Operational Scenarios Research Articles

Techno-Economics Analysis to Reshape Global Clean and Green Energy

Renewable methanol is produced from biomass or synthesized from green hydrogen and carbon dioxide CO2. These are essential components that are consumed as chemical feedstock and fuel. E-methanol is also vital in the petroleum/ petrochemical industry and transport sectors toward net carbon-neutral goals. In the current operational scenario, renewable methanol production costs are high, and production volumes are low. We need to establish the right policies to address the challenges of producing e-methanol costeffectively to deliver clean, green energy and fuel in the competitive market. Keywords—Green hydrogen, Electro Fuel, PV, Renewable, Emethanol

A coordinated control method of slurry density and material level to improve cementing quality

Abstract During the cementing stage, it is necessary to strictly control the density of the slurry injecting well to form cement sheath with good interlayer sealing capacity. However, due to the influence of factors such as unstable ash supply and coupling of operating parameters, problems such as unstable cement slurry density control and serious deviation from process design values often occur, which seriously limit the improvement of cementing efficiency and quality. In order to solve this problem, this paper proposes a coordinated control method of slurry density and level by combining feedforward-cascade control and split range control, to strengthen the collaborative linkage between the operating parameters of cement supply, liquid supply, slurry mixing and pump injection, and improve the quality of cement slurry density control. Finally, the proposed control method is verified by the test platform built for the actual cementing operation scenario. The test results show that the proposed method can achieve stable and accurate control of cement slurry density and effectively guarantee the safety and quality of cementing operation.

Analysis model of energy consumption variables for data processing in high-performance computing systems

One of the main challenges in the efficient operation of a high-performance computing (HPC) center is the energy consumption generated by the operation of the data center where the HPC equipment is housed, mainly because this consumption is reflected in very high accounts payable, and this may affect the level of service offered to users. The study of the different factors and elements that can make energy consumption more efficient in these data centers provides an opportunity to focus these resources on elements that favor the use of HPC. The design variables provided by manufacturers to manage HPC systems and monitoring systems provide an accurate view of the behavior of these variables according to how they are used. HPC architectures are configured in a very particular way for each HPC data center, creating particular scenarios of operation and performance in each implementation. Various proposals and technologies have been developed for the analysis of the energy consumption of a data center, and the processing elements include a series of indicators and technologies that manufacturers have developed to determine the energy efficiency. This article seeks to identify this series of processing and performance variables, which affect the energy consumption of HPC equipment, for the implemented computing architectures based on the analysis of performance models to obtain a general over-view of their effect on energy consumption in a case study to identify the behaviors of particular job assignment factors and provide an analysis of the energy consumption under particular conditions.

On the Feasibility of Deep Geothermal Wells Using Numerical Reservoir Simulation

This study examines the geothermal energy extraction potential from the basement rock within the Denver–Julesburg Basin, focusing on the flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-shaped, V-shaped, inclined V-shaped, and pipe-in-pipe configurations against enhanced geothermal system setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. The results suggest that while closed-loop systems offer moderate temperature increases, Enhanced geothermal system configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.

Transport accessibility changes in metropolitan regions: high-speed rail connection frequency estimation

This article focuses on a very narrowly specific segment of this issue, considering the impacts of HSR in the long term, not as transport arteries connecting the most important metropolitan areas but, on the contrary, as an internal factor of development within a metropolitan region. The paper aims to transfer the present operational European HSR commuting connection frequency experience to a generally applicable frequency estimation formula. Through a quantitative approach, the research analyses the total sample of 1,446 train connections from 10 European metropolitan regions. It answers the secondary research question of what the range of accessibility change between the metropolitan core and the intermediate city is after introducing HSR connection inside metropolitan regions in the time of 1 hour of journey. The estimation model formula calculates the optimal number of HSR connections between the metropolitan core and intermediate city in the HSR developing countries. It is derived and verified from the analysed dataset values. The potential operational change scenarios are presented and described based on the example of 34 metropolitan city pairs.

Earthing System Analysis for Steel Tower Carrying 33kV Line

This study examines the critical analysis of earthing systems connected to steel towers that carry 33 kV power lines. Ensuring the safety and dependability of power transmission infrastructure becomes crucial in light of the growing demand for energy. By utilizing sophisticated computational methodologies and simulation approaches, this research carefully investigates how well the earthing system performs in various operational circumstances and fault scenarios. A thorough modeling technique is used in the analysis, which considers a number of variables including fault currents, tower design, soil resistivity, and grounding electrode configurations. In order to give a comprehensive understanding of the behavior of the system and its consequences for operational reliability, the study simulates many situations, including normal operation and fault occurrences. By using sophisticated numerical simulations and sensitivity analysis, the research pinpoints important factors affecting the earthing system's efficiency and suggests creative optimization techniques. These optimization techniques could involve changing the location of the grounding electrode, improving the materials used in the conductor, or putting additional safety precautions in place. The researcher's conclusions have important ramifications for the engineering community since they provide practical advice on how to strengthen the security and robustness of power transmission networks. The study adds to the continuous efforts to improve the efficiency and dependability of electrical grids by addressing potential weaknesses in the architecture of the earthing system. This thorough study advances the field of earthing system engineering by offering a solid platform for next studies and real-world implementations. Through this work, we can better understand the dynamics of earthing systems and optimization methodologies, which will help build more resilient and sustainable power transmission infrastructure that can adapt to society's changing energy needs.

Experimental analysis and investigation of desiccant coated heat exchanger applications involving condensation and sorption mechanisms

This study focuses on the application of desiccant coated heat exchangers (DCHEs) in conditions where condensation occurs below the dew point temperature. Previous experimental studies on DCHEs and DCHPs have predominantly examined the sorption mechanism above the dew point, leaving a gap regarding material selection and system design in the presence of condensation. To address this, a guide is introduced that combines the understanding of condensation and sorption processes for desiccant applications. The guide is applied to evaluate the suitability of a superabsorbent-LiCl (SAP-LiCl) composite desiccant for desiccant coated heat pump (DCHP) applications. The stability of the desiccant in the presence of condensed water droplets is validated. Additionally, an experimental investigation explores the relationship between sorption and condensation mechanisms, identifying the transitional coolant temperature at which dehumidification shifts from condensation-dominant to sorption-dominant. By incrementally adjusting the coolant temperature in 5 °C steps, the transitional temperature of the SAP-LiCl based DCHE is determined to be approximately 15 °C under the target operation scenario, rendering its suitability for additional below-dew-point applications. The study reveals optimal operational parameters for DCHE, demonstrating a potential energy saving of 20 %. Based on these findings, a DCHP prototype is constructed to assess the feasibility of DCHE in real-world applications. The transient behaviors of this prototype are analyzed during each operating cycle, yielding a coefficient of performance of 4.97 and a cooling capacity of 1.5 kW under baseline operating conditions.

A design method of turboexpander-compressors based on multi-objective optimization applied to reverse brayton cycle

This paper presents a new design method for turboexpander-compressors used in air refrigeration. As a key component of the reverse Brayton cycle, the efficiency of the turboexpander-compressor significantly has an impact on the overall cycle performance. The expander section is optimized for multi-objective efficiency at different flow rates using the Imperialist Competitive Algorithm to achieve high performance across all operating conditions. Regarding achieving high utilization efficiency for output power from efficient expanders, the compressor section adopts combined methods involving the jet-wake model and parameter equations. The proposed design is validated through public models, computational fluid dynamics simulations and experiments. Simulations and analysis are conducted on test cases representing comprehensive operational scenarios for both the compressor and the expander, confirming that conclusions drawn based on this method align well with underlying theoretical principles. At the design mass flow, the expander efficiency is 89%, and the compressor utilizes the output power of the expander with an efficiency of 90%. Near the design flow, the expander efficiency is more than 85%, and the compressor utilizes the output power of the expander with an efficiency exceeding 80%. This paper presents a method for turboexpander-compressors applicable to air refrigeration cycles, which achieves a reduction in design costs and an improvement in efficiency under varying loads.

Actor-Critic Neural-Network-Based Fractional-Order Sliding Mode Control for Attitude Tracking of Spacecraft with Uncertainties and Actuator Faults

This paper investigates the attitude control of rigid spacecraft in the presence of uncertainties, disturbances, and actuator faults. In order to effectively address these challenges and improve the performance of the system, a novel actor-critic neural-network-based fractional-order sliding mode control (ACNNFOSMC) has been developed for spacecraft. The integration of actor-critic neural network, fractional-order theory, and sliding mode control enables dual functionality: the actor-critic neural network serves to approximate the aggregate of uncertain parameters, disturbances, and actuator faults, thereby facilitating their compensation, while the fractional-order sliding mode control mechanism significantly improves the system’s tracking precision and overall robustness against uncertainties. Theoretical analyses are presented to analyze the stability of the proposed control framework. Thorough examination via simulation experiments affirms the effectiveness and control precision of attitude of our proposed control strategy, even in complex operational scenarios.

Comparative Analysis: Fractional PID vs. PID Controllers for Robotic Arm Using Genetic Algorithm Optimization

This paper presents a comparative analysis of a fractional-order proportional–integral–derivative (FO-PID) controller against the standard proportional–integral–derivative (PID) controller, applied to a nonlinear robotic arm manipulator systems. The genetic algorithm (GA) optimization method was implemented to tune the gain parameters of the FO-PID and PID controllers. The performance of the FO-PID and PID controllers were evaluated though different cost functions, including integral of squared error (ISE), integral of absolute error (IAE), integral of time-weighted absolute error (ITAE), and integral of time-weighted squared error (ITSE). The performance of these controllers was examined via extensive simulations by using MATLAB/SIMULINK for different operating scenarios of the robotic arm manipulator system. Based on the obtained results, a comparative performance matrix is proposed, wherein cost functions ISE, IAE, ITAE, and ITSE are represented as columns while characteristic parameters (overshoot, rising time, and settling time) are represented as rows. The proposed performance matrix facilitates the selection between the PID and FO-PID controllers.

Safety evaluation via conflict classification during automated shuttle bus service operations

The widespread adoption of Connected and Automated Vehicles (CAVs) is being propelled, not only in the realm of private vehicles but also within transit systems. This development serves to enhance urban transport activities, rendering transportation more appealing to passengers. The present study aims to identify and examine the safety effects of testing different operational speed shuttle bus services in various future mobility conditions. To investigate impacts of autonomous shuttle bus services and to further examine their operational speed, the microscopic simulation method was performed. Specifically, four sets of simulation scenarios were comprised: a baseline scenario representing the current conditions and three operational speed scenarios (15 km/h, 30 km/h and 45 km/h) for an autonomous shuttle service. Each one of these sets included eleven CAV market penetration rates (MPRs) of CAVs of the general traffic (ranging from 0 to 100% in 10% increments). By analyzing the trajectory data extracted from microsimulation, traffic conflicts were identified and further analyzed by developing Mixed-Effects Multinomial Logit Regression models (ME-MLMs) in order to associate conflict type taking into account network characteristics as well as traffic conditions. Several aspects were determined as statistical significant parameters influencing type of conflict. The analysis yielded several significant findings that provide quantitative measurements and assessments of the effects observed, enabling a better understanding of the safety implications associated with the widespread adoption of automated services.

Sensitivity analysis of commutation failure in multi-infeed HVDC systems: Exploring the impact of ac system representations and fault types

This paper investigates commutation failure (CF) in line commutated HVdc converters within multi-infeed HVDC systems and thereby provides valuable insights for the operation and design of HVdc systems. CF susceptibility across various operational scenarios, fault types, and ac system representations at different frequencies is explored. An Electromagnetic Transients (EMT) model is constructed and parameter changes are applied using Monte-Carlo Simulation. The process is fully automated with the use of a controlling program written in Python, which varies parameter values and facilitates result retrieval and post-simulation analysis. A typical analysis results in several hundred thousands of simulation runs, requiring the procedure to be implemented on a parallel computing platform. The results show that two-phase faults are the most critical CF triggers, an aspect often overlooked in previous literature focused on three-phase or single-phase-to-ground faults. Furthermore, the frequency dependent characteristics of the ac network can result in very different CF susceptibilities.

Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling

This paper proposes a real-time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all controllable devices by power-energy envelopes and provides them to the transmission system operator (TSO). At the transmission system level, a distributed nonlinear model predictive control (nmpc) approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power-energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework’s effectiveness and applicability in real-world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.

A robust statistical framework for cyber-vulnerability prioritisation under partial information in threat intelligence

Proactive cyber-risk assessment is gaining momentum due to the wide range of sectors that can benefit from the prevention of cyber-incidents by preserving integrity, confidentiality, and the availability of data. The rising attention to cybersecurity also results from the increasing connectivity of cyber–physical systems, which generates multiple sources of uncertainty about emerging cyber-vulnerabilities.This work introduces a robust statistical framework for quantitative and qualitative reasoning under uncertainty about cyber-vulnerabilities and their prioritisation. Specifically, we take advantage of mid-quantile regression to deal with ordinal risk assessments, and we compare it to current alternatives for cyber-risk ranking and graded responses. For this purpose, we identify a novel accuracy measure suited for rank invariance under partial knowledge of the whole set of existing vulnerabilities.The model is tested on both simulated and real data from selected databases that support the evaluation, exploitation, or response to cyber-vulnerabilities in realistic contexts. Such datasets allow us to compare multiple models and accuracy measures, discussing the implications of partial knowledge about cyber-vulnerabilities on threat intelligence and decision-making in operational scenarios.

A comprehensive analysis of gas film pressure distribution in gas foil thrust bearings with PVDF sensor array

This research introduces an innovative approach for evaluating gas film pressure distribution in gas foil thrust bearings (GFTBs) utilizing polyvinylidene fluoride (PVDF) sensor arrays. Chosen for their exceptional sensitivity and rapid response, these sensors facilitate precise pressure analysis across various operational scenarios. The study investigates the pressure of integral and circumferentially separated GFTBs through experiments at 12 krpm to 16 krpm and loads of 60N to 120 N. The findings, derived from detailed PVDF sensor data and interpolation analysis, indicate that bearings with circumferential separation achieve more uniform pressure distributions. Experiments under extreme load conditions demonstrate that the separated type has a higher load-bearing capacity. This presents a novel PVDF-based measurement technique and advances the understanding of GFTB dynamics by correlating pressure distribution with operational parameters, thereby offering potential improvements in bearing design and performance.

Conceptual Design of an Unmanned Electrical Amphibious Vehicle for Ocean and Land Surveillance

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV) that can be easily adapted for different types of land and/or water missions with low monetary cost (EUR < 5 k, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then, a market research analysis focused on vehicles currently available and their technological advances is conducted to identify existing UV solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle with approximate dimensions of 1050 × 670 × 450 mm (length–width–height), enabled with 6 × 6 traction capable of reaching 20 km/h on land, which possesses amphibious capabilities of independent propulsion in water up to 8 kts and an estimated autonomy of over 60 min.

Low-Carbon Operation Strategy of Park-Level Integrated Energy System with Firefly Algorithm

The integrated energy system at the park level, renowned for its diverse energy complementarity and environmentally friendly attributes, serves as a crucial platform for incorporating novel energy consumption methods. Nevertheless, distributed energy generation, characterized by randomness, fluctuations, and intermittency, is significantly influenced by the surrounding environment. Within the park, the output of multiple devices frequently diverges significantly from the actual demand, potentially resulting in energy waste phenomena, such as the curtailment of wind and solar power. To tackle the dual challenges of balancing energy supply and demand while reducing carbon emissions in the industrial park, this paper introduces a low-carbon integrated energy system that incorporates distributed renewable and clean energy sources. Mathematical models are formulated for the source–grid–load–storage components of this low-carbon integrated energy system. Furthermore, various operational scenarios for the park-level integrated energy system are analyzed. The ultimate goal is to devise an economically viable, low-carbon, and efficient operational strategy for the integrated energy system, aiming to satisfy the diverse objectives of various stakeholders.

Septage treatment using the First Stage of French Vertical Flow Constructed Wetlands: From the beginning to the closure of the system

The First Stage of French Vertical Flow Constructed Wetlands (FS-FVFCW) offers a sustainable solution for treating septage. The system operates through distinct phases: start-up, full operation and final rest. During full operation, factors such as feeding duration, rest periods and percolate impounding significantly affect performance. This study assessed the performance of a pilot-scale Modified FS-FVFCW in Northern Tropical Andes, from start-up to closure stages under three operational scenarios. These scenarios varied in planted/unplanted conditions and percolate drainage/impounding. A four-month start-up phase proved adequate for vegetation growth and adaptation, achieving over 50% COD removal efficiency. Percolate retention (impounding) during operation notably improved COD and TS removal, increasing efficiencies from 49% to approximately 90% for COD and from 39% to around 70% for TS. Plant presence contributed to mosquito control and odour reduction but had minimal impact on removal efficiencies. The pilot demonstrated significant dewatering potential, with sludge deposit samples showing water content below 76% across all scenarios after 24 h; and a 10% reduction in VS/TS ratio during the operational resting period. After a 5-month closure, the sludge deposit layer exhibited organic matter content similar to long-rested sludge, albeit with persistent faecal contamination.

Return strategies and channel pricing in omni-channel retail considering heterogeneous customer perceptions

As Internet technology advances, the retail industry is increasingly adopting omni-channel operational strategies. This research delves into the interplay between return losses and customer perceptions of online products, and how these factors influence profit-maximizing omnichannel retailers’ optimal return strategy and channel pricing. Previous studies have primarily focused on cross-channel aspects and have not thoroughly explored the impact of return loss on profitability in an omni-channel context. The study assumes that profit-maximizing retailers allow consumers to choose their purchase channels based on perceived utility of different channels, while adhering to the retailer’s stipulated return strategy. To this end, we introduce three distinct return strategies (returning products via the original purchase channel, offline return, and online return) for omni-channel retailers. We aim to identify the most profitable return strategy by considering diverse return losses associated with each channel and consumers’ perceptions of online products. Our analysis identifies scenarios in which a particular return strategy either boosts or reduces retailer profit, thereby facilitating optimal channel pricing decisions. Our findings reveal that customers’ purchasing channel selections are affected by their perception, retailer’s return strategy, and net return loss. We also find that no matter what kind of operation scenarios the retailers adopted, the retailers should let all customers return to the online channel to generate maximum profit when the difference between the retailer’s online and offline net return loss is less than the difference between the customer’s online and offline return hassle cost. Conversely, an offline return strategy proves more profitable. Our findings are supported by numerical simulations, guiding omni-channel retailers in making informed decisions regarding return strategies and channel pricing.

Quantifying the State of the Art of Electric Powertrains in Battery Electric Vehicles: Comprehensive Analysis of the Tesla Model 3 on the Vehicle Level

Data on state-of-the-art battery electric vehicles are crucial to academia; however, these data are not published due to non-disclosure policies in the industry. As a result, simulation models and their analyses are based on assumptions or insider information. To fill this information gap, we present a comprehensive analysis of the electric powertrain of a Tesla Model 3 Standard Range Plus (SR+) from 2020 with lithium iron phosphate (LFP) cells, focusing on the overall range. On the vehicle level, we observe the resulting range in multiple test scenarios, tracing the energy path from source to sink by conducting different test series on the vehicle dynamometer and through alternating current (AC) and direct current (DC) charging measurements. In addition to absolute electric range tests in different operating scenarios and electric and thermal operation strategies on the vehicle level, we analyze the energy density and the power unit’s efficiency on the component level. These tests are performed through procedures on the chassis dynamometer as well as efficiency analysis and electric characterization tests in charge/discharge scenarios. This study includes over 1 GB of attached measurement data on the battery pack and vehicle level from the lab to the real-world environment available as open-source data.