The Experts below are selected from a list of 1154592 Experts worldwide ranked by ideXlab platform
J. M. Serrano - One of the best experts on this subject based on the ideXlab platform.
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Mapping management zones in a sandy pasture soil using an Objective Model and multivariate techniques
Precision Agriculture, 2020Co-Authors: F. J. Moral, F. J. Rebollo, J. M. Serrano, F. CarvajalAbstract:Soils occupied by dryland pastures usually have low fertility but can exhibit a high spatial variability. Consequently, logical application of fertilisers should be based on an appropriate knowledge of spatial variability of the main soil properties that can affect pasture yield and quality. Delineation of zones with similar soil fertility is necessary to implement site-specific management, reinforcing the interest of methods to identify these homogeneous zones. Thus, the formulation of the Objective Rasch Model constitutes a new approach in pasture fields. A case study was performed in a pasture field located in a montado (agrosilvopastoral) ecosystem. Measurements of some soil properties (texture, organic matter, nitrogen, phosphorus, potassium, cation exchange capacity and soil apparent electrical conductivity) at 24 sampling locations were integrated in the Rasch Model. A classification of all sampling locations according to pasture soil fertility was established. Moreover, the influence of each soil property on the soil fertility was highlighted, with the clay content the most influential property in this sandy soil. Then, a clustering process was undertaken to delimit the homogeneous zones, considering soil pasture fertility, elevation and slope as the input layers. Three zones were delineated and vegetation indices (normalized difference vegetation index, NDVI, and normalized difference water index, NDWI) and pasture yield data at sampling locations were employed to check their differences. Results showed that vegetation indices were not suitable to detect the spatial variability between zones. However, differences in pasture yield and quality were evident, besides some key soil properties, such as clay content and organic matter.
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Delineating site-specific management zones on pasture soil using a probabilistic and Objective Model and geostatistical techniques
Precision Agriculture, 2019Co-Authors: Francisco J. Moral, Francisco J. Rebollo, J. M. SerranoAbstract:In recent years, different algorithms have been utilised to delineate management zones, areas with similar properties, within agricultural fields. However, there are few applications in pasture systems. In this work, the formulation of the Rasch Model, as an Objective and probabilistic technique to integrate different soil properties, provided measures of pasture soil fertility that were used to analyse spatial variability throughout a field. To illustrate the proposed approach, a case study was conducted in a pasture field. Ten soil properties (sand, silt, and clay contents, moisture content, pH, organic matter, nitrogen, phosphorus, potassium, and soil apparent electrical conductivity) were measured at 76 locations in a pasture field; after their integration in the Model, a classification of all sampling locations according to pasture soil fertility was determined, and the influence of each soil property on the soil fertility was highlighted, with the soil moisture, clay, and sand contents and nitrogen being the most influential properties and the silt content being the least influential property. Then, an ordinary kriging algorithm was used to estimate pasture soil fertility throughout the field, and homogeneous zones were delimited from the kriged map. The possibility of using probability maps to determine management zones and provide information for hazard assessments of pasture soil fertility in the field was also shown. Finally, NDVI data at each sampling location were utilised to verify the differences between the management zones.
Kazem Zare - One of the best experts on this subject based on the ideXlab platform.
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optimal performance of microgrid in the presence of demand response exchange a stochastic multi Objective Model
Computers & Electrical Engineering, 2019Co-Authors: Tohid Khalili, Sayyad Nojavan, Kazem ZareAbstract:Abstract This paper investigates optimal scheduling of the microgrids, including renewable energy sources and conventional generators. Due to the stochastic nature of the wind speed and the sun irradiation, generated power of the wind turbines and photovoltaic are highly uncertain and in the proposed Model the uncertainty of the load, price, and renewable energy sources generation are considered by utilizing the normal distribution function. Incentive-based demand response program is implemented in the operating process. The optimal economic status is achieved by maximizing the microgrid's demand response program profit and minimizing the generators cost, and the trading cost. This multi-Objective Model is solved by the weighted sum technique in order to produce the optimal Pareto solutions and the trade-off solution is selected by applying the fuzzy satisfying method. It is performed on two different microgrids and sensitivity analysis is executed. Results demonstrate that demand response program reduces unused energy in both scenarios.
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a multi Objective Model for optimal operation of a battery pv fuel cell grid hybrid energy system using weighted sum technique and fuzzy satisfying approach considering responsible load management
Solar Energy, 2017Co-Authors: Majid Majidi, Sayyad Nojavan, Naser Nourani Esfetanaj, Afshin Najafighalelou, Kazem ZareAbstract:Abstract In the past, no attention was paid to the kinds of sources by which loads were supplied and the only energy resource supplying electrical demand was the upstream grid. Recently, due to the appearance of new technologies in the field of energy resources such as distributed generation systems, operators are encouraged to use these resources along with upstream grid to ensure a reliable power to the load and reduce the role of upstream grid in supplying electrical demand. In the proposed paper, several renewable and non-renewable energy sources like photovoltaic system (PV), fuel cell (FC) and battery storage are integrated in a grid-connected hybrid energy system to supply energy demand. In this paper, a multi-Objective optimization Model is proposed to solve the cost-emission problem of battery/PV/fuel cell hybrid system in the presence of demand response program (DRP). Two conflicting Objective functions namely minimization of total cost of hybrid system and reduction of CO 2 emission are the main goal of proposed multi-Objective Model. The proposed Model is solved by weighted sum technique and the best possible solution is selected by employing fuzzy satisfying approach. DRP transfers some amount of load from peak periods to other periods which flattens the load curve and minimizes total cost of system. A mixed-integer linear program is used to Model the proposed cost-emission operation problem of hybrid system and it is solved by GAMS software. Two different cases have been studied to show the effects of DRP and the results are compared.
Francisco J. Moral - One of the best experts on this subject based on the ideXlab platform.
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Delineating site-specific management zones on pasture soil using a probabilistic and Objective Model and geostatistical techniques
Precision Agriculture, 2019Co-Authors: Francisco J. Moral, Francisco J. Rebollo, J. M. SerranoAbstract:In recent years, different algorithms have been utilised to delineate management zones, areas with similar properties, within agricultural fields. However, there are few applications in pasture systems. In this work, the formulation of the Rasch Model, as an Objective and probabilistic technique to integrate different soil properties, provided measures of pasture soil fertility that were used to analyse spatial variability throughout a field. To illustrate the proposed approach, a case study was conducted in a pasture field. Ten soil properties (sand, silt, and clay contents, moisture content, pH, organic matter, nitrogen, phosphorus, potassium, and soil apparent electrical conductivity) were measured at 76 locations in a pasture field; after their integration in the Model, a classification of all sampling locations according to pasture soil fertility was determined, and the influence of each soil property on the soil fertility was highlighted, with the soil moisture, clay, and sand contents and nitrogen being the most influential properties and the silt content being the least influential property. Then, an ordinary kriging algorithm was used to estimate pasture soil fertility throughout the field, and homogeneous zones were delimited from the kriged map. The possibility of using probability maps to determine management zones and provide information for hazard assessments of pasture soil fertility in the field was also shown. Finally, NDVI data at each sampling location were utilised to verify the differences between the management zones.
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Using an Objective Model to estimate overall ozone levels at different urban locations
Stochastic Environmental Research and Risk Assessment, 2014Co-Authors: Francisco J. Moral, Francisco J. Rebollo, Francisco MéndezAbstract:Ground-level tropospheric ozone is one of the air pollutants of most concern. Ozone levels become particularly high in regions close to high ozone precursor emissions and during summer, when high insolation and high temperatures are common. Ozone levels continue to exceed both target values and the long-term Objectives established in EU legislation to protect human health and prevent damage to ecosystems, agricultural crops and materials. Researchers or decision-makers frequently need information about atmospheric pollution patterns in urbanized areas. The preparation of this type of information is a complex task, due to the influence of several factors and their variability over time. In this work, some results of urban ozone distribution patterns in the city of Badajoz, which is the largest (140,000 inhabitants) and most industrialized city in Extremadura region (southwest Spain) are shown. Twelve sampling campaigns, one per month, were carried out to measure ambient air ozone concentrations, during periods that were selected according to favourable conditions to ozone production, using an automatic portable analyzer. Later, to evaluate the overall ozone level at each sampling location during the time interval considered, the measured ozone data were analysed using a new methodology based on the formulation of the Rasch Model. As a result, a classification of all locations according to the ozone level, which was the value of the Rasch measure, was obtained. Moreover, information about unexpected behaviours of ozone patterns was generated. Finally, overall ozone level at locations where no measurements were available was estimated which can be used to generate hazard assessment maps.
Gang Chen - One of the best experts on this subject based on the ideXlab platform.
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reducing truck emissions at container terminals in a low carbon economy proposal of a queueing based bi Objective Model for optimizing truck arrival pattern
Transportation Research Part E-logistics and Transportation Review, 2013Co-Authors: Gang Chen, Kannan Govindan, Mihalis M GoliasAbstract:This study proposes a methodology to optimize truck arrival patterns to reduce emissions from idling truck engines at marine container terminals. A bi-Objective Model is developed minimizing both truck waiting times and truck arrival pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck arrivals can significantly reduce truck emissions, especially at the gate.
F. Carvajal - One of the best experts on this subject based on the ideXlab platform.
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Mapping management zones in a sandy pasture soil using an Objective Model and multivariate techniques
Precision Agriculture, 2020Co-Authors: F. J. Moral, F. J. Rebollo, J. M. Serrano, F. CarvajalAbstract:Soils occupied by dryland pastures usually have low fertility but can exhibit a high spatial variability. Consequently, logical application of fertilisers should be based on an appropriate knowledge of spatial variability of the main soil properties that can affect pasture yield and quality. Delineation of zones with similar soil fertility is necessary to implement site-specific management, reinforcing the interest of methods to identify these homogeneous zones. Thus, the formulation of the Objective Rasch Model constitutes a new approach in pasture fields. A case study was performed in a pasture field located in a montado (agrosilvopastoral) ecosystem. Measurements of some soil properties (texture, organic matter, nitrogen, phosphorus, potassium, cation exchange capacity and soil apparent electrical conductivity) at 24 sampling locations were integrated in the Rasch Model. A classification of all sampling locations according to pasture soil fertility was established. Moreover, the influence of each soil property on the soil fertility was highlighted, with the clay content the most influential property in this sandy soil. Then, a clustering process was undertaken to delimit the homogeneous zones, considering soil pasture fertility, elevation and slope as the input layers. Three zones were delineated and vegetation indices (normalized difference vegetation index, NDVI, and normalized difference water index, NDWI) and pasture yield data at sampling locations were employed to check their differences. Results showed that vegetation indices were not suitable to detect the spatial variability between zones. However, differences in pasture yield and quality were evident, besides some key soil properties, such as clay content and organic matter.
