Search Results (27)

While traditional risk importance measures in probabilistic risk assessment are effective for ranking safety-significant components, they often overlook critical aspects such as the timing of accident progression and consequences. Dynamic probabilistic risk assessment offers a framework to quantify such risk information, but standardized approaches for estimating risk importance measures remain underdeveloped. This study addresses this gap by: (1) reviewing traditional risk importance measures and their regulatory applications, highlighting their limitations, and introducing newly proposed risk-triplet-based risk importance measures, consisting of timing-based worth, frequency-based worth, and consequence-based worth; (2) conducting a case study of Level 2 dynamic probabilistic risk assessment using the Japan Atomic Energy Agency’s RAPID tool coupled with the severe accident code of MELCOR 2.2 to simulate a station blackout scenario in a boiling water reactor, generating probabilistically sampled sequences with quantified timing, frequency, and consequence of source term release; (3) demonstrating that the new risk importance measures provide differentiated insights into risk significance, enabling multidimensional prioritization of systems and mitigation strategies; for example, the timing-based worth quantifies the delay effect of mitigation systems, and the consequence-based worth evaluates consequence-mitigating potential. This study underscores the potential of dynamic probabilistic risk assessment and risk-triplet-based risk importance measures to support risk-informed and performance-based regulatory decision-making, particularly in contexts where the timing and severity of accident consequences are critical. Full article

To provide reliable safety margins in reactor design and safety analysis, the best estimate plus uncertainty (BEPU) analysis, which is recommended by the International Atomic Energy Agency (IAEA), has drawn increasing attention worldwide. In order to systematically evaluate the sensitivity and uncertainty in the design and safety analysis of molten salt reactors (MSRs), a sensitivity and uncertainty analysis framework has been developed by integrating the reactor system safety analysis code RELAP5-TMSR with the data analysis code RAVEN. The framework is tested using the transient scenarios of the molten salt reactor experiment (MSRE): reactivity insertion accident (RIA) and station blackout (SBO). The testing results demonstrate that the proposed framework effectively conducts sensitivity and uncertainty analysis. Sensitivity analyses identify key input parameters, including the primary exchanger parameters, air radiator parameters, initial temperatures, delayed neutron parameters and volumetric heat capacity of the INOR-8 alloy. Uncertainty quantification provides 95% confidence intervals for the figures of merit (FOMs) and the steady-state and RIA scenarios remained within safety limits. The developed framework enables automated, efficient, and high-capacity sensitivity and uncertainty analysis across multiple parameters and transient scenarios. The systematic analysis provides sensitivity indicators and uncertainty distributions, offering quantitative insights into the safety margins and supporting the design and safety analysis of MSRs. Full article

The 2023–2024 blackouts in Quito, Ecuador, led to severe air quality deterioration, primarily driven by diesel generator use and increased vehicular traffic. This study analyzed data from seven urban and peri-urban monitoring stations, applying meteorologically normalized data and machine learning models (Boosted Regression Trees and Random Forests) to isolate the direct impact of blackouts on pollutant concentrations. The results revealed that PM₁₀ increased by up to 45% and PM_2.5 by 30%, frequently exceeding regulatory limits, particularly in industrial and residential zones. SO₂ exhibited the most extreme rise, surging by 390%, with peak values reaching 500 µg/m³ in areas heavily reliant on high-sulfur diesel generators. The NO₂ concentrations exceeded 200 µg/m³ in high-traffic areas, while O₃ showed dual behavior, decreasing in urban cores due to titration effects but increasing by 15% in suburban valleys, driven by photochemical interactions. A comparison between 2023 and 2024 blackouts highlighted worsening pollution trends, with longer (8–12 h) outages in 2024 causing severe environmental impacts. The findings demonstrate that blackouts significantly worsen air quality, posing critical public health risks. This study underscores the urgent need for policy interventions to mitigate the environmental impact of energy disruptions. Key recommendations include stricter fuel quality standards, diesel generator emission controls, and an accelerated transition to renewable energy. These results provide scientific evidence for future environmental regulations, supporting sustainable air quality management strategies to minimize future energy crises’ health and ecological consequences. Full article

Four severe nuclear accident scenarios have been identified for operating nuclear power plants (ONPPs). However, there is a research gap in predicting the mid–long-term radiation doses for these scenarios. This study aims to address this gap by proposing a novel approach for predicting the mid–long-term radiation dose in the case of a hypothetical short-term station blackout (STSBO) scenario, one of the aforementioned scenarios. Firstly, the Weather Research and Forecasting (WRF) model was coupled with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (WRF-HYSPLIT) model to establish an atmospheric transport and diffusion model for airborne radionuclides, and the regularity of the atmospheric transport and diffusion for the airborne radionuclides was determined. Subsequently, the Residual Radioactive Material Guidelines (RESRAD) OFFSITE (RESRAD-OFFSITE) code was utilized to establish a radiation dose model for predicting the mid–long-term radiation dose resulting from the airborne radionuclides, and the evolution of the mid–long-term radiation dose was analyzed. Finally, the proposed approach was applied to an ONPP, and the results were used to predict the mid–long-term public radiation dose. The results indicated that the total radiation dose would be lower than the dose limit recommended by the International Commission on Radiological Protection (1 mSv/yr) from the second month to the 100th year after the hypothetical STSBO nuclear accident, and the total radiation dose would decrease slowly over time. Recommendations are made for offsite emergency response measures. These research findings can assist ONPPs in analyzing their environmental impacts in the event of an STSBO scenario. Full article

In a pressurized water reactor (PWR) during a loss of coolant accident (LOCA) or a station blackout (SBO) accident, water and steam are released into the containment building. The water vapor mixes with the atmosphere, partially condensing into droplets or condensing on the containment walls. Although a significant amount of water vapor condenses, it coexists with hydrogen generated by the reactor core oxidation. As water vapor condenses, the volume fraction of hydrogen increases, raising the risk of explosion or flame acceleration. As such, water vapor’s behavior directly affects hydrogen distribution. To conservatively evaluate hydrogen safety in a PWR during a severe accident, lumped-parameter codes have been heavily used. As a best-estimate approach for hydrogen safety analysis in a PWR containment, a turbulence-resolved CFD code called contain3D has been developed. This paper presents the validation results of the code and simulation results of hydrogen behavior affected by water vapor condensation and hydrogen removal by passive autocatalytic recombiners (PARs) in the APR1400 containment. The results provide insight into the three-dimensional behaviors of the hydrogen in the containment. Full article

Global warming increases the risk of power outages. Mine water pumping stations pump approximately 100 million m³ of water per year (2023). The cessation of mine water pumping would expose neighboring mines and lower lying areas to flooding. The pumping stations have some containment, but a prolonged shutdown could cause environmental problems. Remediation of the resulting damage would be costly and time-consuming. The combination of the problems of dewatering abandoned mines and storing energy in the form of hydrogen to ensure continuity of power supply to pumping stations has not been the subject of extensive scientific research. The purpose of this paper was to develop options for protecting mine water pumping stations against the “blackout” phenomenon and to assess their investment relevance. Six technically feasible options for the modernization of mine water pumping stations were designed and analyzed in the study. All pumping station modernization options include storage of the generated energy in the form of green hydrogen. For Q1 2024 conditions, the option with the partial retail sale of the produced hydrogen and the increased volume of produced water for treatment is recommended for implementation. Full article

Remotely performing real-time distributed generation control and a demand response is a basic aspect of the grid ancillary services provided by grid operators, both the transmission grid operators (TSOs) and distribution grid operators (DNOs), in order to ensure that voltage, frequency and power loads of the grid remain within safe limits. The stochastic production of electrical power to the grid from the distributed generators (DGs) from renewable energy sources (RES) in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the efforts of the DNOs to keep the grid’s operation within safe limits and prevent cascading blackouts while staying in compliance with the SAIDI and SAIFI indices during repair and maintenance operations. Also taking into consideration the aging of the existing grid infrastructure, and making it more prone to failure year by year, it is yet of great significance for the DNOs to have access to real-time feedback from the grid’s infrastructure—which is fast, has low-cost upgrade interventions, is easily deployed on the field and has a fast response potential—in order to be able to perform real-time grid management (RTGM). In this article, we present the development and deployment of a control system for DG units, with the potential to be installed easily to TSO’s and DNO’s substations, RES plants and consumers (i.e., charging stations of electric vehicles). This system supports a hybrid control mechanism, either via ripple signaling or through a network, with the latter providing real-time communication capabilities. The system can be easily installed on the electric components of the grid and can act as a gateway between the different vendors communication protocols of the installed electrical equipment. More specifically, a commercially available, low-cost board (Raspberry Pi) and a ripple control receiver are installed at the substation of a PV plant. The board communicates in real-time with a remote server (decision center) via a 5G modem and with the PV plants inverters via the Modbus protocol, which acquires energy production data and controls the output power of each inverter, while one of its digital inputs can be triggered by the ripple control receiver. The ripple control receiver receives on-demand signals with the HEDNO, triggering the digital input on the board. When the input is triggered, the board performs a predefined control command (i.e., lower the inverter’s power output to 50%). The board can also receive control commands directly from the remote server. The remote server receives real-time feedback of the acquired inverter data, the control signals from the ripple control receiver and the state and outcome of each performed control command. Full article

Electric vehicles have become a crucial component of modern power systems, possessing substantial energy reserves that can be important power supplies in blackouts where the power grid has weak reserves or limited connections to other grids. In order to clarify the technical conditions and control methods of the centralized electric vehicle charging station as the black-start power source of the power grid, assuming that the centralized electric vehicle charging station can be considered a single, large-scale energy storage system, this paper proposes a three-stage coordinated recovery strategy based on the centralized electric vehicle charging station. The strategy involves three distinct stages, beginning with the establishment of AC frequency and voltage by the electric vehicle charging station to initiate the auxiliary load of the power plant. In the middle stage, considering the traditional generator has been connected, the charging station’s control mode is set to provide constant active and reactive power output, providing extra voltage and frequency support to the grid-connected generating units and crucial loads. Finally, in the later stage, control strategies are tailored to the charging power stations’ capacities, with one group of additional oscillation damping controllers, while the other group adopts additional frequency control to decrease power disturbances, ensuring a smooth recovery of the power grid. A PSCAD/EMTDC-based model was constructed to verify the proposed coordinated grid recovery strategies. The results demonstrated that the centralized station successfully established the voltage and frequency of the AC system, and the designed additional controller also made the recovery process much more stable. Full article

With the emergence of the smart grid, the distribution network is facing various problems, such as power limitations, voltage uncertainty, and many others. Apart from the power sector, the growth of electric vehicles (EVs) is leading to a rising power demand. These problems can potentially lead to blackouts. This paper presents three meta-heuristic techniques: grey wolf optimization (GWO), whale optimization algorithm (WOA), and dandelion optimizer (DO) for optimal allocation (sitting and sizing) of solar photovoltaic (SPV), wind turbine generation (WTG), and electric vehicle charging stations (EVCSs). The aim of implementing these techniques is to optimize allocation of renewable energy distributed generation (RE-DG) for reducing active power losses, reactive power losses, and total voltage deviation, and to improve the voltage stability index in radial distribution networks (RDNs). MATLAB 2022a was used for the simulation of meta-heuristic techniques. The proposed techniques were implemented on IEEE 33-bus RDN for optimal allocation of RE-DGs and EVCSs while considering seasonal variations and uncertainty modeling. The results validate the efficiency of meta-heuristic techniques with a substantial reduction in active power loss, reactive power loss, and an improvement in the voltage profile with optimal allocation across all considered scenarios. Full article

The impressed current cathodic protection (ICCP) scheme is a more reliable and efficient method of corrosion prevention mechanism than the sacrificial method. Currently, the grid connected transformer rectifier units supported with a battery banks are used for the ICCP-based corrosion protection system in the desalination plant. This conventional method is entirely grid-dependent, more expensive, and suffers during prolonged grid failure. The present trend of industrialization is the application of multi-renewable energy sources based on a nanogrid to power the station’s auxiliary power supply. This paper introduces a concept of distributed energy resources (DERs) operated integrated nanogrid (ING) system to provide a stable power supply solution to the ICCP scheme. A 100-million-litter per day capacity-based seawater desalination plant (SWDP) in India has been chosen as the test station. The conceptual hardware design and operational logic details for smooth integration of the integrated nanogrid module into the ICCP scheme of the Desalination plant is proposed. This research aims to investigate the behaviour of DERs during on-grid, off-grid and switching over from one mode of operation to another and vice-versa by using the accelerated Gauss–Seidel method in ETAP software (version 16.0.0). The simulation results confirm that the ING suffers from a high-frequency change rate during islanded operation, and in some cases, a complete blackout occurs. A PLC-based Smart Versatile ING Controller has been suggested to overcome the blackout issue. Finally, it has been proven that the stability of an industrial power system can be improved further by introducing the ING module into it. Full article

The strongest X-class solar flare (SF) event in 24th solar cycle, X9.3, occurred on 6 September 2017, accompanied by earthward-directed coronal mass ejections (CMEs). Such space weather episodes are known to cause various threats to human activities ranging from radio communication and navigation disturbances including wave blackout to producing geomagnetic storms of different intensities. In this study, SFs’ ionospheric impacts and effects of accompanied heliospheric disturbances on primary cosmic rays (CR) are investigated. This work offers the first detailed investigation of characteristics of these extreme events since they were inspected both from the perspective of their electromagnetic nature, through very low frequency (VLF) radio waves, and their corpuscular nature of CR by multi-instrumental approach. Aside data recorded by Belgrade VLF and CR stations, data from GOES and SOHO space probes were used for modeling and analysis. Conducted numerical simulations revealed a significant change of ionospheric parameters (sharpness and effective reflection height) and few orders of magnitude increase of electron density. We compared our findings with those existing in the literature regarding the ionospheric response and corresponding parameters. In addition, Forbush decrease (FD) magnitude, corrected for magnetospheric effect, derived from measurements, and one predicted from power exponents used to parametrize the shape of energetic proton fluence spectra at L1 were compared and found to be in good agreement. Presented findings could be useful for investigation of atmospheric plasma properties, particles’ modeling, and prediction of extreme weather impacts on human activities. Full article

After the massive integration of distributed energy resources, energy storage systems and the charging stations of electric vehicles, it has become very difficult to implement an efficient grid energy management system regarding the unmanageable behavior of the power flow within the grid, which can cause many critical problems in different grid stages, typically in the substations, such as failures, blackouts, and power transformer explosions. However, the current digital transition toward Energy 4.0 in Smart Grids allows the integration of smart solutions to substations by integrating smart sensors and implementing new control and monitoring techniques. This paper is proposing a hybrid artificial intelligence multilayer for power transformers, integrating different diagnostic algorithms, Health Index, and life-loss estimation approaches. After gathering different datasets, this paper presents an exhaustive algorithm comparative study to select the best fit models. This developed architecture for prognostic (PHM) health management is a hybrid interaction between evolutionary support vector machine, random forest, k-nearest neighbor, and linear regression-based models connected to an online monitoring system of the power transformer; these interactions are calculating the important key performance indicators which are related to alarms and a smart energy management system that gives decisions on the load management, the power factor control, and the maintenance schedule planning. Full article

Following the recent surge in harnessing clean energy sources to fast-track carbon neutrality, renewable and nuclear energies have been the best-rated sources of clean energy. Even though renewable energy presents an almost insignificant risk to public health and the environment, they are insufficient to support the growing demand for the high energy required for industrialization. Despite the competitive potential of nuclear energy to meet these demands, public concerns about its safety have significantly hindered its mass deployment in developing countries. Therefore, one of the primary considerations in commissioning a nuclear power plant is the establishment of emergency planning zones based on the reactor type and other siting criteria. Based on Ghana’s reactor type assessment (RTA), four reactor designs were considered in this study which are APR1400, HPR1000, VVER1200, and Nuscale Power Module. Using the NRC’s SNAP/RADTRAD and RASCAL codes, this research sought to investigate radionuclide doses released at the Exclusion Area Boundary (EAB), Low Population Zone (LPZ), Control room (CR), and the 16 km recommended public safe zone during Fuel handling Accidents (FHA), Rod Ejection Accident (REA), and Long-Term Station Blackout (LTSBO). The results revealed that reactors’ power contributed to the source term activities and offsite consequences during REA and LTSBO, while FHA was predominantly affected by the number of fuel assemblies and a fraction of damaged fuel. Additionally, the accidents considered in this study followed a similar trend of impact in decreasing order of reactor power and the number of fuel assemblies; APR1400 < VVER1200 < HPR1000 < Nuscale. Nevertheless, all the doses were within regulatory limits. Full article

A comprehensive uncertainty analysis in the event of a severe accident in a two-loop pressurized water reactor is conducted using an uncertainty package integrated in the ASYST code. The plant model is based on the nuclear power plant (NPP) Krško, a Westinghouse-type power plant. The station blackout scenario with a small break loss of coolant accident is analyzed, and all processes of the in-vessel phase are covered. A best estimate plus uncertainty (BEPU) methodology with probabilistic propagation of input uncertainty is used. The uncertain parameters are selected based on their impact on the safety criteria, the operation of the NPP safety systems and to describe uncertainties in the initial and boundary conditions. The number of required calculations is determined by the Wilks formula from the desired percentile and confidence level, and the values of the uncertain parameters are randomly sampled according to appropriate distribution functions. Results showing the thermal hydraulic behaviour of the primary system and the propagation of core degradation are presented for 124 successful calculations, which is the minimum number of required calculations to estimate a 95/95 tolerance limit at the 3rd order of the Wilks formula application. A statistical analysis of the dispersion of results is performed afterwards. Calculation of the influence measures shows a strong correlation between the decay heat and the representative output quantities, which are the mass of hydrogen produced during the oxidation and the height of molten material in the lower head. As the decay heat increases, an increase in the production of hydrogen and the amount of molten material is clearly observed. The correlation is weak for other input uncertain parameters representing physical phenomena, initial and boundary conditions. The influence of the order of the Wilks formula is investigated and it is found that increasing the number of calculations does not significantly change the bounding values or the distribution of results for this particular application. Full article

This study proposes a grid-connected inverter for photovoltaic (PV)-powered electric vehicle (EV) charging stations. The significant function of the proposed inverter is to enhance the stability of a microgrid. The proposed inverter can stabilize its grid voltage and frequency by supplying or absorbing active or reactive power to or from a microgrid using EVs and PV generation. Moreover, the proposed inverter can automatically detect an abnormal condition of the grid, such as a blackout, and operate in the islanding mode, which can provide continuous power to local loads using EV vehicle-to-grid service and PV generation. These inverter functions can satisfy the requirements of the grid codes, such as IEEE Standard 1547–2018 and UL 1741 SA. In addition, the proposed inverter can not only enhance the microgrid stability but also charge EVs in an appropriate mode according to the condition of the PV array and EVs. The proposed inverter was verified through experimental results with four scenarios in a lab-scale testbed. These four scenarios include grid normal conditions, grid voltage fluctuations, grid frequency fluctuations, and a power blackout. The experimental results demonstrated that the proposed inverter could enhance the microgrid stability against grid abnormal conditions, fluctuations of grid frequency and voltage, and charge EVs in an appropriate mode. Full article