ppm (by weight), on the dwell-fatigue behavior of Ti-6242Si alloy were investigated. The examined alloy had a bimodal microstructure comprising approximately 70 vol% primary α grains and 30 vol% transformed β regions. The dwell-fatigue life generally increased with increasing hydrogen content. The dwell-fatigue lives were longer by a factor of as high as 6 for high (≥150 ppm) hydrogen contents than for the low ( 150 ppm) hydrogen contents. Specifically, these facets were inclined at ∼8 – 17° from the basal plane. Therefore, the longer dwell-fatigue lives observed for the alloys with hydrogen contents ≥150 ppm could not be explained on the basis of any differences in crystallography of the facets at crack-initiation sites. The longer dwell-fatigue lives for higher hydrogen contents can be explained within the framework of time-dependent load shedding from the soft microtextured regions (MTRs) to the hard MTRs if the local stress redistribution at the soft MTR/hard MTR boundary due to the hold at maximum load is reduced with increasing hydrogen content.