Operation Strategy Research Articles

Microalgae bio-reactive façade: System thermal–biological optimization

This article explores numerically the biotechnological performances of microalgae biofaçade. The model computes the system’s thermal behavior using a radiative-convective approach accounting for location on Earth and actual weather data. In a coupled manner, it simulates the microalgae culture behavior, i.e. light-driven growth and cell pigment content acclimation. In addition, it features refinement such as wavelength-dependent biomass optical properties and thermal-modulated biological rates. Thanks to this model, operation strategies and design possibilities were evaluated using actual weather data for a biofaçade module deployed in Marseille in 2023. Investigations revealed that a semi-batch mode of operation, while simplistic, is the most efficient way to operate a biofaçade if sole biological production is considered (about 18.0 ± 0.9 kg per year, 2.44 ± 0.12 g/L output concentration). However, if intended as an office glazing, turbidostat mode of operation should be preferred for aesthetic and visual comfort reasons (about 19.1 ± 1.1 kg per year, 0.64 ± 0.07 g/L output concentration). System optimization also confirmed the experimental observation that the system could be prone to overheating. Nevertheless, while overheating can be mitigated by increasing the reservoir thickness, this strategy is detrimental to the average output concentration. Finally, location-specific optimization revealed that a standard biofaçade module could be deployed over France, and system performances are derived for the whole country thanks to the weather forecast agency data.

A Wide-Range TCSC Based ADN in Mountainous Areas Considering Hydropower-Photovoltaic-ESS Complementarity.

Due to the radial network structures, small cross-sectional lines, and light loads characteristic of existing AC distribution networks in mountainous areas, the development of active distribution networks (ADNs) in these regions has revealed significant issues with integrating distributed generation (DGs) and consuming renewable energy. Focusing on this issue, this paper proposes a wide-range thyristor-controlled series compensation (TCSC)-based ADN and presents a deep reinforcement learning (DRL)-based optimal operation strategy. This strategy takes into account the complementarity of hydropower, photovoltaic (PV) systems, and energy storage systems (ESSs) to enhance the capacity for consuming renewable energy. In the proposed ADN, a wide-range TCSC connects the sub-networks where PV and hydropower systems are located, with ESSs configured for each renewable energy generation. The designed wide-range TCSC allows for power reversal and improves power delivery efficiency, providing conditions for the optimization operation. The optimal operation issue is formulated as a Markov decision process (MDP) with continuous action space and solved using the twin delayed deep deterministic policy gradient (TD3) algorithm. The optimal objective is to maximize the consumption of renewable energy sources (RESs) and minimize line losses by coordinating the charging/discharging of ESSs with the operation mode of the TCSC. The simulation results demonstrate the effectiveness of the proposed method.

Consensus SE(3)-Constrained Extended Kalman Filter for Close Proximity Orbital Relative Pose Estimation

In this paper, a recently proposed SE(3)-constrained extended Kalman filter (EKF) is extended to formulate a strategy for relative orbit estimation in a space-based sensor network. The resulting consensus SE(3)-constrained EKF utilizes space-based sensor fusion and is applied to the problem of spacecraft proximity operations and formation flying. The proposed filter allows for the state (i.e., pose and velocities) estimation of the deputy satellite while accounting for measurement error statistics using the rotation matrix to represent attitude. Via a comparison with a conventional filter in the literature, it is shown that the use of the proposed consensus SE(3)-constrained EKF can improve the convergence performance of the existing filter for satellite formation flying. Moreover, the benefits of faster convergence and consensus speed by using communication networks with more connections are illustrated to show the significance of the proposed sensor fusion strategy in spacecraft proximity operations.

Assessment of airborne transmitted infection risk in classrooms using computational fluid dynamics and machine learning-based surrogate modeling

In recent years, the assessment of airborne transmitted infection risk has been extensively performed using Computational Fluid Dynamics (CFD) simulations, especially in response to the COVID-19 pandemic. Nevertheless, the high computational demands and time-intensive nature of CFD simulations highlight the need for fast or real-time infection risk predictions. This capability is crucial for swift decision-making in dynamic environments where timely health interventions are critical. This paper presents a thorough analysis of airborne infection risks in classroom environments based on CFD simulations to understand key factors such as ventilation strategies, air change rates, occupant arrangements, source locations, and particle sizes. This study also employs data-driven supervised learning methods—specifically, Long Short-Term Memory (LSTM) and Artificial Neural Networks (ANN)—to generate surrogate models for predicting airborne infection risk. Key findings reveal that different ventilation strategies significantly affect airborne infection risk, reducing it by 49 %–77 %. Moreover, the conventional Wells-Riley model was identified as lacking in its ability to accurately predict local infection risks. The study further challenges the assumption that higher air change rates are universally beneficial, considering that occupants seated in the back rows of a classroom experienced up to a 166 % increased risk, despite elevating air change rates from 1.1 h−1 to 11 h−1. These results suggest that physical distancing alone may be insufficient and highlight the importance of considering other factors such as occupant arrangements. Regarding the model performance, the ANN-based surrogate model demonstrated varying prediction accuracy. For inhalable particle concentration predictions for susceptible occupants, R2 values ranged from 0.31 to 0.65 with CVRMSE values between 100 % and 180 %. In contrast, the model achieved an R2 of 0.79 and a CVRMSE of 34 % for infectors. The insights and methodologies from this study can inform HVAC system design and operation strategies to better mitigate infectious disease transmission in densely occupied indoor environments.

Optimised Two-Layer Configuration of SESS-CCHP System Considering Wind and Light Output Correlation and Load Sensitivity

With the gradual depletion of fossil energy sources and the diversification of users’ energy demand, combined cooling, heating and power (CCHP) microgrids have become a hot technology to improve energy efficiency and promote efficient and synergistic energy operation. However, the uncertainty and correlation of wind power and photovoltaic (PV) outputs have posed a great challenge to the reliability of CCHP system operation, so CCHP systems are often equipped with energy storage devices to improve system flexibility to ensure the reliability of energy supply. However, system-owned reserves still have shortcomings such as high investment O&M costs and large space requirements. As an emerging model, “shared energy storage” can reduce the investment pressure of users and open up new ways for the economic and stable operation of CCHP systems. Therefore, based on the scenario of wind and solar power correlation and considering different types of load flexibility, this paper proposes to construct a shared energy storage station (SESS)-CCHP double-layer synergistic optimal allocation model. The model incorporates the consideration of the actual operation strategy of the CCHP system in the planning stage of energy storage. An example analysis shows that SESS reduces the total operating cost of the CCHP system by 25.96% and improves the new energy consumption rate by 10.46% compared with no energy storage. Compared with the system independently configured with energy storage, the cost saving is 2.14%, thus validating the effectiveness of the proposed model.

A novel dual-wheel air-conditioning system operating strategy in different seasons

The application of solid desiccant air-conditioning systems can significantly reduce building energy consumption. Previous studies have focused on innovating the integration of solid desiccant air-conditioning systems (DACS) to improve dehumidification performance in summer. In this paper, a novel DACS is proposed, which can humidify the supply air in winter based on satisfying the dehumidification demands in summer. It can satisfy the year-round humidity requirements of domestic housing with significant savings in humidification costs. Furthermore, the operating strategy of the novel DACS is proposed, particularly for winter humidification conditions. It is adaptable as well as cost-effective compared to traditional operating strategies. The dehumidification/humidification capacity of the core component, polymer desiccant wheel, and the variation of temperature rise/temperature drop are investigated under different variations of parameters, including air temperature, air humidity, air volume flow rate, and wheel speed. The results show that with the increase of supply air mass flow from 0.6 kg/s to 1.9 kg/s, the power consumption of the system only increases by 9.5 kW. In winter, when the supply air temperature decreases from 8 °C to 1 °C, the power consumption increases by 7.2 kW, but in summer, when the temperature of the supply air increases by 7 °C, the power consumption of the system decreases by 7.0 kW. The power consumption of the system varies greatly when the humidity of the supply air is less than 17 g/kg, conversely, the power consumption of the system showed a negative trend. The analysis demonstrates the effective performance of the proposed system under varying climatic conditions.

A Systems Firm-Centered Perspective on the Environmental Assessment of Recyclable PET and Glass Soft Drink Containers

This paper adopts a systems firm-centered perspective on the environmental assessment of recyclable glass and PET soft drink containers. We employ LCA and discrete-event simulation modeling for the environmental assessment of the two soft drinks packaging alternatives in operational terms over the entire supply chain over a period of three years. The assessment is based on real data collected from a large soft drink producer and its suppliers. The research and practice contribution of the paper is twofold: first, it introduces a methodological framework for environmental assessment of companies’ packaging environmental impact under different product and operations strategies; and secondly, it provides a holistic environmental assessment of the two packaging materials (PET and glass) taking into account specific operational issues, such as product mix and recycling and reuse options, as well as activity interdependences and stochasticity. The results of the simulation experiments confirm at the operations system level, for glass, the importance for sustainability, to increase the number of reuse cycles (for the particular case, for significant improvement, seven reuses) and the percentage of used bottles collected for refilling (80% recovery rate), whereas for PET, to increase the percentage of recycled PET in new bottles (towards 30%).

Economic Impact of CSP Plants with Storage Addressing the Energy Transition in Locations with High Electricity Demand in Chile

This study explores the economic implications of hybrid plants combining photovoltaic (PV) and Concentrated Solar Power (CSP) technologies with energy storage in response to Chile's ongoing energy transition. Utilizing the System Advisor Model (SAM), six diverse locations were evaluated to assess energy generation profiles, calculate the Levelized Cost of Energy (LCOE), and analyze gross margins. The key finding is that higher solar multiples or storage capacities do not consistently lead to lower LCOE, primarily due to operational strategies aligning CSP generation profiles with PV. Notably, northern regions consistently yield higher gross margins despite occasional zero marginal costs, while areas near Santiago experience lower gross margins, with Salamanca presenting the lowest margin. This highlights the critical role of available solar resources in shaping economic outcomes.

Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell

Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies help to better understand and model degradation and to optimize the operating strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications. To our knowledge, the dataset1 presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for more than a year under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to cells. The dataset1 includes result data (such as the remaining usable capacity or impedance measured in check-ups) and raw data (i.e., measurement logs with two-second resolution). The data can be used in a wide range of applications, for example, to model battery degradation, gain insight into lithium plating, optimize operating strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.

Beyond the Horizon: Understanding Rural Secondary School Dropout through Case Studies

Despite numerous initiatives targeted to improve education outcomes, secondary school dropout rates in rural India remain a tenacious challenge. This paper sheds light on the underlying causes of dropout rates in rural areas through a qualitative case study approach. Drawing on in-depth interviews with rural students and their parents, this study examines the interplay of poverty, gender disparities, lack of access to quality education, and social expectations that contribute to students' decisions to leave school. The findings disclose the nuanced and complex ways various dynamics intersect and influence a student's educational trajectory. By exploring the personal, familial, and community factors that shape educational experiences, this study intends to contribute to a more comprehensive understanding of the dropout phenomenon in rural India. The findings have implications for policymakers, educators, and community leaders seeking operative strategies to address this prominent issue.

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

Uncertainty quantification of the inlet boundary conditions in a supercritical CO2 centrifugal compressor based on the non-intrusive polynomial chaos

Given the sensitivity of supercritical carbon dioxide centrifugal compressors performance to inlet boundary parameter fluctuations, this study focuses on the uncertainty quantification of the inlet boundary conditions. Non-intrusive polynomial chaos surrogate models were developed for both performance parameters and flow field of a supercritical carbon dioxide centrifugal compressor. Sensitivity and correlation analyses revealed that inlet total temperature is the primary influencing parameter. Fluctuations of 1.37 % in total temperature and 6.75 % in total pressure result in changes of 40.94 %, 18.57 %, and 1.77 % in mass flow rate, total pressure ratio, and total to total isentropic efficiency, respectively. Flow field statistical analysis shows that inlet uncertainties nonlinearly impact the dryness fraction and relative Mach number distributions near the blade leading edge, while the density in the condensation zone on the suction side of the leading edge is less affected. Error bands in static pressure on blade surfaces highlight significant variations, particularly at 90 % spanwise on the blade suction side, where shocks and supersonic flow induce prominent disturbances. This study offers a preliminary methodology and theoretical guidance for robust aerodynamic optimization and operational strategies of supercritical carbon dioxide centrifugal compressors.

A Mark-Recapture Approach to Estimating Item Pool Compromise

Testing organizations routinely investigate if secure exam material has been compromised and is consequently invalid for scoring and inclusion on future assessments. Beyond identifying individual compromised items, knowing the degree to which a form is compromised can inform decisions on whether the form can no longer be administered or when an item pool is compromised to such an extent that serious action on a broad scale must be taken to ensure the validity of score interpretations. Previous research on estimating the population of item compromise is sparse; however, this is a more generally long-studied problem in ecological research. In this note, we exemplify the utility of the mark-recapture technique to estimate the population of compromised items, first through a brief demonstration to introduce the fundamental concepts and then a more realistic scenario to illustrate applicability to large-scale testing programs. An effective use of this technique would be to longitudinally track changes in the estimated population to inform operational test security strategies. Many variations on mark-recapture exist and interpretation of the estimated population depends on several factors. Thus, this note is only meant to introduce the concept of mark-recapture as a useful application to evaluate a testing organization’s compromise mitigation procedures.

Circuit categorization approach of office building energy consumption based on data features for energy-saving diagnosis

Energy-saving in office buildings is crucial. Research on data-driven diagnostics of building energy consumption is pivotal. The emergence and development of itemized electricity platforms have expanded the scope of diagnosis from total building energy consumption to individual electrical equipment. However current studies rarely address the characteristics of sub-circuits. This paper highlights the importance of recognizing the features of electrical equipment sub-circuits based on historical energy consumption data by examining various aspects of energy use in office buildings, including electrical consumption disaggregation, equipment operational strategies, sub-item consumption proportion, and sub-circuit composition. A circuit categorization approach in office buildings by features analysis of historical data is innovatively proposed. Operational conditions, time series stationarity, and correlations with factors affecting energy consumption are considered in historical data feature analysis. The method categorizes the electric circuits into 5 categories with typical features based on the ADF-KPSS co-test and Spearman correlation analysis. The rationality and validity of the circuit categorization method were verified with actual building data in case studies. On this basis, an interpretable energy consumption anomaly diagnosis method based on the categorization results is proposed. The circuit categorization approach explores how to further investigate the typical features of sub-circuits, and provides new directions for subsequent building operation and maintenance(O&M) research, including energy consumption diagnostics. Additionally, it offers decision support for building managers for O&M evaluation from an interpretable perspective.

Shadows of fear: Extortion and protection racketeering amidst organized crime in South Africa

This paper investigates organized crime networks that engage in extortion and protection racketeering in South Africa. Due to socio-economic hardships and weak institutional frameworks, criminals have employed fear and violence as a means to gain control over local communities and businesses illegally. The study employed a literature analysis of scholarly materials such as peer-reviewed journals, books, and reports by law enforcement agencies and nongovernmental organizations among others to gather knowledge on extortion and protection racketeering in organized crime in South Africa. The study examines the operational strategies and impacts of organised crime networks on extortion and protection racketeering on local economies as well as public safety. The findings review that there is an all-pervasive culture of fear which underlies blackmailing as well as racketeering activities thereby increasing the vulnerability of communities while undermining social cohesion. The paper concludes by recommending policies meant to improve law enforcement capability and community resilience against this threat on communities.

Methane capture, utilization, and sequestration technology based on biological ectoine production using Methylotuvimicrobium alcaliphilum 20Z

Methanotroph-based CH4 conversion technology is a promising alternative to conventional CH4 utilization methods that rely on energy-intensive CO2 capture processes. In this study, we introduce a novel CH4 capture, utilization, and sequestration (MCUS) technology as a proof-of-concept for eco-friendly CH4 conversion that is applicable to various methanotroph strains. We validated this hypothesis by evaluating ectoine production in Methylotuvimicrobium alcaliphilum 20Z. Cultivation experiments were conducted using pure O2 pulse injection to facilitate the separation of the CO2 generated during CH4 oxidation by concentrating it. To verify the MCUS concept systematically, we performed a model-based process analysis. The operational strategies for the reactors were developed using experiment-based kinetics and reactor models, followed by the design of a rigorous process flow diagram. Economic and environmental impact analyses were conducted to compare MCUS with air-based cultures and existing oxidative CH4 conversion technologies. The key advantage of MCUS is its significantly lower CO2 emissions (0.71 kg-CO2 eq/kg-CH4) than oxidative CH4 utilization (>2.75 kg-CO2 eq/kg-CH4). Moreover, the net present value per CH4 molecule was estimated at 0.7 $/kg-CH4, substantially higher than existing oxidative conversion methods (0.03 $/kg-CH4). Additionally, compared with air-based cultivation, the MCUS process exhibits superior economic and environmental performances. We used methanotrophs for CH4 “capture” and “utilization,” effectively leveraging “sequestration” to convert emissions into pure CO2. The proposed MCUS technology holds promise for practical applications of methanotrophs in producing various high-value-added products, emphasizing eco-friendly approaches.

Performance analysis of multi-stack fuel cell systems for large buildings using electricity and heat

The fuel cell market, which utilizes hydrogen as a fuel for zero-carbon power generation to address global warming, continues to grow steadily. In the building sector, where small-scale fuel cells of 10 kW or less have been predominant, there is increasing interest in scaling up fuel cells to increase deployment and reduce system costs. The multi-stack fuel cell system (MFCS), which consists of connecting multiple modules, is one method of configuring large-scale fuel cell systems, offering advantages in system efficiency, durability, and cost. The objective of this paper is to compare and analyze the behavior of the MFCS according to different operation strategies. In particular, it compares the Equivalent operation method, which behaves similarly to the single-stack fuel cell system (SFCS), with others (Daisy-Chain, Electrical Optimization). Unlike previous studies that only focused on the electrical efficiency of MFCS, this study analyzed thermal energy, which is indispensable in building applications, to maximize the effects of MFCS. Simulation of operation strategies based on the electricity and heat demand of a specific residence showed that MFCS outperformed the SFCS in terms of electrical and heat efficiency, hydrogen consumption, degradation, and operating costs.

A novel approach for perfusion process design based on a "Grey-Box" kinetic model.

Perfusion cell-culture mode has caught industrial interest in the field of biomanufacturing in recent years. Thanks to new technology, perfusion-culture processes can support higher cell densities, higher productivities and longer process times. However, due to the inherent operational complexity and high running costs, the development and design of perfusion-culture processes remain challenging. Here, we present a model-based approach to design optimized perfusion cultures of Chinese Hamster Ovary cells. Initially, four batches of bench-top reactor continuous-perfusion-culture data were used to fit the model parameters. Then, we proposed the model-based process design approach, aiming to quickly find out the "theoretically optimal" operational parameters combinations (perfusion rate and the proportion of feed medium in perfusion medium) which could achieve the target steady-state VCD while minimizing both medium cost and perfusion rate during steady state. Meanwhile, we proposed a model-based dynamic operational parameters-adjustment strategy to address the issue of cell-growth inhibition due to the high osmolality of concentrated perfusion medium. In addition, we employed a dynamic feedback control method to aid this strategy in preventing potential nutrient depletion scenarios. Finally, we test the feasibility of the model-based process design approach in both shake flask semi-perfusion culture (targeted at 5 × 107 cells/ml) and bench-top reactor continuous perfusion culture (targeted at 1.1 × 108 cells/ml). This approach significantly reduces the number of experiments needed for process design and development, thereby accelerating the advancement of perfusion-mode cell-culture processes.

EP454 - Left Paraduodenal Hernia and Large Bowel Obstruction: A Case Report

Abstract Aims Internal hernias are uncommon and difficult to diagnose clinically. Of these, a paraduodenal hernia is the most common, but remains a rare condition. Cases reported in the literature are few and often describe small bowel obstruction as a result of small bowel herniation into the left paraduodenal space and lesser sac. Here we describe a case of left paraduodenal hernia resulting in large bowel obstruction. Method Written consent from the patient has been obtained to present the case and associated radiological and intra-operative images. A 50 year old male with no surgical history presented to the general surgical team via the emergency department with a 12 hour history of epigastric pain, vomiting, abdominal distension and 24 hours history of absolute constipation. CT showed a large bowel obstruction with a transition point in the mid transverse colon with a swirling of the mesentery and large bowel concerning for left paraduodenal hernia. Results Open laparotomy was the preferred approach. There was gross dilatation of the large bowel with a competent ileocaecal valve. The hepatic flexure was found herniating into the lesser sac under the ligament of Treitz. This was reduced and the large bowel decompressed via the appendix. The narrow based small bowel mesentery was expanded by dividing the mesenteric parietal peritoneum. The large defect was closed with interrupted non-absorbable sutures. The patient made an unremarkable post-operative recovery. Conclusion This is a rare pathology with interesting surgical anatomy and we present its radiological and intraoperative findings and operative management strategy.

The intersection of power: law enforcement, political authorities and protest policing in Italy

This article challenges the notion of police neutrality and independence by highlighting the inherent politicisation within the policing apparatus. It explores the complex relationship between the police and political authorities in managing crowds and maintaining public order. Drawing on criminological and sociological perspectives, the study adopts a critical approach to analyse the operational decisions made by the police and their interactions with political authorities. This interaction significantly influences the operational strategies employed during the management of public demonstrations. The dynamic emphasises how a segment of the police force in Italy is tasked with ‘political policing’, serving as a link between government authorities and field agents. Ultimately, this work aims to fill a gap in the literature by demonstrating the ongoing politicisation of the police mandate in Italy, particularly in the context of public order management.