Market-Oriented Joint Optimal Dispatch Strategy for Virtual Power Plants Considering Management Costs

A cohort mortality study was conducted of 123,401 industrial radiographers in the United States to estimate risks following protracted radiation exposures. The cohort was constructed from the Nuclear Regulatory Commission Radiation Exposure Information Reporting System and the Landauer, Inc. dosimetry databases. Workers were monitored between 1939 and 2011 and were exposed mainly to external gamma radiation from 192Ir and 60Co. Causes of death were obtained from the National Death Index and state mortality files with follow-up through 2019. The mean duration of follow-up was 27.7 years. Nearly 19% of workers were monitored for more than 10 years. There were 30,617 (24.8%) who worked at shipyards and 5,071 (4.1%) at nuclear power plants with the potential for asbestos exposure. The mean radiation dose to the red bone marrow (RBM) was 15.2 mGy (maximum 1.24 Gy; percent >100 mGy was 3.6%), 17.2 mGy to lung, 18.1 mGy to colon, 11.9 mGy to brain, and 18.1 mGy to heart. Overall, 30,537 deaths occurred; the Standardized Mortality Ratio and 95% confidence interval for all-cause mortality was 0.92 (0.91, 0.93); for all solid cancers 1.01 (0.99, 1.03; n = 7,734); for ischemic heart disease (IHD) 0.83 (0.81; 0.85; n = 5,820); for cerebrovascular disease (CeVD) 0.88 (0.83, 0.93; n = 1,257); for mesothelioma 6.08 (5.35, 6.89; n = 248); and for asbestosis 13.4 (11.2, 15.9; n = 134). The linear excess relative risk (ERR) per 100 mGy (95% CI) for leukemia (excluding CLL) was 0.45 (0.05, 0.85) and for non-Hodgkin lymphoma (NHL) was 0.33 (0.04; 0.62). For all solid cancers it was 0.06 (0.02, 0.10); lung cancer 0.11 (0.04, 0.19); all solid cancers excluding lung cancer and mesothelioma 0.02 (-0.03, 0.07); Parkinson's disease 0.24 (-0.13, 0.61); IHD -0.03 (-0.06, 0.01); and CeVD 0.05 (-0.08, 0.17). The ERR per 100 mGy for chronic obstructive pulmonary disease (COPD) was 0.19 (0.08, 0.30) and was similar in magnitude to that for lung cancer. This finding suggests that residual confounding by smoking may have influenced the results, warranting cautious interpretations. No significant association was found between cumulative radiation exposure and all solid cancers after excluding lung cancer and mesothelioma, nor for IHD or CeVD. The marginally non-significant increased risk of Parkinson's disease, also seen in other Million Person Study cohorts, requires further investigation. Early workers monitored entirely before 1979 had the same linear ERR per 100 mGy for solid cancers [0.06 (0.00, 0.12) n = 3,587] as for all other more contemporary workers monitored after 1978 [0.07 (0.01,0.13) n = 4,150]. This report provides convincing evidence that low-dose and low-dose-rate exposures over time significantly increases the risk of leukemia (excluding CLL) following cumulative doses up to 200 mGy while also providing information on early versus contemporary workers.

This study presents a comprehensive thermo-economic and environmental analysis of an innovative air-inlet cooling system for combined cycle power plants utilizing ice-based thermal energy storage (ITES). Designed to counteract efficiency losses in gas turbines during high-temperature periods, the system stores cooling capacity during off-peak hours and deploys it during peak demand to lower compressor inlet air temperatures. A de tailed thermodynamic model is developed and validated, followed by multi-objective optimization using genetic algorithms (GAs) to maximize exergy efficiency and minimize cost and environmental impact. The results indicate that the implementation of ITES can enhance turbine power output by up to 25% and reduce overall fuel consumption, with payback periods between 4.5 and 8 years depending on capacity. This work demonstrates the technical and economic feasibility of thermal storage integration for power augmentation in regions with high ambient temperatures.

The smart grid concept is based on the full integration of different types of energy sources and intelligent devices. Due to the short- and long-term volatility of these sources, new flexibility measures are necessary to ensure the smart grid operates stably and reliably. One option is to convert renewable energy into hydrogen, especially during periods of generation overcapacity, in order that the hydrogen that is produced can be stored effectively and used “just in time” to stabilize the power system by undergoing a reverse conversion process in gas turbines or fuel cells which then supply power to the network. On the other hand, in order to achieve a sustainable general energy system (GES), it is necessary to replace other forms of fossil energy use, such as that used for heating and other industrial processes. Research indicates that a comprehensive hydrogen supply infrastructure is required. This infrastructure would include electrolyzers, conversion stations, pipelines, storage facilities, and hydrogen gas turbines and/or fuel cell power stations. Some studies in Germany suggest that the existing gas infrastructure could be used for this purpose. Further, nuclear and coal power plants are not considered reserve power plants (as in the German case), and an additional 20–30 GW of generation capacity in H2-operated gas turbines and strong H2 transportation infrastructure will be required over the next 10 years. The novelty of the approach presented in this article lies in the development of a unified modeling framework that enables the simultaneous and coherent representation of both economic and technical aspects of hydrogen production systems which will be used for planning and pre-decision making. From the technical perspective, the model, based on the black box approach, captures the key operational characteristics of hydrogen production, including energy consumption, system efficiency, and operational constraints. In parallel, the economic layer incorporates capital expenditures (CAPEX), operational expenditures (OPEX), and cost-related performance indicators, allowing for a direct linkage between technical operation and economic outcomes. This paper describes the systematic transformation from today’s power system to one that includes a hydrogen economy, with a particular focus on practical experiences and developments, especially in the German energy system. It discusses the components of this new system in depth, focusing on current challenges and applications. Some scaled current applications demonstrate the state of the art in this area, including not only technical requirements (reliability, risks) and possibilities, but also economic aspects (cost, business models, impact factors).

The main objective of this research is to validate Axpo’s core dynamics models—based on CASMO-5, SIMULATE5 (S5), and SIMULATE-3K (S3K)—against the stability tests performed at the Leibstadt Nuclear Power Plant (KKL). The validation effort began with benchmarking the model against the stability measurements of cycle 19, as well as against solutions developed by multiple organizations that participated in an earlier benchmark organized by KKL. The validation was subsequently extended to include stability measurements from cycles 10, 13, and 38, providing a broader basis for assessing model performance. To ensure the reliability of the stability analysis, the steady-state results of S3K were systematically compared with the already validated S5 model, confirming accurate core initialization. Various parameters of interest were evaluated, and overall good agreement was observed for most parameters across the majority of tests. Further validation was performed by comparing S3K predictions with traversing in-core probe (TIP) measurements for cycles 19 and 38, demonstrating excellent consistency with plant data. In particular, the Axpo S3K model shows very good agreement at the bottom of the core and ranks among the best-performing models submitted in the KKL benchmark. Validation of key stability parameters—decay ratio and resonance frequency—confirmed the robustness of the model. Decay ratio predictions agree with measurements for all cycle 13 and cycle 19 tests and for most cycle 10 and cycle 38 tests, with remaining cases showing a systematic overprediction likely attributable to mixed-core configurations. Resonance frequency results show very good agreement, with only a slight underestimation observed for a few cycle 19 tests, consistent with trends reported in the benchmark.

This study presents an integrated experimental simulation and multi-objective optimization methodology that maximizes energy production and optimizes economic performance in the design of wind power plants (WPPs). The relationship between five fundamental design parameters (wind speed (XWS), hub height (XHH), rotor diameter (XRD), turbine spacing (XTS), and row spacing (XRS)) and five techno-economic outputs (annual AC energy (YAEP), net present value (YNPV), levelized cost of energy (YLCOE), net cost of capital (YNCCpw), and total BOS cost (YTBC)) is systematically investigated using a Multi-Level Full Factorial Experimental Design (DoE) for four different US regions (Southern Wyoming, Southern California, Northeastern West Virginia, and South Florida). The optimization was performed by applying a multi-objective desirability function to regression models derived from 1200 NREL SAM simulation data points, thereby simultaneously evaluating five design parameters across five techno-economic responses. ANOVA results revealed that 77.5% of the variability in annual energy production was due to wind speed and 21.4% to rotor diameter, clearly demonstrating the decisive role of resource quality in project feasibility. Optimization identified the optimal configuration (XRS = 5, XTS = 3, XWS = 10.157 m/s, XHH = 120 m, XRD = 70 m) that provided a balanced trade-off between conflicting objectives, achieving 575.16 GWh of YAEP, $42.02 million of YNPV, $43.66 million of YTBC, 2.368 cents/kWh of YLCOE, and $1.508/W of YNCCpw. The study emphasizes that resource evaluation precedes technological optimization in the planning phase of wind energy projects, demonstrating that integrating DoE, simulation, and multi-objective optimization provides a strong framework for achieving realistic, feasible, and economically sustainable WPPs. The novelty of this approach lies in its ability to simultaneously account for environmental stochasticity and economic feasibility, providing a robust computational roadmap for stakeholders to maximize energy efficiency while minimizing levelized costs.

River sediment metal contamination from a coal-fired thermal power plant: Spatio-seasonal variability, ecological risk and source apportionment.

Minas Gerais is Brazil’s largest charcoal producer, relying on carbonization kilns that release effluent gases and waste energy while generating environmental impacts. This work evaluates the electricity generation potential from these gases using different conversion technologies. A database-based assessment of charcoal production units, based on official institutional records, enabled estimating the energy potential for 2020 and projecting it to 2030. Three technologies were assessed: Steam Rankine Cycle, Organic Rankine Cycle, and Externally Fired Gas Turbine. For each one, efficiencies were calculated and applied to the surveyed producers, ranging from 5% to 24% for power capacities between 100 kW and 2000 kW. The highest energy generation potential, 1348 GWh/year, was obtained using the regenerative and superheated ORC with n-decane as the working fluid. In addition, an economic analysis was performed based on Brazilian electricity auction prices, together with a sensitivity analysis of key variables, including installed power, electricity price, minimum attractiveness rate, taxes, operating hours, and capital expenditure. The results demonstrate that current technical and economic conditions are unfavorable for implementing waste-heat-based power plants in Minas Gerais. Plants below 10 MW are especially unfeasible. A Life Cycle Assessment estimated emissions of 2437.7 kg CO2eq per ton of charcoal. Sustainable measures such as eliminating native wood use, increasing Gravimetric Yield, and adding afterburners could reduce emissions by over 57%.

Conversion of CO2 from power plant into CaCO3 nanoparticles

Particulate matter 2.5 is one of the primary components of air pollution. Sources of PM2.5 may be natural or anthropogenic. The main sources of the pollutants in Iraq include burning natural gas, oil, and power plants. The study is based on archived datasets from the Iraqi Meteorological Organization and Seismology and satellite data available from ECMWF and NASA for a ten-year period in Baghdad and Basra Airdromes. The spatial and temporal analysis showed that the highest frequency of thunderstorms occurs in April about 64.03%. The highest annual frequency of thunderstorms was for Baghdad Airport station in 2018 and 2002 (20 days) and Basra Airport station in 2003 and 2018 (13 days). The PM2.5 concentration at Baghdad Airport and Basra Airport stations prior to, during, and following the storm was of the category D of the air quality indices. The concentration kept growing without addressing the causes. It looks like the rise in PM2.5 concentrations that thunderstorms increased in the station is caused by arid thunderstorms and the storm's downdrafts, which lift dust upwards. This leads to PM2.5 concentrations remaining in the atmosphere for a longer period. As the Normalized Difference Dust Index results indicate, 90–95% of Baghdad is situated in areas with moderate dust levels for the period 2000-2019, while 95% or more of Basra is situated in areas with moderate to high dust levels for the same period.

Pioneer plants drives initial pedogenesis in fly ash: Mechanisms of iron mineral transformation and microbial community reorganization.

Performance enhancement of nuclear power plant cooling towers through gradient droplet configuration and coordinated water distribution strategy

A self-organized fuzzy neural model for the pressurizer system in nuclear power plants

Thermal discharge exerts limited effects on sediment prokaryotic community compositions but markedly enhances oxidative phosphorylation as revealed by metatranscriptomics.

Developing temporal coupling of human performance, physical twin, and digital twin models for probabilistic risk assessment in nuclear power plants

A surrogate-assisted evolutionary algorithm for robust scheduling of nuclear power plant construction under project risk interactions

Perspective of the effect of caesium on nitrogen transport in the aquatic insect body of Kamimuria tibialis (Plecoptera) and Epeorus latifolium (Ephemeroptera).

Design and evaluation of a smart inline micro-hydro power plant for fluid transmission networks with adaptive control and self-cleaning capabilities

Long-term atmospheric cadmium deposition and its time-lagged response to policy measures in southern China.

Because the cost of installing solar power plants is relatively large, careful planning and design is needed, including the calculation of load needs and the determination of capacity and placement of solar power plants so that the system can work effectively and efficiently. This research aims to determine the capacity of solar power plants to supply the existing load economically in the Medan State Polytechnic building based on the availability of existing land. The data obtained was processed using HOMER software to simulate the optimal capacity of solar PV. Furthermore, an economic analysis was carried out. The results of the study show that solar power plants are one of the alternative solutions to support energy efficiency while supporting the campus's commitment to the application of new and renewable energy