Plant Configuration Research Articles

Techno-Economic Analysis of Power to Ammonia Production

This study introduces a novel methodology for conducting a techno-economic analysis of green ammonia production using mathematical models that meticulously parameterize plant units and technical specifications. The approach involves two key steps: first, identifying and modeling the essential components of green ammonia production, such as electrolyzers, ammonia synthesis units, and plant configurations; second, developing a non-linear optimization model to minimize the levelized cost of ammonia, payback period, internal rate of return, and return on investment. The model also incorporates constraints like maintaining minimum plant unit loads and optimizing electricity costs. By leveraging renewable energy through power purchase agreements, the study ensures a stable energy supply and carbon neutrality across the ammonia value chain. Two scenarios are examined: one with a user-defined electrolyzer configuration and another with an optimized configuration. In the latter, electricity consumption drops to 10 MWh per ton of ammonia produced, saving 60 GWh of energy annually, along with reductions in capital costs by 53% and operating costs by 10% compared to the first scenario.

Assessment of whole-site methane emissions from anaerobic digestion plants: Towards establishing emission factors for various plant configurations

This study examines methane (CH4) emission factors from biogas and wastewater treatment plants, based on primary and secondary data collected from 109 facilities. Primary emission data were measured at 19 facilities representing prevalent plant configurations across Europe. Statistical analysis highlights two categorical variables, namely primary feedstock and plant size, expressed as CH4 production (≤250 kgh−1: small and medium-sized plants, >250 kgh−1: large plants), each of which has a significant impact on whole-site CH4 emissions. Additionally, digestate storage (gastight vs. not-gastight) has a meaningful effect when considering CH4 production as a continuous variable in the statistical analysis.Our results indicate that wastewater treatment plants have the highest average CH4 losses (7.0 % of CH4 produced, n = 31 or 0.10 kgpopulation equivalent(PE)-1yr−1, n = 28), followed by manure-based plants (3.7 %, n = 49), biowaste treatment facilities (2.8 %, n = 11) and energy crop-processing plants (1.9 %, n = 14). Furthermore, small and medium-sized plants have elevated emissions (5.6 %, n = 67) compared to larger counterparts (2.2 %, n = 42), primarily attributed to the absence of gastight digestate storage. Emissions tend to be lower with gastight digestate storage (2.7 %, n = 61) than not-gastight storage options (6.2 %, n = 48).Emission factors were determined for normal operating conditions, with a further investigation into other-than-normal operating conditions revealing temporal or constant emission peaks in eight out of 19 facilities. These peaks, suggesting potential areas for targeted mitigation strategies, were attributed to pressure relief valves, flare ignition problems and major leakages.

Optimal configuration of a solar-powered Organic Rankine Cycle power plant utilizing thermochemical energy storage

Optimal configuration of a solar-powered Organic Rankine Cycle power plant utilizing thermochemical energy storage

Elman neural network optimized by improved golden search optimization algorithm for optimal designing of the hybrid renewable energy systems

ABSTRACT Hybrid renewable energy systems (HRESs) could offer a promising solution to the challenges of providing a dependable, economical and sustainable energy’s source. The integration of these technologies can help to overcome the limitations of intermittency, variability, and storage. Further, the economic and environmental benefits of HRESs make them an attractive option for widespread adoption in the future. However, designing an optimal configuration that can guarantee stable production at the minimum LCOE (Levelized Cost of Electricity) and LPSP (Loss of Power Supply Probability) values is the main concern of researchers. In this regard, the present study aims to optimize the configuration of a hybrid plant and determine the plant’s economic viability. The proposed plant, containing of a storing unit (VRFB, Vanadium Redox Flow Batteries-based battery energy storing), a solar photovoltaic (PV) plant, a wind farm, and a hydrogen storage system (for running an FC (Fuel Cell)), is designed to provide a stable production to the grid at a minimum LCOE value under least LPSP value and extra energy output. The development of the proposed optimal model for the HRES is based on an Elman Neural Network (ENN) model established by a new optimization algorithm (i.e. Improved Golden Search Optimization Algorithm (IGSOA)). The model is applied to a case study, San Luis Ayucan in Mexico, to verify the method efficacy. From the results, the storing system, including in cooperation battery and hydrogen indicate the main cost driver for each model arrangement with total cost percentage of 63.4%, 70.2%, 73.2%, and 73.7% for the proposed ENN/IGSOA, ENN, SVR, and ANN, respectively. Further, an ANN model had zero’s both an excess energy and an LPSP value; so, the system needs to rely heavily on energy storing to ensure that the stable load can be fulfilled. As a result, this increases the system’s total rate and subsequently results in a higher LCOE.

Performance Assessment of Atmospheric Water Generators: A Review of Evaluation Tools and Proposal for a Novel Advanced Global Evaluation Index for HVAC–AWG Hybrid Solutions

In the context of an increasing water crisis and rising energy consumption, an integrated approach to plant design and improvement can be highly effective. Specifically, the use of advanced multipurpose Atmospheric Water Generator (AWG) machines, integrated into existing or new HVAC systems, can improve efficiency while simultaneously extracting atmospheric water. However, hybrid plant configurations, which encompass both integrated and traditional solutions, can be difficult to assess. This paper presents a brief review of the most widely used AWG evaluation tools and proposes a new index, called AGEI, designed to address the knowledge gap in evaluating hybrid plants from an efficiency perspective. The paper shows how this index provides results that more accurately reflect the real efficiency of hybrid plant configurations compared to the Global Evaluation Index (GEI), which is the only existing tool addressed to the evaluation of integrated multipurpose machines. The work is complemented by the application of AGEI to three complex hybrid plant configurations, two of which include a bottling system supplied by desalination for drinking water production. The index is straightforward and requires only knowledge of the useful effects produced by the analysed plant and their corresponding efficiency indicators.

Optimization of High-Density Planting Configurations for Poovan Banana (Musa spp.) in Coconut-Based Agroforestry Systems of the Cauvery Delta Zone

Bananas (Musa spp.) are a vital global agricultural commodity and an essential crop in tropical agricultural systems. The Poovan cultivar, known for its high productivity and adaptability, is particularly effective in intercropping within coconut-based agroforestry systems. This study investigates the impact of planting geometries on crop performance in the Cauvery Delta Zone by evaluating five spatial configurations, ranging from 2.1×2.1m to 0.9×0.9m, with a focus on morphological, physiological, and economic parameters. The results indicate that wider spacing configurations, especially 2.1×2.1m, significantly improve leaf morphological traits, including maximum leaf length (148.17 cm), breadth (77.75 cm), and leaf area index (2.61m²/plant). Additionally, these configurations enhance key fruit quality characteristics, such as increased bunch weight (16kg), improved fruit dimensions (20cm length), higher sugar content (22°Brix), and greater fruit firmness (4.5kg/cm²). The economic analysis suggests that a 1.5×1.5m spacing provides the most favorable cost-benefit ratio (1.14). This study offers valuable insights into the complex relationships between planting density, resource allocation, and productivity in tropical farming systems, providing evidence-based recommendations for optimizing both agricultural performance and economic viability in integrated farming systems.

Energetic and economic advantages of energy communities: a case study referred to a southern Italian town

Energy Districts and Communities are at the heart of EU programs. Nevertheless, several challenges are encountered when bringing into fruition. Their convenience is not fully understood on a small scale, due to the complexity of the start-up practices, which make them more suitable for commercial or industrial companies. In this scenario the present study arises, aimed at pointing out to small communities, at condominium scale, the economic benefits, in terms of Net Present Value (NPV), deriving from the adoption of the new community plant configurations. Such indicator gives a glance of the total cost, both investment and functioning ones, to be sustained during the plant life, together with the enjoyed benefits. Particularly the investment cost is presently a big obstacle to the spread of renewable energy systems whereas the high operative cost of conventional plants is less adequately considered. In this frame, through the paper the satisfaction of the electricity needs of the users of a building, sited in Reggio Calabria (Italy), when their plant configurations turn from single grid-connected into community is analyzed using 2024 tariffs. From the study the economic advantages of the community result, pointing out an NPV increase (€ 3798), with a consequent reduction of the investment pay-back time for most users. The benefit increases (€ 24,918) when an energy intensive user joins the community. The study also considers a plant configuration equipped with storage, pointing out the reduced grid exchanges: a lower injection of 5.6 MWh and a lower withdrawal of 6.9 MWh. Concerning NPV, despite the batteries cost and their replacement every 10 years, only low reductions are observed, thanks to the great saving obtained by stored energy, that make the investment convenient. In the future the study will be enriched with the analysis of plant configurations that consider aggregation among adjacent buildings.

Techno-economic assessment of a green liquid hydrogen supply chain for ship refueling

Maritime transportation is an essential component of international trade and global economic growth: according to the 2021 Review of Maritime Transport, transportation by sea is responsible for more than 80% of the global product flow. To facilitate decarbonization and reduce pollutant emissions in the maritime sector, the International Maritime Organization (IMO) has set very ambitious targets, and hydrogen is one of the most promising energy vectors capable of supporting the required low-carbon energy transition. Recently, therefore, more attention has been paid to finding technical solutions for the development of hydrogen-based alternative propulsion systems and, at the same time, a hydrogen distribution infrastructure suitable for shipping. In this scenario, this study aims to analyze, through design, modeling and optimization approaches, the energy and economic performance of an offshore wind power plant integrated with a liquid hydrogen production system to be used for refueling ships far from ports. This study focuses on the development of an optimization procedure dedicated to finding the best technical solution in terms of component sizes and management strategies that ensure the minimum Levelized Cost of Hydrogen (LCOH). Resultshave highlighted that the proposed innovative plant configuration for the offshore liquid hydrogen production is able to produce 317 tons per year of green hydrogen with a LCOH of 16.77 €/kg by using 19 MW offshore wind farm and 5 MW PEM electrolyzer.

Optimization of Wetland Plant Selection and Configuration in Urban Water Environment Ecological Restoration Projects

Optimization of Wetland Plant Selection and Configuration in Urban Water Environment Ecological Restoration Projects

Photovoltaic power forecasting: A Transformer based framework

The accurate prediction of photovoltaic (PV) energy production is a crucial task to optimise the integration of solar energy into the power grid and maximise the benefit of renewable source trading in the energy market. This paper systematically and quantitatively analyses the literature by comparing different machine learning techniques and the impact of different meteorological forecast providers. The methodology consists of an irradiance model coupled with a meteorological provider; this combination removes the constraint of a local irradiance measurement. The result is a Transformer Neural Network architecture, trained and tested using OpenMeteo data, whose performance is superior to other combinations, providing a MAE of 1.22 kW (0.95%), and a MAPE of 2.21%. The implications of our study suggest that adopting a comprehensive approach, integrating local weather data, modelled irradiance, and PV plant configuration data, can significantly improve the accuracy of PV power forecasting, thus contributing to more effective technological and economic integration.

Planting Strategy Influences Vegetable Response to Glyphosate and Glufosinate Applied Preplant in Plasticulture

Abstract In Georgia plasticulture vegetable production, a single installation of plastic mulch is utilized for up to five cropping cycles over an 18-month period. Preplant applications of glyphosate and glufosinate ensure fields are weed-free before transplanting, but recent data suggest residual activity of these herbicides may pose a risk to transplanted vegetables. Glyphosate and glufosinate were applied preplant in combination with three different planting configurations, including 1) a new plant hole into new mulch, 2) a pre-existing plant hole, 3) or a new plant hole spaced 15 cm from a pre-existing plant hole (adjacent). Following herbicide application, overhead irrigation was utilized to remove residues from the mulch before punching transplanting holes for tomato, cucumber, or squash. Visible injury, widths, biomass, yield of tomato, cucumber, or squash were not influenced by herbicide in the new mulch or adjacent planting configurations. When glyphosate was applied at 5.0 kg ae ha-1 and the new crop was planted into pre-existing holes, tomato was injured 45%, with reduced heights, biomass, and yields; at 2.5 kg ae ha-1 injury of 8% and a biomass reduction was observed. Cucumber and squash were injured 23% to 32% by glyphosate at 5.0 kg ae ha-1, with reductions in growth and early-season yield; lower rates did not influence crop growth or production when the crop was placed into a pre-existing plant hole. Glufosinate at the same rates did not affect tomato growth or yield when planted into pre-existing plant holes. Cucumber, when planted into pre-existing plant holes, was injured 43 to 75% from glufosinate, with reductions in height and biomass, and yield losses at 1.3 and 2.6 kg ai ha-1; similar results from glufosinate were observed in squash. In multi-crop plasticulture production, growers should ensure vegetable transplants are placed a minimum of 15 cm away from soil exposed to these herbicides.

Optimised scheduling of a cogenerative subnetwork based on a micro gas turbine and thermal storage with the addition of an innovative solar assisted heat pump and Ni-Zn battery

The Innovative Energy Systems (IES) laboratory at the University of Genoa features a plant configuration comprising a micro gas turbine, latent heat thermal energy storage, an innovative heat pump system connected to solar façade panels, and a NiZn battery. This study presents the optimization of four distinct sub-plant configurations, focusing on their economic and environmental performance across different seasons (January, April, July, and October) under two market scenarios (no selling price or selling price equal to buying price). A genetic algorithm-based tool is developed for the optimized energy scheduling of these configurations, taking into account the operational characteristics of programmable, non-programmable energy sources and energy storage devices. The analysis highlighted that when the selling price is equal to zero, the system is optimised to improve sell-consumption. The addition of the battery or the heat pump to the system always leads to reduction of operational costs compared to the baseline case with only the micro gas turbine and thermal energy storage. Notably, the heat pump alone provides greater cost benefits than the battery, although the combined use of both systems yields the highest cost reductions ranging, depending on the month, up to −16.9% in the “no sell” scenario and up to −12.3% when selling and buying prices are equal. Regarding the CO2 emissions, both components lead to an emission reduction in the “no sell” scenario while only the HP guarantees an emission reduction during the “equal to buy” scenario, in both cases up to −20.5% less. This analysis highlights the economic and environmental advantages of integrating NiZn battery storage and a solar-assisted heat pump into the energy system, demonstrating cost savings and emission reductions across various market conditions and seasonal demands.

A comparative study of time-related performance: COBOT with industrial robots using digital twin robotic cells

In the context of the industry 4.0, defined by highly personalized processes, there’s a rising interest of technologies related to the extraction of data of the process in real time to better decide future actions i.e. define more efficient and productive configurations of the industrial plant. From this, Cyber-physical systems such as digital twins are the most suited technology to follow the process performance through data and reliably validate different outcomes from simulations. Furthermore, COBOTs that can adapt to the environment are ideal to deal with such changing demands which have to work alongside industrial robots. Therefore, this study aims to use the digital twin capabilities of data extraction and simulation from the FANUC’s robot simulator software to validate the performance of industrial and collaborative robots in order to offer insights to better apply each type of robot. It was used a robotic cell with the robot PRBT 6 as a reference to make 2 digital twins of the cell with 2 different robot models, one collaborative and one industrial. Two digital twins were made using ROBOGUIDE simulator, version 9.4 for the COBOT and version 9.1 for the industrial robot. It’s presented the method used to build the digital twin of the robotic cell and the results show that the cycle time of the COBOT’s cell is significantly higher than the industrial one but has higher flexibility.

Exploiting the Ocean Thermal Energy Conversion (OTEC) technology for green hydrogen production and storage: Exergo-economic analysis

This study presents and analyses three plant configurations of the Ocean Thermal Energy Conversion (OTEC) technology. All the solutions are based on using the OTEC system to obtain hydrogen through an electrolyzer. The hydrogen is then compressed and stored. In the first and second layouts, a Rankine cycle with ammonia and a mixture of water and ethanol is utilised respectively; in the third layout, a Kalina cycle is considered. In each configuration, the OTEC cycle is coupled with a polymer electrolyte membrane (PEM) electrolyzer and the compression and storage system. The water entering the electrolyzer is pre-heated to 80 °C by a solar collector. Energy, exergy, and exergo-economic studies were conducted to evaluate the cost of producing, compressing, and storing hydrogen. A parametric analysis examining the main design constraints was performed based on the temperature range of the condenser, the mass flow ratio of hot and cold resource flows, and the mass fraction. The maximum value of the overall exergy efficiency calculated is equal to 93.5% for the Kalina cycle, and 0.524 €/kWh is the minimum cost of hydrogen production achieved. The results were compared with typical data from other hydrogen production systems.

Effects of Earthworm Density on Greenhouse Gas Emissions from Constructed Wetlands with Different Plant Configurations

Effects of Earthworm Density on Greenhouse Gas Emissions from Constructed Wetlands with Different Plant Configurations

Vertical Plant Configuration: Its Impact on Microclimate and Thermal Comfort in Urban Small Green Spaces

The presence of small green spaces throughout high-density urban areas is essential for enhancing thermal comfort and combating the urban heat island effect. Extensive research has been conducted on plants, which play a key role in cooling green spaces. However, the majority of research focuses on trees, overlooking the efficiency of vertical plant configurations, especially shrubs. Hence, this paper selected a typical small green space in Tokyo’s high-density urban area and employed scenario simulation to examine how various vertical plant configurations impact the microclimate and thermal comfort of small green spaces, with a particular emphasis on quantifying the efficiency of shrubs. The research primarily discovered four findings. First, trees significantly outperform shrubs in improving thermal comfort, especially during periods of strong sunlight during the day, leading to a direct modification of the thermal comfort levels. Second, while shrubs (height < 2 m) usually do not make a substantial difference in the overall thermal comfort levels of small green spaces, they are effective in reducing areas classified as “hot” and “very hot” during the day, with their cooling effect becoming more pronounced in the late afternoon. Third, when small green spaces combine trees and shrubs in their plant configuration, taller shrubs (within 0–2 m) exhibit a more pronounced cooling effect and improvement in thermal comfort. The conclusions of this study could offer guidance for the planning, design, and renovation of small green spaces in high-density urban areas.

A Study on Vegetation Restoration and Ecological Rehabilitation of Mine Slopes Based on Bioengineering Technology

This paper studies the application of bioengineering technology for vegetation restoration and ecological rehabilitation of mine slopes. Bioengineering technology is a comprehensive engineering technology that uses living plants and other auxiliary materials to construct slope structures, and realizes the stability, vegetation restoration and ecological rehabilitation of the slopes. Then, the paper reveals the principle and mechanism of bioengineering technology, which is mainly to use the parts of plants, such as roots, stems and leaves, to reinforce, fix and protect the slope soil, and to improve and regulate the slope ecosystem. The paper further explores the methods and techniques of bioengineering technology, and studies and summarizes the specific methods and techniques of plant selection, configuration, planting and management of bioengineering technology. Finally, the paper points out the problems and challenges of bioengineering technology, such as the imperfection of theory and method, the limitation of application and promotion, the deficiency of monitoring and management, and the uncertainty of social and environmental impact, and suggests further research and exploration of bioengineering technology. The paper concludes that bioengineering technology is a promising technology for vegetation restoration and ecological rehabilitation of slopes.

Introduction and Agrotechnology of Greek Chambala (Trigonella Foenum-Graecum L.) in Surkhondaryo Region

This research explores the introduction and agrotechnology of Greek Chambala (Trigonella foenum-graecum L.) in the Surkhandarya region of Uzbekistan. The study focuses on the growth development and medicinal properties of this leguminous herb, with particular emphasis on agrotechnological factors such as planting dates, row spacing, and chemical protection measures that influence productivity. Greek Chambala is valued for its bioactive compounds, known for medicinal benefits like managing diabetes and obesity. The experiment was conducted at the "Jonchekka Sarhadlari" farm using different planting configurations and fertilization methods. The results showed that planting in November yielded optimal seed development and contributed to soil fertility through nitrogen fixation. The findings provide practical insights for enhancing the cultivation of Greek Chambala in Surkhandarya's climatic conditions, making it a promising crop for both agricultural and medicinal purposes.

Development of near-optimal advanced control sequences for chiller plants with water-side economizers in U.S. Climates (ASHRAE RP-1661)

Various advanced control sequences for chiller plants with water-side economizers (WSE) have been proposed in literature, but the evaluation and optimization of those controls is limited. It is possible to maximize energy savings by selecting different sequences and related parameters based on the plant configuration, load, and climate. This paper addresses this gap by developing near-optimal advanced control sequences for chiller plants with WSEs. First, advanced control sequences for chiller plants with WSEs are categorized into condenser water, chilled water, and hybrid controls and representative sequences from each category are identified. Next, 504 different scenarios are optimized. These scenarios represent all possible combinations of two plant configurations, a constant or variable load profile, three advanced control sequences, and seven optimization parameter combinations in six climate zones. The results show the recommended near-optimal sequences can reduce energy consumption by up to 15% relative to the baseline depending on the configuration, load profile, and climate. Specifically, the CW-CHW sequence is recommended for the majority of systems because it is often the most energy efficient and/or reduces the runtime of chillers. The methodology in this paper provides practical guidance for achieving energy savings through near-optimal control of chiller plants with WSEs.

How to alleviate seasonal limitations on water quality in farmland ditches? The importance of plant selection and configuration

In subtropical monsoon climate regions, traditional plants in constructed wetlands such as farmland ditches underperform in cold months, detracting from both purification capacity and esthetic appeal. To alleviate this weakness, this study introduced Phalaris arundinacea, a species with strong adaptability and cold tolerance, into a plant community dominated by Phragmites australis, constructing an ingenious composite plant community for year‐round water quality restoration and enhancement of attractiveness. First, laboratory simulations revealed significant seasonal differences in the removal rates of ammonia nitrogen (NH3‐N), total nitrogen (TN), and total phosphorus (TP) by the P. arundinacea community and P. australis community under different pollutant loads. Phragmites australis showed superior NH3‐N and TN removal capabilities from May to October, whereas P. arundinacea excelled in the rest of the months throughout the year. For TP removal, P. australis outperformed P. arundinacea from July to October, while P. arundinacea was more effective from January to May. We then verified this in rear farmland ditches, where P. australis were strategically partial substituted with P. arundinacea (Partial Replacement Treatment [PRT]), and compared it with unchanged farmland ditches (Control Treatment). We found that PRT enhanced decontamination efficiency over the year, especially significantly improving the water quality during colder months. Hence, this study advocates a novel strategy for effective annual decontamination and maintenance of wetlands such as farmland ditches, highlighting the importance of seasonally adaptive plant communities for water restoration. This transformative approach dramatically advances the field of wetland management, insisting on the important role of cold‐resistant species for year‐round ecosystem service optimization.