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In systems in which many heterogeneous agents operate autonomously, with competing goals and without a centralized planner or global information repository, safety and performance can only be guaranteed by "social" rules imposed on the behavior of individual agents. Social laws are structured in a way that they can be verified just by using local information made available to an agent by a small number of its neighbors. Automobile mobility with traffic rules and logistics robots in warehouses are canonical examples of such "regulated autonomy", but many other fairly-competing autonomous systems are to be expected shortly. In these systems, detecting whether an agent is not abiding by the rules is crucial for raising an alert and taking appropriate countermeasures. However, the limited visibility due to the local nature of the information makes the problem of misbehavior detection hard for any single agent, and only an exchange of information between agents can provide sufficient clues to arrive at a decision. This paper attacks the misbehavior detection problem for a class of socially organized autonomous systems, where the behavior of agents depends on the presence or absence of other neighbors. We propose a solution involving a "local monitor", which runs on each agent and includes a hybrid observer and a set-valued consensus node. Based on whatever visibility is available, it reconstructs a set-valued occupancy estimate of nearby regions and combines it with communicating neighbors to reach a shared view and a mismatch discovery. We provide a formal framework for describing social rules that unify many different applications and a tool to generate code automatically for local monitors. The technique is demonstrated in various systems, including self-driving cars, autonomous forklifts, and distributed power plants. [ABSTRACT FROM AUTHOR]

This work aims to analyse the performance of the SUT power plant in the environmental conditions of Nagpur and develop machine learning (ML) model to predict the power output of the SUT power plant. The developed ML model readily predicts the power output without rigorous calculations. Regularised polynomial regression with multiple variables technique was used to develop the ML model. Optimum values of the regularisation parameter, degree of the polynomial and the number of training examples were obtained from learning curves. A mathematical model of the SUT power plant is developed for analysing the performance of the SUT power plant and collecting training datasets for the ML regression model. The mathematical model analysed the effect of variation in chimney height, chimney and collector radius on SUT's performance and flow parameters. The results demonstrate that raising the height and radius of the chimney and collector radius enhances the power generation of the SUT power plant. The monthly average power output was observed to be maximum in June and July and minimum in December. Calculation of the power output is done from 5.00 AM to 6 PM. The maximum power production in June is 120 kW and in May is 117 kW. The average annual power output is around 64 kW. [ABSTRACT FROM AUTHOR]

SUMMARY STATEMENT: This article explores the dual benefits of reducing lignin content in plants, which streamlines biofuel production while maintaining robust defence mechanisms. It discusses how plants compensate for lower lignin levels through alternative defence strategies, recent biotechnological advances in lignin modification, and the implications for agriculture and industry. [ABSTRACT FROM AUTHOR]

This study aimed to assess the characteristics of particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) from various stationary and mobile emission sources in Taiwan, with a focus on source apportionment and associated health risks. The northern power plant, equipped with bag filters operating at 150 °C, had significantly lower FPM and CPM levels (0.44 and 0.13 mg/m3, respectively) compared to the central and southern power plants, which used electrostatic precipitators operating at 250 °C (FPM, 1.45–8.35 mg/m3; CPM, 2.37–3.73 mg/m3). Additionally, emissions from diesel vehicles under both idle and high-speed conditions exhibited higher FPM levels (3.46–4.67 mg/m3) than gasoline vehicles (0.19–0.40 mg/m3). In terms of PAH toxicity, diesel vehicle emissions had significantly higher BaP-TEQ (87.3 ng/m3) and BaP-MEQ (25.9 ng/m3) levels compared to power plants (BaP-TEQ, 5.49 ng/m3; BaP-MEQ, 2.65 ng/m3). The highest ambient concentrations of PM2.5, BaP-TEQ, and BaP-MEQ were recorded at traffic sites, with values of 48 ± 36 µg/m3, 0.29 ng/m3, and 0.11 ng/m3, respectively. Differences in PAH distributions between stationary and mobile sources were influenced by factors such as pollution control technologies, combustion temperatures, and fuel types. Diesel vehicle emissions were dominated by benzo[g,h,i]perylene (BghiP), indeno[1,2,3-cd]pyrene (IND), benzo[a]pyrene (BaP), and benzo[b]fluoranthene (BbF) under idle conditions, while phenanthrene (PA), pyrene (Pyr), and BghiP were prevalent under high-speed conditions. Source apportionment conducted using principal component analysis (PCA) and positive matrix factorization (PMF) identified diesel and gasoline vehicles as the dominant contributors to atmospheric PAHs in Taiwan, accounting for 38% of the total, followed by coal-fired power plants at 35%. The highest lifetime excess cancer risk (ECR) of 2.5 × 10⁻5 was observed in traffic-dense areas, emphasizing the public health implications of vehicle emissions. The study adds credibility to the source apportionment findings, and the health risk analysis highlights variations across different regions, including traffic, urban, rural, and background zones. [ABSTRACT FROM AUTHOR]

The paper presents an approach to use the associated gases from geothermal water deposits for electric and thermal energy cogeneration in centralized distribution systems. [ABSTRACT FROM AUTHOR]

Inverse data envelopment analysis (DEA) method is a useful tool for analyzing the optimization of resource allocation of a set of homogeneous decision-making units (DMUs). However, the assumption of homogeneity for DMUs is not necessarily applied in reality. For example, universities with the same input structure cultivate students with different orientations; power plants consume different resources to generate electricity. Therefore, how to handle nonhomogeneous DMUs in inverse DEA becomes an issue when analyzing the optimization of resource allocation. In this study, an inverse DEA method for nonhomogeneous DMUs under constant returns to scale (CRS) is proposed to handle the aforementioned issue. Furthermore, the inverse DEA method for nonhomogeneous DMUs is extended to the case of variable returns to scale (VRS). The adjustment range of inputs-outputs under VRS is discussed to avoid the problem of infeasibility, and relevant properties of our method are proved. Moreover, the effect of frontier changes on the proposed method is also discussed. Finally, numerical examples are provided to illustrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

The present study focuses on the harris hawks optimizer. harris hawks optimization (HHO) is introduced based on population and nature patterns. The HHO algorithm imitates harris hawks attacking behavior and includes two phases called exploration and exploitation, which can be modeled with three strategies, 1) discovering the prey, 2) surprising attack, and 3) prey attack. The main purpose of using this type of algorithm is to optimally solve the short-term hydro-thermal self-scheduling (STHTSS) problem with wind power(WP), photovoltaic (PV), small hydro (SH) and pumped hydro storage (PHS) powr plants while considering uncertainties such as energy prices, ancillary services prices, etc, in the energy market. It will be shown how energy generation companies can use this algorithm and other algorithms and innovative methods that will be introduced in the future to achieve profit maximum with careful scheduling. It is worth mentioning that in this study, the effect of the presence and absence of two important factors, namely valve load cost (VLC) effect and prohibited operating zones (POZs) (with linear modeling) that can affect the profit of units (power plants) has been pointed out. Finally, as shown in this study, several tests perfomed on the IEEE118-bus system validate the precision and credibility of the harris hawks optimization algorithm. [ABSTRACT FROM AUTHOR]

In this paper, virtual power plant (VPP) planning is done using distributed generation sources to create a safe platform for electricity exchange and to increase the profitability and sustainability of electricity. In the proposed model, the effect of micro-grid interaction with the electricity market in the presence of distributed generation resources and storage is investigated. To solve this problem, an improved artificial bee colony algorithm using the accept-reject method (AR-ABC) is used. The AR method is employed to limit the initial search space as well as for the scenario reduction process. Also, uncertainties related to loads and renewable sources are formulated in a sample micro-grid including micro-turbine (MT), fuel cell (FC), wind turbine (WT), photovoltaic cells (PV) and batteries for storage; the results are compared with those of other methods, which shows this method works better than others. The software simulations of this research are done in the MATLAB software environment. [ABSTRACT FROM AUTHOR]

The study's objective is to evaluate and compare the sustainability of power production techniques for India's transition to clean power generation. It specifically focuses on coal-based power generation with emission control technologies, flue gas desulfurization (FGD) with carbon capture and storage (CCS), and compares it with solar photovoltaic (PV) systems. The study conducted a life cycle assessment (LCA) to determine the environmental impact of electricity generation in each scenario. Inventory data has been collected for each case through plant visits, emission modelling, and literature searches. The study evaluated midpoint and endpoint impact indicators utilizing the ReCiPe (H) assessment methodology. The economic viability of all the cases was determined by calculating the levelized cost of electricity (LCOE). The results showed that retrofitting an existing power plant with flue gas desulfurization (FGD) and carbon capture and storage (CCS) reduced efficiency by 30%, required 1.2 times more auxiliary power, and increased heat rates. The LCA results showed that the global warming potential (GwP) for FGD and CCS together was 0.614 kg CO2 eq. per kWh of power generation. On the other hand, the GwP for the solar PV system was much lower, at 0.043 kg CO2 eq. per kWh. There were trade-offs in both cases, but solar PV plants are more environmentally friendly than thermal power plants equipped with CCS systems in almost all categories. Furthermore, the LCOE results showed Rs 3.87 per kWh for an on-grid solar PV plant and Rs 5.33 for thermal power, with CCS and FGD showing solar as an economically more feasible option. Retrofitting thermal power facilities with emission control technology is necessary to achieve net zero emissions, but transition to renewable energy sources is inevitable. [ABSTRACT FROM AUTHOR]

This comprehensive review examines the key role and optimization dispatch of Technical Virtual Power Plants (TVPPs) in the new energy era. This study provides an overview of Virtual Power Plants (VPPs), including their definition, development history, and classification into Technical and Commercial VPPs. It then systematically analyzes optimization methods for TVPPs from five aspects: deterministic optimization, stochastic optimization, robust optimization, and bidding-integrated optimization. For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. Through methodological classification and comparative analysis, this review aims to provide valuable insights for the design, operation, and management of TVPPs in future power systems. [ABSTRACT FROM AUTHOR]

The market for microinverters is growing, especially in Europe. Driven by rising electricity prices and an easing in legislation since 2024, the number of mini-photovoltaic energy systems (mini-PVs) being installed is increasing substantially. Indoor and outdoor studies of microinverters have been carried out at Paderborn University since 2014. In the indoor lab, conversion efficiencies as a function of load have been measured with high accuracy and ranked according to Euro and CEC weightings; the latest rankings from 2024 are included in this paper. In the outdoor lab, energy yields have been measured using identical and calibrated crystalline silicon PV modules; until 2020, measurements were carried out using 215 Wp modules. Because of increasing PV module power ratings, 360 Wp modules were used from 2020 until 2024. In 2024, the test modules were upgraded to 410 Wp modules, taking into account the increase from 600 W to 800 W of inverter power limits, which is suitable for simplified operation permission ("plug-in") in many European countries within a homogenised legislation area for such mini-photovoltaic energy systems or "balcony power plants". This legislation for simplified operation also covers overpowered mini-plants, although the maximum AC output remains limited to 800 W. Presently, yield assessments are being carried out in the outdoor lab, which will take at least a year to be valid and comparable. Kits consisting of PV modules, inverters, and mounting systems are also being evaluated. Yield rankings sometimes differ from efficiency rankings due to the use of different MPPT algorithms with different MPP approach speeds and accuracies. To accelerate yield assessment, we developed a novel, simple formula to determine energy yield for any module and inverter configuration, including overpowered systems. This is a linear approach, determined by just two coefficients, a and b, which are given for several inverters. To reduce costs, inverters will be integrated into the module frame or the module terminal box in the future. [ABSTRACT FROM AUTHOR]

Today, most of the world's electric energy is generated by burning hydrocarbon fuels, which causes significant emissions of harmful substances into the atmosphere by thermal power plants. In world practice, flue gas cleaning systems for removing nitrogen oxides, sulfur, and ash are successfully used at power facilities but reducing carbon dioxide emissions at thermal power plants is still difficult for technical and economic reasons. Thus, the introduction of carbon dioxide capture systems at modern power plants is accompanied by a decrease in net efficiency by 8–12%, which determines the high relevance of developing methods for increasing the energy efficiency of modern environmentally friendly power units. This paper presents the results of the development and study of the process flow charts of binary and trinary combined-cycle gas turbines with minimal emissions of harmful substances into the atmosphere. This research revealed that the net efficiency rate of a binary CCGT with integrated post-combustion technology capture is 39.10%; for a binary CCGT with integrated pre-combustion technology capture it is 40.26%; a trinary CCGT with integrated post-combustion technology capture is 40.35%; and for a trinary combined-cycle gas turbine with integrated pre-combustion technology capture it is 41.62%. The highest efficiency of a trinary CCGT with integrated pre-combustion technology capture is due to a reduction in the energy costs for carbon dioxide capture by 5.67 MW—compared to combined-cycle plants with integrated post-combustion technology capture—as well as an increase in the efficiency of the steam–water circuit of the combined-cycle plant by 3.09% relative to binary cycles. [ABSTRACT FROM AUTHOR]

With the increase of wind power generation, the safety and economy of power system operations are greatly influenced by the intermittency and fluctuation of wind power. To take the advantage of the complementary characteristics between different energy storage devices, a Hybrid Energy Storage System (HESS) consisting of Battery Energy Storage System (BESS) and Flywheel Energy Storage System (FESS) can alleviate the uncertainty of wind power. This article has proposed a coordinated control strategy through group consensus algorithm based on Model Predictive Control (MPC) for Hybrid Energy Storage Array (HESA) to smooth wind power fluctuations. To allocate power commands to the FESS and BESS, the fluctuation of wind power output is extracted with different frequency domain characteristics as instructions by Empirical Mode Decomposition (EMD) technology. Moreover, a group consensus algorithm based on MPC is proposed to complete the adaptive power allocation of energy storage units. Eventually, the actual wind farm data is used for the simulation to verify the effect of control strategy proposed in this paper. It can be seen that the developed group consensus algorithm based on MPC can cope with different frequency power commands, avoid overcharging and discharging of energy storage media, and smooth wind power effectively. [ABSTRACT FROM AUTHOR]

Distributed power supply has seen a significant rise because of the increasing demand for renewable energy. This rise has also presented various challenges, including independent operation and a lack of coordination among the sources. As a result of these challenges, these distributed power supplies are combined into a virtual power plant (VPP). This paper addresses these issues of interaction and coordination with a proposal for multitype VPP and modeling technology. First, it recommends establishing a peer‐to‐peer (P2P) transaction framework. Second, Nash bargaining cooperative game theory comes into play, which involves multiple stakeholders in establishing a P2P transaction framework among stakeholders. After that, this proposed model is solved using the alternating direction multipliers method (ADMM). In the end, the verification of this proposed model is achieved by the numerical example that ensures that the VPP alliance operates stably. [ABSTRACT FROM AUTHOR]

ABSTRACT Recently, battery energy storage systems (BESS) have gained importance due to the growing introduction of intermittent renewable energy power plants. Although BESS already has multiple applications, the current standard approach presents several drawbacks aggravated by the second‐life batteries use. In order to deal with this issue, the literature proposes the integration of dc/dc converters in the batteries, an approach known as smart battery. However, due to the different capacities of the batteries, the conventional control of smart battery packs does not guarantee a constant dc‐link voltage, because during operation, some dc/dc converters can reach their physical voltage limit. Therefore, this paper proposes an algorithm called offset compensation network (OCN) that guarantees constant dc‐link voltage even when there are saturated converters. Simulations in software PLECS and hardware‐in‐the‐loop experiments validate the proposal. The results prove the improvement of the technology as the possibility to operate with fixed dc‐link voltage, enabling the use of second‐life batteries, OCN algorithm reduces the SOC balancing time in 6.25% and avoids dc‐link voltage variations during the balancing process. Finally, this technology is fully compatible with current power conversion systems, allowing an easy retrofit of standard BESS. [ABSTRACT FROM AUTHOR]

With the large-scale integration of renewable energy into the grid, traditional short-circuit current (SCC) calculation methods for synchronous generators are no longer applicable to inverter-based non-synchronous machine sources (N-SMSs). Current SCC calculation methods for N-SMSs often use a single-machine multiplication method, which tends to overlook the internal variability of N-SMSs within power plants, leading to low calculation accuracy. To address this issue, this paper first derives an analytical expression for SCC in grid-connected inverters under low voltage ride through (LVRT) control strategies. Then, a single-machine steady-state SCC calculation model is proposed. Based on the classification of N-SMSs, a practical SCC calculation model for renewable power plants is introduced, balancing accuracy and computational speed. The feasibility of the model is validated through simulations. The proposed method enables simple calculations to obtain the steady-state voltage and SCC at the machine terminal, offering strong engineering practicality. [ABSTRACT FROM AUTHOR]

This article presents examples of the use of complex sheet metal in everyday life and the course of modeling a sheet bent simultaneously in two planes. The element selected to describe the modelling process is a fragment of the side wall of a lever hydroelectric power plant that operates on the Bystrzyca River in Lublin. The shape of the element is conditioned by the need to achieve a gentle change in the cross-section of the water stream during the flow between the steering system and the outflow area. The segment through which the water flows is clearly lower and wider than the other modules of the power plant, which is due to the average water level in the Bystrzyca River. Such a shape is necessary because the inflow and outflow parts of the power plant must be submerged under water all the time. This is due to the principle of operation of the power plant, which works by obtaining a vacuum created by pumping air from the inside. The article also presents the results of the strength analysis, which was performed for the segment exposed to the highest loads. The analysis and the entire design were performed in Autodesk Inventor, and the results obtained were as expected and even in the most critical places no values were reached that would require changes to the design. [ABSTRACT FROM AUTHOR]

This paper investigates energy and exergy analyses of 660 MW capacity supercritical coal power plant with single reheat and regenerative. The fuel utilized in the plant is a combination of sub‐bituminous and lignite coal. It is found that the turbine section of the system exhibits the highest energy efficiency (around 94.17%) and exergy efficiency (around 90.73%). Also, 82.07% of the total exergy destruction is found for the boiler, and the remaining 17.93% of the irreversibility is determined for the turbine, condenser, and other components. The overall cycle energy efficiency at maximum load is computed as 40.77%, while the overall cycle exergy efficiency at maximum load is found to be 39.69%. These findings provide valuable insights into the performance of the power plant and suggest the improvements needed in performance enhancement of the boiler. [ABSTRACT FROM AUTHOR]

This paper presents a "hybrid" approach to direct drive inertial confinement fusion that can exploit a high-energy gas laser with two opposed beams. The target and driver are asymmetric, much like experiments performed on the National Ignition Facility, but have been designed to benefit from scale and their particular compatibility with a fusion power plant. The imploded masses (and areal densities) are increased by a factor of 12 (3) relative to findings by Abu-Shawareb et al. [Phys. Rev. Lett. 129, 075001 (2022)] and provide a path to high-gain implosions that robustly ignite. The design also mitigates common concerns such as laser imprint and cross-beam energy transfer. We discuss the rationales for a hybrid target, the methods used to control implosion symmetry, and the implication(s) for inertial fusion energy. [ABSTRACT FROM AUTHOR]

The correct generator circuit breaker (GCB) dimensioning is essential for the safe and reliable operation of a power plant or generation system. The dimensioning is usually based on standardized calculation methods according to standards (IEC standard 60909‐0, IEC/IEEE standard 62271‐37‐013, IEEE Std C37), often supplemented by selected transient calculations. A non‐systematic approach can often be observed here, which does not adequately take into account significant influencing variables or operating states of the generator. This article therefore systematically examines various parameters that influence the short‐circuit current components of the generator and are relevant for the dimensioning of the generator circuit‐breaker: short‐circuit angle, operating point, impedance ratios, phase clearing, switching arc, and fault arc. The results of the current parameters most relevant to the dimensioning of the GCB were then compared for different calculation methods. Special attention was paid to the effect of the switching and fault arc, which were modelled as a constant arc voltage, and its effect on the short‐circuit currents is systematically recorded. This work aims to summarize all relevant variables that influence the generator short‐circuit current and are relevant for the dimensioning of the GCB and to present the different results based on a short‐circuit calculation according to the standard and transient calculation to create a basis for a proper dimensioning of the generator circuit breaker. [ABSTRACT FROM AUTHOR]

This article investigates the issue of H ∞ security output feedback control for a nonlinear networked cascade control system with deception attacks. First, to further reduce the amount of communication data, reasonably schedule network resources, and alleviate the impact of multi-channel deception attacks, an attack-dependent adaptive event-triggered mechanism is introduced into the primary network channel, and its adaptive triggered threshold can be adjusted according to the random attack probability. Secondly, the output dynamic quantization of the secondary network channel is considered. Then, a novel security cascade output feedback controller design framework based on the Takagi–Sugeno (T-S) fuzzy networked cascade control system under deception attacks is established. In addition, by introducing the Lyapunov–Krasovskii stability theory, the design conditions of the controller are given. Finally, the effectiveness and superiority of the proposed design strategies are verified by two simulation examples of power plant boiler–turbine system and power plant boiler power generation control system. [ABSTRACT FROM AUTHOR]

Mathematical modeling of combined-cycle units has produced a variety of valuable results, primarily significant advances in their energy efficiency and education of power plant operators. These positive results motivate the need for more complex modeling and simulation techniques with the goal of greater accuracy and accessibility. This study presents a simplified and enhanced version of a gas turbine model for dynamic performance simulation. The theoretical improvements have been proved through modeling philosophy and simulation accuracy attained by metaheuristic optimization techniques. The model has been constructed using thermodynamic and mathematical concepts, with parameter optimization and calibration performed using metaheuristic optimizers. The suggested model's resilience has been demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

The oil ash radioactive waste was generated from electrical power plants and it was presented great concern due to environmental impact. In this study oil ash was characterized from technical and radiological aspects. Oil ash average activity concentrations for 226Ra, 232Th, and 40K were (1718 ± 85.9, 278.1 ± 13.9, and 136 ± 6.7) Bq/kg respectively, that were higher than the worldwide average. The average value of AEDtot was (10.5 ± 0.5) mSv/y, which was higher than the dose limit of public. All the radiological parameters were higher than worldwide. The samples examined by XRF, and XRD. That contained economic elements as iron, vanadium, nickel. [ABSTRACT FROM AUTHOR]

Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO2 emissions from point sources based on Orbiting Carbon Observatory-2 and -3 (OCO-2 and OCO-3) satellite measurements, but the factors affecting CO2 flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO2 emissions from three power plants in China based on OCO-3 XCO2 measurements. Moreover, flux uncertainties resulting from wind information, background values, satellite CO2 measurements, and atmospheric stability are discussed. This study highlights the CO2 flux uncertainty derived from the satellite measurements. Finally, satellite-based CO2 emission estimates are compared to bottom-up inventories. The satellite-based CO2 emission estimates at the Tuoketuo and Nongliushi power plants are ∼30 and ∼10 kt d−1 smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) respectively, but ∼10 kt d−1 larger than the ODIAC at Baotou. [ABSTRACT FROM AUTHOR]

The DIII-D tokamak has elucidated crucial physics and developed projectable solutions for ITER and fusion power plants in the key areas of core performance, boundary heat and particle transport, and integrated scenario operation, with closing the core-edge integration knowledge gap being the overarching mission. New experimental validation of high-fidelity, multi-channel, non-linear gyrokinetic turbulent transport models for ITER provides strong confidence it will achieve Q ⩾ 10 operation. Experiments identify options for easing H-mode access in hydrogen, and give new insight into the isotopic dependence of transport and confinement. Analysis of 2,1 islands in unoptimized low-torque IBS demonstration discharges suggests their onset time occurs randomly in the constant β phase, most often triggered by non-linear 3-wave coupling, thus identifying an NTM seeding mechanism to avoid. Pure deuterium SPI for disruption mitigation is shown to provide favorable slow cooling, but poor core assimilation, suggesting paths for improved SPI on ITER. At the boundary, measured neutral density and ionization source fluxes are strongly poloidally asymmetric, implying a 2D treatment is needed to model pedestal fuelling. Detailed measurements of pedestal and SOL quantities and impurity charge state radiation in detached divertors has validated edge fluid modelling and new self-consistent 'pedestal-to-divertor' integrated modeling that can be used to optimize reactors. New feedback adaptive ELM control minimizes confinement reduction, and RMP ELM suppression with sustained high core performance was obtained for the first time with the outer strike point in a W-coated, compact and unpumped small-angle slot divertor. Advances have been made in integrated operational scenarios for ITER and power plants. Wide pedestal intrinsically ELM-free QH-modes are produced with more reactor-relevant conditions, Low torque IBS with W-equivalent radiators can exhibit predator-prey oscillations in T e and radiation which need control. High- β P scenarios with q min > 2, q 95–7.9, β N > 4, β T–3.3% and H 98y2 > 1.5 are sustained with high density ( n ¯ = 7E19 m−3, f G–1) for 6 τ E, improving confidence in steady-state tokamak reactors. Diverted NT plasmas achieve high core performance with a non-ELMing edge, offering a possible highly attractive core-edge integration solution for reactors. [ABSTRACT FROM AUTHOR]

In recent years, Poland has seen a rapid increase in installed capacity in the renewable energy sources (RES) sector. This increase mainly concerns weather-dependent sources such as PV and wind installations, whose intermittent operation destabilizes the Polish power system (PPS). The solution to fluctuations in PPS operating parameters are stable and controllable RES sources, among which demand-driven biogas plants (with an energy storage in the form of biogas) have a special development potential. The aim of this paper was to describe the construction and principles of operation of peak biogas plants and to analyze the possibilities of including them in the operation of PPS. The paper shows the fundamental differences between the operation of typical biogas plants (producing electricity and heat continuously) and demand-driven biogas plants, in which biogas production takes place continuously, while electricity production occurs periodically, during the highest demand for power during the day. It was found that demand-driven biogas plants are a promising alternative to the previously used coal-fired units, battery energy storage units and pumped-storage power plants and in the future they may act as a stabilizer of the National Power System, achieving available electrical power of up to 11.1 GW. [ABSTRACT FROM AUTHOR]

The control of heliostat is crucial for the development of solar tower power plant. Currently, most power plants use open‐loop control, which has low cost but low efficiency, closed‐loop control has high concentrating efficiency, but each heliostat requires sensors and has high cost, and Proportional‐Integral‐Derivative (PID) controller has good control effect, but the parameter adjustment is difficult and overshooting problem occurs. In this paper, we propose a DDPG‐based heliostat cluster control aimed at improving the heliostat control effect and reducing the control cost. A leader‐follower strategy is used to control the heliostat, where the whole heliostat field is divided into several groups, each group is assigned a leader heliostat, and the rest of the heliostats follow the leader heliostat to rotate. The leader acquires the control error by means of a photoelectric sensor or a camera device. The following heliographs rotate with the leader to obtain the control signal, so there is no need for sensors, which reduces the number of sensors and lowers the cost. To address the shortcomings of traditional PID, we propose a DDPG‐based PID control algorithm. The algorithm is trained to find out the optimal value at each moment, which ensures that the controller parameters are optimal at each moment. The results show that the tracking error is below 0.0001 rad for both cluster control and individual control. This ensures effective tracking performance while reducing the sensor cost. The controller based on the DDPG algorithm eliminates overshoots, reduces errors, and shortens the stabilization time by 0.5 seconds. [ABSTRACT FROM AUTHOR]

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The results of experimental and modeling studies of the distributed generation sources (DG) influence on the occurrence in the Interconnected Power System (IPS) of Ukraine asynchronous modes (AM) caused by accidents in its main electrical network are presented. According to simulation scenarios it was assumed that the DG power was introduced into electrical distribution networks instead of the power units of thermal power plants of the IPS of Ukraine which were destroyed as a result of missile attacks by the Russians. In the absence of information about DGs, certain generalizations and assumptions are made regarding the possibility of DG groups modeling of in the form of turbine generators with different inertia constants. Various scenarios of the accidents occurrence and the functioning of relay protection and anti-emergency automation devices were considered. Conducted studies results show that the DG introduction into distribution electrical networks does not contribute to the AM occurrence in the main electrical network of the IPS of Ukraine. References 11, figures 10, tables 3. [ABSTRACT FROM AUTHOR]

The energy transition towards renewable energy sources is vital for handling climate change, air pollution, and health-related problems. However, fossil fuels are still used worldwide as the main source for electricity generation. This work aims to contribute to the energy transition by exploring the best options for integrating a solar field within a combined cycle power plant. Different integration positions at the gas and steam cycles for the solar field were studied and compared under several operating conditions using a thermodynamic model implemented in MATLAB R2024a. Fuel-saving and power-boosting (flowrate and parameter boosting) strategies were studied. The results revealed that, for a maximum fuel savings of 7.97%, the best option was to integrate the field into the steam cycle before the economizer stage. With an integrated solar thermal power of 3 MW, carbon dioxide emissions from fuel combustion were reduced to 8.3 g/kWh. On the other hand, to maximize power plant generation, the best option was to integrate the field before the superheater, increasing power generation by 24.2% for a solar thermal power of 4 MW. To conclude, guidelines to select the best integration option depending on the desired outcome are provided. [ABSTRACT FROM AUTHOR]

The multi-area multi-source power system (MAMSPS), which uses a variety of power sources including gas, hydro, thermal, and renewable energy, has recently been implemented to balance the growing demand for electricity and the overall capacity for power generation. In this paper, an integral sliding mode control with a single-phase technique (ISMCSP) is applied to two areas, with each area including gas–wind–thermal power systems with HVDC system. Firstly, a two-area gas–wind–thermal power system with HVDC (TAGWTPSH) is the first model in this scheme to consider the parameter uncertainties of a MAMSPS. Secondly, sliding mode design law with a single-phase technique is introduced to alleviate chattering and oscillation problems. Then, power system stability is ensured by the Lyapunov control theory based on the new LMIs technique. Thirdly, the ISMCSP's effectiveness in a MAMSPS is also assessed under random load patterns and parameter variations regarding settling time and over-/undershoot. The ISMCSP was created to alter the fundamental sliding mode control, and therefore the suggested approach performs better than recently published approaches. This is demonstrated by the frequency overshoot deviation value in frequency deviations: 0.7 × 10−3 to 2.8 × 10−3 for the TAGWTPSH with the suggested ISMCSP. In the last case, for random changes in load from −0.4 to +0.5 p. u, the proposed ISMCSP method still stabilizes the frequency of the areas meeting the standard requirements for AGC. [ABSTRACT FROM AUTHOR]

To meet the escalating electricity demand and rising fuel costs, along with notable losses in power transmission, exploring alternative solutions is imperative. Gas turbines demonstrate high efficiency under ideal International Organization for Standardization (ISO) conditions but face challenges during summer when ambient temperatures reach 40°C. To enhance performance, the proposal suggests cooling inlet air by 15°C using a vapor absorption chiller (VAC), utilizing residual exhaust gases from a combined cycle power plant (CCPP) to maximize power output. Additionally, diverting a portion of exhaust gases to drive an organic Rankine cycle (ORC) for supplementary power generation offers added efficiency. This integrated approach not only boosts power output but also minimizes environmental impact by repurposing exhaust gases for additional operations. This study presents a detailed energy and economic analysis of a modified combine cycle power plant, in Kotri, Pakistan. R600A is used as organic fuel for the ORC while LiBr-H2O solution is used for the VAC. Two performance parameters, efficiency and energy utilization factor, Four energetic parameters, Work output of ORC, modified CCPP, original CCPP and cooling rate, and one economics parameter, payback period were examined under varying ambient conditions and mass fraction of exhaust gases from outlet of a gas turbine (ψ). A parametric investigation was conducted within the temperature range of 18°C to 50°C, relative humidity between 70% and 90%, and the ψ ranging from 0 to 0.3. The findings reveal that under elevated ambient conditions (40°C, 90% humidity) with ψ at 0, the Energy Utilization Factor (EUF) exceeds 60%. However, the ORC exhibits a low work output of 100 KW alongside a high cooling load of 29,000 kW. Conversely, the modified system demonstrates an augmented work output of approximately 81,850 KW compared to the original system's 78,500 KW. Furthermore, the integration of this system proves advantageous across all metrics. Additionally, the payback period of the system is contingent on ambient conditions, with lower conditions correlating to shorter payback periods and vice versa. [ABSTRACT FROM AUTHOR]

The coupling of solar cells and Li-ion batteries is an efficient method of energy storage, but solar power suffers from the disadvantages of randomness, intermittency and fluctuation, which cause the low conversion efficiency from solar energy into electric energy. In this paper, a circuit model for the coupling system with PV cells and a charge controller for a Li-ion battery is presented in the MATLAB/Simulink environment. A new three-stage charging strategy is proposed to explore the changing performance of the Li-ion battery, comprising constant-current charging, maximum power point tracker (MPPT) charging and constant-voltage charging stages, among which the MPPT charging stage can achieve the fastest maximum power point (MPP) capture and, therefore, improve battery charging efficiency. Furthermore, the charge controller can improve the lifetime of the battery through the constant-current and constant-voltage charging scheme. The simulation results indicate that the three-stage charging strategy can achieve an improvement in the maximum power tracking efficiency of 99.9%, and the average charge controller efficiency can reach 96.25%, which is higher than that of commercial chargers. This work efficiently matches PV cells and Li-ion batteries to enhance solar energy storages, and provides a new optimization idea for hybrid PV/Li-ion systems. [ABSTRACT FROM AUTHOR]

The high performance of the photovoltaic cell requires proper and efficient cooling because the electrical efficiency of the photovoltaic cell is affected by the operating temperature. Providing a suitable operating environment for the photovoltaic cell at a low temperature is necessary, which can be achieved using devices with highly effective thermal performance in which heat is transferred from the cell to the external surroundings via pulsating heat pipes, and this process leads to significant energy generation and the best efficiency of the photovoltaic unit. In this work, we use pulsating heat pipes with copper fins to achieve adequate cooling of the cell and make it operate at the best temperature, leading to a higher photovoltaic cell efficiency. The metal used for the pulsating heat pipes is copper, which has high conductivity needed to increase performance. The study showed that pulsating heat pipes are the most suitable options for cooling the photovoltaic cell, which leads to increasing its efficiency and increasing electricity production. [ABSTRACT FROM AUTHOR]

The low-voltage distribution network (LVDN) is the final stage in delivering electric energy from power plants to consumers, and its operational condition greatly impacts many power users. While medium-voltage and high-voltage distribution networks can be managed through intelligent digital systems, load imbalance issues in LVDNs often rely on planners' experience, leading to significant limitations. With advancements in electric vehicle (EV) charging technology and vehicle-to-grid (V2G) technology, where EVs act as distributed energy storage units, bidirectional energy exchange between vehicles and the grid can now contribute to LVDN operation. This paper proposes a low-voltage load distribution planning method that integrates street information and V2G technology. A two-stage stochastic programming mixed-integer model is developed to tackle load imbalance in LVDNs, with the planning scheme derived from solving this model. A case study is presented to verify the effectiveness of the method, demonstrating that incorporating V2G technology enhances load distribution accuracy and reduces reliance on manual planning, improving network stability and operational efficiency. [ABSTRACT FROM AUTHOR]

Massive and diversified distributed energy resources (DERs) have great potential for improving the flexibility of power system operations. However, given the wide distribution, small capacity, and variable ownership subject characteristics of DERs, virtual power plants (VPPs) are suitable for aggregating the flexible DERs for participation in the wholesale energy market. Extant studies have focused on obtaining bidding strategies in multiple electricity markets. However, there are shortcomings in the relevant market mechanisms and temporal relationships for participating in energy and ancillary service markets. This work proposes a joint market temporal rolling bidding strategy for VPPs in the wholesale market based on real unified electricity market mechanisms in the southern region of China. Accordingly, the proposed method enhances the market-oriented operational profits of VPPs. [ABSTRACT FROM AUTHOR]

The operation effects of a source-side carbon capture power plant (CCPP) and power-to-gas (P2G) equipment do not match. The response range of the load-side traditional demand response strategy is small, and the adjustment period is limited, which leads to the problem that the complementary potential of low-carbon characteristics on both sides of the source and load is not fully utilized. This article proposes an electricity–heat coupling system scheduling strategy considering the complementary low-carbon characteristics of "source-load." First, the low-carbon operation characteristics of CCPP and P2G with integrated, flexible operations are analyzed, and a source-side CCPP-P2G comprehensive flexible operation mode is proposed. Second, based on the characteristics of flexible adjustment and mutual substitution of electricity and heat load, a load-side comprehensive demand response method is proposed. Finally, the complementary mechanism of low-carbon characteristics on both sides of the source and load is analyzed, and a low-carbon economic dispatch model of the electricity–heat coupling system is constructed to realize the source–load collaborative low-carbon operations. The simulation analysis verifies that the proposed strategy can give full play to the energy time shift advantages of the source-side CCPP and P2G and improve the economic and environmental benefits of the system operations. [ABSTRACT FROM AUTHOR]

The study investigated the efficiency improvement of a 9.5 MW gas engine‐based combined cycle power plant utilizing multiple waste heat streams in an organic Rankine cycle. Four different waste heat sources were considered: I) boiler stack gas, II) engine jacket water, III) boiler steam, and IV) engines' exhaust gas. Besides, three different organic fluids; R245fa, R134a, and R1234ze(Z) were employed to find the best working fluid in the given operating conditions. The performance analysis of the ORC revealed that R245fa is a suitable potential fluid for cases I and II, whereas R134a performs better for cases III and IV. Integrating the ORC with the boiler stack using R245fa at 8 barg provided an additional 16.5% waste gas heat recovery. It increased the net electric efficiency of the existing plant by 0.7%. The jacket water heat recovery further improved the net electric efficiency by 2.1%. By integrating both streams with the ORC in the existing system, the net electrical efficiency was increased from 42.6% to 45.3%. The estimated payback period for the jacket water heat recovery scenario utilizing Chinese ORC equipment was 9.3 years. However, this period was significantly reduced to 4.6 years for general industry applications, rendering it economically viable. [ABSTRACT FROM AUTHOR]

This paper proposes an improved slime mould algorithm (ISMA) to minimize the total electricity generation cost of thermal power plants (TPs) in newly developed hybrid power systems with pumped storage hydropower plants (PSHPs), cascaded hydropower plants (CHPs), photovoltaic power plants (PVPs), conventional hydropower plants, and TPs. ISMA is a better version of the original slime mould algorithm (OSMA) by cancelling OSMA's shortcomings and applying new methods to update new control variables. ISMA replaces two equations of OSMA to update new solutions. In the first equation, ISMA search around each old solution by adding one more increased interval, while OSMA multiplies each old solution by a vector with terms having smaller values than one. In the second equation, OSMA searches around the best solution by adding one more increased interval, but ISMA has a more flexible search by expanding search zones with two additional increased intervals or keeping narrow search zones with one additional increased interval. In addition to OSMA, ISMA is also compared to equilibrium optimizer (EO), jellyfish algorithm (JS), and northern goshawk optimization algorithm (NGO). After solving a test system, ISMA reaches a smaller cost than NGO, JS, EO, and OSMA by 2.43%, 0.68%, 2.83%, and 1.52%, respectively. Then, ISMA is applied for two cases: considering and neglecting the water storage function of PSHPs. Thanks to the water storage function of PSHPs, the total cost of the system is smaller than another case without the water storage function of PSHPs by $196,578.6, corresponding to 8.4%. Clearly, the contribution of the PSHPs to the economic effectiveness of hybrid power systems is huge, and the proposed ISMA is a very suitable optimization tool for finding operation solutions for newly developed hybrid power systems. Hence, the proposed ISMA should be tried for other hybrid power systems with the PSHPs and other power sources, as well as more practical conditions. [ABSTRACT FROM AUTHOR]

The Spherical Tokamak for Energy Production (STEP) environment will include magnetic, thermal, mechanical and environmental loads far greater than those seen in the Joint European Torus campaigns of the past decade or currently contemplated for ITER. Greater still are the neutron peak dose rates of 10−6 displacements per atom, per second, which in-vessel materials in STEP are anticipated to be exposed to. Reduced activation and high-fluence resilience therefore dominate the materials strategy to support the STEP Programme. The latter covers the full life cycle from downselected compositions and new microstructural developments to irradiation-informed modelling and end-of-life strategies. This article discusses how the materials downselection is oriented in plant power trade-off space, outlines the development of an advanced ferritic-martensitic structural steel, describes the 'Design by Fundamentals' mesoscale modelling approach and reports some of the waste mitigation routes intended to make STEP operations as sustainable as possible. This article is part of the theme issue 'Delivering Fusion Energy – The Spherical Tokamak for Energy Production (STEP)'. [ABSTRACT FROM AUTHOR]

This paper presents the development and application of a deep learning-based method for inverting CO2 atmospheric plumes from power plants using satellite imagery of the CO2 total column mixing ratios (XCO2). We present an end-to-end CNN approach, processing the satellite XCO2 images to derive estimates of the power plant emissions, that is resilient to missing data in the images due to clouds or to the partial view of the plume due to the limited extent of the satellite swath. The CNN is trained and validated exclusively on CO2 simulations from 8 power plants in Germany in 2015. The evaluation on this synthetic dataset shows an excellent CNN performance with relative errors close to 20 %, which is only significantly affected by substantial cloud cover. The method is then applied to 39 images of the XCO2 plumes from 9 power plants, acquired by the Orbiting Carbon Observatory-3 Snapshot Area Maps (OCO3-SAMs), and the predictions are compared to average annual reported emissions. The results are very promising, showing a relative difference of the predictions to reported emissions only slightly higher than the relative error diagnosed from the experiments with synthetic images. Furthermore, the analysis of the area of the images in which the CNN-based inversion extract the information for the quantification of the emissions, based on integrated gradient techniques, demonstrates that the CNN effectively identifies the location of the plumes in the OCO-3 SAM images. This study demonstrates the feasibility of applying neural networks that have been trained on synthetic datasets for the inversion of atmospheric plumes in real satellite imagery of XCO2, and provides the tools for future applications. [ABSTRACT FROM AUTHOR]

This study discusses the coal conversion project undertaken by Paiton Energy (PE) in Indonesia in response to changes in coal supply. The root cause analysis method is used to systematically map PE case studies. The results show that PE has successfully adapted to changes in coal quality through the coal conversion project, but faces new challenges with the increasingly limited reserves of high-quality coal in the future. Therefore, further adaptation measures are needed to ensure the sustainability of power plant operations in the future. [ABSTRACT FROM AUTHOR]

In pursuit of the "double carbon" objectives, converting high-carbon thermal power plants into carbon capture power plants is recognized as an effective measure to mitigate carbon emissions. In order to improve the economy of the system, an electric hydrogen generation unit is introduced, and an economic dispatch strategy that considers the combination of a flexible carbon capture power plant and electric hydrogen generation is proposed. Firstly, the low-carbon principle of the flexible carbon capture plant is introduced, and secondly, the joint operation structure of the flexible carbon capture plant, pumped storage, and hydrogen generation is constructed in order to fully exploit the synergistic operation potential of the hydrogen and carbon capture plants. On this basis, an economic dispatch model with the objective of the lowest combined system cost of the sum of system operation cost, system carbon trading cost, hydrogen production revenue, and wind and light abandonment cost is established, fuzzy parameters are used to characterize the uncertainty levels of wind and light, fuzzy opportunity constraints are established, and the model is solved using an improved sparrow search algorithm. The results of the example show that the proposed model reduces the comprehensive cost by 20.9% and carbon emissions by 61.77% compared with the existing model, which has significant low-carbon economic benefits. [ABSTRACT FROM AUTHOR]

Noise pollution is an important environmental problem and in comparison, to other pollutants, the control of environmental noise has been hampered by insufficient knowledge as well as a lack of criteria. Power Plant industries have worldwide substantial progress and noise pollution is one of the considerable environmental impacts of various processes of these industries. This cross-sectional research aimed to study the sound levels to control noise pollution at different sections of the Mazandaran Thermal Power Plant in Iran. Sound pressure level measurements and frequency analysis were performed using the net" method where the results were compared with ACGIH Threshold Limit Values. It was found that inside the factory most of the measuring stations have high sound levels in comparison to industrial standards of 85 dB(A). Office buildings have the lowest sound pressure among measured areas. As 43% of measured stations are located in danger areas. Also, environmental noise measurements around Mazandaran Power Plant as an industrial residential area have revealed that sound levels were not higher than the admissible standards in Iran. The electricity generator's fan and Feed Water Pump section produce high levels of noise; therefore, a silencer and an enclosure were designed respectively. The amount of noise reduction for the enclosure was 38.7 dB(A) while the values of insertion loss and for the silencer 63.9 dB(A) reduction has been achieved. [ABSTRACT FROM AUTHOR]

The flexible operation of carbon capture units is crucial for the economic performance of coal-fired power plants equipped with CO2 capture systems. This paper aims to investigate the impact of electricity, CO2, and fuel prices on the economic operation of such plants. A novel economic optimization model is proposed, integrating a static model of the carbon capture system with a particle swarm optimization algorithm. A new concept, the CO2 boundary price, is introduced as a key metric for determining the operating conditions of CO2 capture units. The CO2 boundary price rises when the power load decreases due to the decline in power generation efficiency, and it also increases with rising fuel prices, as the cost of steam for CO2 capture increases. Additionally, when the objective is to meet power load demand, CO2 prices have a great influence on the operation of CO2 capture units, assuming fixed coal and electricity prices. However, when the primary goal is to maximize plant profitability, the system's operational conditions are strongly influenced by the relative prices of electricity and CO2. The proposed optimization model and the uncovered price-effect mechanisms provide valuable insights into the economic operation of carbon capture power plants. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NOxs) are some of the most important hazardous air pollutants from industry. In China, the annual NOx emission in the waste gas of industrial sources is about 8.957 million tons, while power plants remain the largest anthropogenic source of NOx emissions, and the precise control of NOx in power plants is crucial. However, due to inherent issues with measurement and pipelines in coal-fired power plants, there is typically a delay of about three minutes in NOx measurements, bringing mismatch between its control and measurement. Measuring delays in NOx from power plants can lead to excessive ammonia injection or failure to meet environmental standards for NOx emissions. To address the issue of NOx measurement delays, this study introduced a hybrid boosting model suitable for on-site implementation. The model could serve as a feedforward signal in SCR control, compensating for NOx measurement delays and enabling precise ammonia injection for accurate denitrification in power plants. The model combines generation mechanism and data-driven approaches, enhancing its prediction accuracy through the categorization of time-series data into linear, nonlinear, and exogenous regression components. In this study, a time-based method was proposed for analyzing the correlations between variables in denitration systems and NOx concentrations. This study also introduced a new evaluation indicator, part of R2 (PR2), which focused on the prediction effect at turning points. Finally, the proposed model was applied to actual data from a 330 MW power plant, showing excellent predictive accuracy, particularly for one-minute forecasts. For 3 min prediction, compared to predictions made by ARIMA, the R-squared (R2) and PR2 were increased by 3.6% and 30.6%, respectively, and the mean absolute error (MAE) and mean absolute percentage error (MAPE) were decreased by 9.4% and 9.1%, respectively. These results confirmed the accuracy and applicability of the integrated model for on-site implementation as a 3 min advanced prediction soft sensor in power plants. [ABSTRACT FROM AUTHOR]

The ongoing transition to energy systems with high shares of variable renewables motivates the development of novel thermal power cycles that operate economically at low capacity factors to accommodate wind and solar intermittency. This study presents two recuperated power cycles with low capital costs for this market segment: (1) the near-isothermal hydrogen turbine (NIHT) concept, capable of achieving combined cycle efficiencies without a bottoming cycle through fuel combustion in the expansion path, and (2) the intercooled recuperated water-injected (IRWI) power cycle that employs conventional combustion technology at an efficiency cost of only 4% points. The economic assessment carried out in this work reveals that the proposed cycles increasingly outperform combined cycle benchmarks with and without CO2 capture as the plant capacity factor reduces below 50%. When the cost of fuel storage and delivery by pipelines is included in the evaluation, however, plants fired by hydrogen lose competitiveness relative to natural gas-fired plants due to the high fuel delivery costs caused by the low volumetric energy density of hydrogen. This important but uncertain cost component could erode the business case for future hydrogen-fired power plants, in which case the IRWI concept powered by natural gas emerges as a promising solution. [ABSTRACT FROM AUTHOR]

In response to the issues of poor economic efficiency and high CO2 emissions in the urea-to-ammonia technology of thermal power plants, this paper innovatively proposes a new ammonia production process for thermal power plants. This process utilizes the waste heat of thermal power plant boilers and conducts urea pyrolysis through two-stage heating to prepare ammonia and cyanuric acid. From this, the prepared ammonia can be used in the denitrification process of thermal power plants, and the prepared cyanuric acid can bring additional benefits to thermal power plants. The optimal process scheme was determined through orthogonal experiments of urea pyrolysis. And with the help of Aspen Plus software, a whole-process modeling analysis of urea pyrolysis experiments was carried out to investigate the influences of the melting temperature, melting time, reaction temperature, and reaction time on the process. The results show that when the melting temperature was 160 °C, the melting time was 45 min, the reaction temperature was 240 °C, and the reaction time is 20 min, which was the best scheme, 18.45% ammonia and 52.35% cyanuric acid could be obtained. Through the combined analysis of the Aspen Plus simulation and urea pyrolysis experiments, it was found that the melting temperature should be controlled within 160–167 °C, the melting time should be controlled within 40–45 min, the reaction temperature should be controlled within 240–245 °C, and the reaction time should be controlled within 15–20 min. Compared with the existing urea-to-ammonia process, this process has the advantages of nearly zero emissions and good economic benefits, thus providing reliable research data support for future industrialization. [ABSTRACT FROM AUTHOR]

Multi-criteria decision analysis (MCDA) methods are vital in assessing decision variants under multiple conditions. However, involving domain experts in developing decision models can be challenging and costly, necessitating more scalable and independent solutions. This paper introduces the intelligent characteristic objects method (INCOME), which combines the k-Nearest Neighbor (kNN) algorithm and the COMET method to create a theoretical decision-maker for comparing characteristic objects (COs). INCOME overcomes limitations of classical MCDA methods, such as the TOPSIS approach, which struggles with complex functions and non-monotonic modeling. INCOME influences data-based knowledge to provide a robust framework for assessing decision options. The integration of the COMET method and kNN algorithm enables improved modeling of decision functions based on evaluated data, increasing the flexibility and independence of the INCOME approach. A case study assessing gas power plants based on four criteria is presented to validate the performance of the INCOME method. The results demonstrate high correlations with the reference model and slightly higher classical approaches like TOPSIS and TOPSIS-COMET. However, INCOME exhibits greater stability and flexibility by utilizing all available data instead of relying on limited expert knowledge. The proposed INCOME approach offers several advantages, including creating a continuous decision model, resistance to the Rank-Reversal phenomenon, and the potential for replacing domain experts with artificial experts. This study highlights the effectiveness of INCOME in Multi-Criteria Decision Analysis. It suggests future research directions, such as parameter selection and testing in different decision-making problems. [ABSTRACT FROM AUTHOR]

This article substantiates the possibility of solving a difficult task to offer a reliable estimate of the residual resource of the power plant of a hybrid car, which is exposed during operation to the influence of a complex set of external factors. This task is solved by monitoring the time change of diagnostic parameters and controlling the load–speed mode of the hybrid power plant, as well as using physical and chemical processes that cause the degradation of the traction battery. Methodological principles for assessing the resource of a hybrid power plant of a car have been developed, which are based on the disclosure of cause-and-effect relationships between realized and nominal quality indicators, operating conditions, and indicators of technical condition. The choice of rational solutions for the operation of a hybrid car is given, and the external conditions are determined, under which the residual life of the hybrid power plant will change. The scientific result of the study is a theoretical generalization of the scientific provisions of forecasting the resource of the hybrid power plant of a car. This ensures the efficient use of hybrid vehicles and reduces maintenance costs. [ABSTRACT FROM AUTHOR]