Large-scale Farms Research Articles

Decision Support Systems adoption in pesticide management

This paper presents the findings from a survey on factors influencing the adoption of agricultural Decision Support Systems (DSS). Our study focuses on examining the influence of behavioural, socioeconomic and farm specific characteristics on DSS adoption. Using two structural equation models, we investigate how these factors influence the willingness to pay (WTP) and willingness to adopt. Our analysis reveals nuanced insights into the user and farm-specific factors that influence the decision-making process of DSS adoption and WTP. Notably, farm size significantly influences both adoption and WTP, with larger farms more likely to adopt and exhibit higher WTP. To promote adoption, it is important to adapt promotion strategies, with a focus on productivity benefits for large-scale farms and addressing price barriers for smaller ones. Additionally, the main crop type grown impacts WTP and adoption, with arable crop farmers exhibit a lower WTP but more likely to adopt, especially in large-scale operations. Conversely, small-scale arable farmers exhibit higher WTP but lower adoption rates due to scale constraints. Farmer characteristics such as experience and attitudes also play a crucial role, with experienced users and those perceiving productivity improvements due to DSS showing higher WTP. In addition, adoption is also influenced by ease of use and pricing, underpinning the importance of user-friendly designs and clear cost justifications. DSSs with user-centric designs and clear cost justifications can enhance adoption rates.

Archetypes of climate change adaptation among large-scale arable farmers in southern Romania

Effects of climate change and especially the associated climate variability require farmers to adjust to increasing frequencies of extreme events. In the agriculturally highly productive Romanian Plain, the frequency, intensity, and duration of heatwaves and drought have increased over the past 20 years. Although recent surveys revealed farmers’ awareness of climate change and enumerated a number of farm adaptation measures in the Romanian context, a systems approach to adaptation that allows conclusions on farm vulnerability and adaptive capacity is missing. Here, we use archetypal analysis to elucidate and characterize for the first time the types of adaptation responses of arable farmers in southern Romania. We conducted semi-structured interviews with 30 farmers managing 51,500 ha located across the southern lowlands of Romania, selected for their diversity of management approaches. Farmers were asked about experienced climatic disturbances, crop production losses during the most extreme events over the past 5–10 years, and the adaptation measures they implemented over that period of time. In addition, structural characteristics of the farm were recorded. The adaptation measures were classified and mapped on the efficiency, substitution, and redesign gradient used to classify sustainability stages. Results revealed three archetypes of adaptation, consisting of measures at field and farm level ranging from predominantly efficiency-enhancing ones (e.g., crop choice and management and risk insurance) to complete farm redesign involving agrotechnical and financial management changes. Structural farm characteristics did not explain differences between farms in their association with one of the archetypes. Our approach and results show for the first time both the need for strengthening farmer-level support in one of Europe’s key food production areas and the lessons that can be drawn from the outlier adaptation examples. Current European and national policies offer opportunities for farmer organizations in Romania to make these conclusions actionable.

Environmental and Human Risk Assessment from Pesticides During Irrigation Practices: A Case of Haik, Amhara, Ethiopia

Agriculture is the backbone of the Ethiopian economy. Therefore, to increase productivity and to alleviate food insecurity, pesticides were used for in large-scale and small-scale irrigation farming system. On the other hand, pesticides have high risk on the environment and human beings, to estimate this type of pesticide risks the PRIMET model were used. The four main steps were used in this study. The first step was to collect data from secondary sources and the literature. The second step was focused on consulting partners and local communities. The third step of the study mainly focused on identifying analytical and data collection tools. Lastly, risk identification and quantification were developed. The application dose of 2,4-D and Malathion were higher than other pesticides, and its value were 1750 and 1400 g/ha. The predicted environmental concentration values of Lambdacyhalothrin, Malathion, 2,4-D, Propiconazole, and Profenofos pesticides for Fish, Daphnia, and Algae were 0.15,0.25,0.53,0.89 and 0.12 respectively. Propiconazole pesticides were 5000 g/ha and 68.6 mg/kg, which were higher than other pesticides in the terrestrial and Bee risk assessment type. The lambda-cyhalothrin was the higher risk, and ETR values pesticide for Fish, Daphnia, Algae, and Bees, and its ETR values were 70, 64, 6.99, and 5.50. The Profenofos pesticide ETR values were 59.63 and 49.12, which means high risk for terrestrial and Bee risk assessment. The ESTI% value of Lambdacyhalothrin, Malathion, 2,4-D, Propiconazole, and Profenofos pesticides were 0.29, 0.01, 0.11, 0.03, and 0.00. The higher the PEC value, the higher ETR, and ESTI%, which means the pesticide was a higher potential risk to the environment and human beings. The lambda-cyhalothrin and Malathion pesticides were at high possible risk in Lake Haik organisms (Fish, Daphnia, Algae) and Bee around the Lake. The Lambda-cyhalothrin pesticide was a higher potential risk pesticide for humans.

Investigating Economic and Climate Signals in Groundwater Data

Hydrologic, climatic, regulatory and economic factors interact in complex ways to influence groundwater conditions. These relationships can be difficult to measure and model but are important for water management and for considering viable futures for regional economies. This paper proposes a strategy for an improved understanding of how groundwater levels reflect signals of regulatory, economic and climate factors. Most existing econometric studies of groundwater use focus on large-scale irrigated agriculture and urbanized areas in first world nations, where groundwater extraction data is available. In much of the world, groundwater extraction data are not available for individual farms and other water users. The goal of this study is to explore the responsiveness of groundwater levels (a more widely available measure of groundwater conditions) to regulatory, economic and climate signals in rural areas, using a growing body of remotely sensed land cover data. Pooled Ordinary Least Squares econometric models examine the effects of regulatory, climatic and economic factors on groundwater levels in rural Arizona. Groundwater regulations, recharge projects, housing units and irrigated acreage have statistically significant relationships to groundwater levels in the study areas. This approach can be valuable for understanding factors that influence groundwater conditions and which may be useful in managing groundwater use in widespread areas where groundwater extraction data is unavailable.

National Greenhouse Gas Emission Reduction Potential from Adopting Anaerobic Digestion on Large-Scale Dairy Farms in the United States.

Waste-to-energy systems can provide a functional demonstration of the economic and environmental benefits of circularity, innovation, and reimagining existing systems. This study offers a robust quantification of the greenhouse gas (GHG) emission reduction potential of the adoption of anaerobic digestion (AD) technology on applicable large-scale dairy farms in the contiguous United States. GHG reduction estimates were developed through a robust life cycle modeling framework paired with sensitivity and uncertainty analyses. Twenty dairy configurations were modeled to capture important differences in housing and manure management practices, applicable AD technologies, regional climates, storage cleanout schedules, and methods of land application. Monte Carlo results for the 90% confidence interval illustrate the potential for AD adoption to reduce GHG emissions from the large-scale dairy industry by 2.45-3.52 MMT of CO2-eq per year considering biogas use only in renewable natural gas programs and as much as 4.53-6.46 MMT of CO2-eq per year with combined heat and power as an additional biogas use case. At the farm level, AD technology may reduce GHG emissions from manure management systems by 58.1-79.8% depending on the region. Discussion focuses on regional differences in GHG emissions from manure management strategies and the challenges and opportunities surrounding AD adoption.

The effect of pollen monodiets on fat body morphology parameters and energy substrate levels in the fat body and hemolymph of Apis mellifera L. workers

Human activities associated with large-scale farms and the monocultures expose honey bees to one type of food. Moreover, there is an ongoing decline of plant species producing pollen and nectar in Europe. A poorly balanced diet affects a number of processes occurring in a bee’s body. The fat body and hemolymph are the tissues that participate in all of them. Therefore, the aim of our study was to determine the effect of hazel, pine, rapeseed, buckwheat, phacelia and goldenrod pollen on the morphological parameters of fat body trophocytes, the diameters of cell nuclei in oenocytes and the concentrations of compounds involved in energy metabolism (glucose, glycogen, triglycerides and protein). In the cage tests, the bees were fed from the first day of life with sugar candy (control group) or candy with a 10% addition of one of the 6 pollen types. Hemolymph and fat body from various locations were collected from 1-, 7- and 14-day-old workers. Pollen produced by plant species such as hazel and pine increased glucose concentrations in the bee tissues, especially in the hemolymph. It can therefore be concluded that they are valuable sources of energy (in the form of simple carbohydrates) which are quickly used by bees. Pollen from plants blooming in the summer and autumn increased the concentrations of proteins, glycogen and triglycerides in the fat body, especially that from the third tergite. The accumulation of these compounds was associated with an increased the length and width of trophocytes as well as with enhanced metabolic activity, which was evidenced in the increasing diameter of oenocyte cell nuclei. It seems a balanced multi-pollen diet is more valuable for bees, but it is important to understand the effects of the particular pollen types in the context of a mono-diet. In the future, this will make it possible to produce mixtures that can ensure homeostasis in the apian body.

Pathogenicity of Multidrug-Resistant Salmonella typhimurium Isolated from Ducks.

Salmonella typhimurium (S. typhimurium) is one of the most common Salmonella serotypes in epidemiological surveys of poultry farms in recent years. It causes growth retardation, mortality, and significant economic losses. The extensive use of antibiotics has led to the emergence of multi-drug resistance (MDR) in Salmonella, which has become a significant global problem and long-term challenge. In this study, we investigated the prevalence and features of S. typhimurium strains in duck embryos and cloacal swabs from large-scale duck farms in Shandong, China, including drug resistance and virulence genes and the pathogenicity of an S. typhimurium strain by animal experiment. The results demonstrated that a total of 8 S. typhimurium strains were isolated from 13,621 samples. The drug resistance results showed that three of the eight S. typhimurium strains were MDR with the dominant resistance profile of CTX-DX-CTR-TE-AMX-AMP-CAZ. In particular, the virulence genes invA, hilA, pefA, rck, and sefA showed high positive rates. Based on the analysis of the biological characteristics of bacterial biofilm formation and mobility, a strain of S. typhimurium with the strongest biofilm formation ability, designated 22SD07, was selected for animal infection experiments with broiler ducklings. The results of animal experiments demonstrated that infection with 22SD07 reduced body weight and bursa index but increased heart and liver indexes compared to the control group. Histological examination revealed desquamation of the intestinal villous epithelium, the presence of large aggregates of lymphocytes, and a decrease in goblet cells following infection. Furthermore, the expression of IL-10 was significantly increased in the liver at 3 dpi, while TNF-α was significantly increased in the spleen at 7 dpi. The above results indicate that S. typhimurium may pose a potential threat to human health through the food chain. This helps us to understand the frequency and characteristics of S. typhimurium in duck farms and emphasizes the urgent need to strengthen and implement effective continuous monitoring to control its infection and transmission.

An Overview of Infectious and Non-Infectious Causes of Pregnancy Losses in Equine.

Equine breeding plays an essential role in the local economic development of many countries, and it has experienced rapid growth in China in recent years. However, the equine industry, particularly large-scale donkey farms, faces a significant challenge with pregnancy losses. Unfortunately, there is a lack of systematic research on abortion during equine breeding. Several causes, both infectious and non-infectious, of pregnancy losses have been documented in equines. The infectious causes are viruses, bacteria, parasites, and fungi. Non-infectious causes may include long transportation, ingestion of mycotoxins, hormonal disturbances, twinning, placentitis, umbilical length and torsion, etc. In current review, we discuss the transmission routes, diagnostic methods, and control measures for these infectious agents. Early detection of the cause and appropriate management are crucial in preventing pregnancy loss in equine practice. This review aims to provide a comprehensive understanding of the potential causes of abortion in equines, including infectious agents and non-infectious factors. It emphasizes the importance of continued research and effective control measures to address this significant challenge in the equine industry.

Online Monitoring of the Temperature and Relative Humidity of Recycled Bedding for Dairy Cows on Dairy Farms

In large-scale dairy farming, the use of high-temperature-fermented dairy manure bedding instead of rice husk-based bedding and other commercial types of bedding is widely favored. Strip-stacking aerobic fermentation is the main production method of dairy manure bedding, but it has problems including unstable fermentation and the secondary breeding of pathogens. In this work, a multi-probe, integrated, online monitoring system for temperature and relative humidity was used for fermentation process optimization. The effects of the temporal and spatial distribution of fermentation temperature and relative humidity on the nutrient content curve and the moisture and ash content of manure bedding materials were systematically studied. The effect of the fermentation process on the retention rate of effective bedding materials (cellulose, hemicellulose, and lignin) was analyzed. The experiments proved that high-quality bedding material can be obtained through reasonable stacking fermentation. The fabricated bedding material has a total dry base content consisting of cellulose, hemicellulose, and lignin of 78%, an ash content of 6%, and a nutrient content of 17%. The obtained bedding material was produced to increase the bed rest rate and continuously inhibit the bedding bacteria content, keeping it at a low level for 5 days. This study proves that temperature and humidity monitoring can guide the optimization of the strip-stacking fermentation process of dairy manure and that it can be applied to large-scale farms to improve fermentation parameters.

Neonicotinoid insecticides in a large-scale agricultural basin system-Use, emission, transportation, and their contributions to the ecological risks in the Pearl River Basin, China

Neonicotinoid pollution has increased rapidly and globally in recent years, posing significant risks to agricultural areas. Quantifying use and emission, transport and fate of these contaminants, and risks is critical for proper management of neonicotinoids in river basin. This study elucidates use and emissions of neonicotinoid pesticides in a typical large-scale agriculture basin of China, the Pearl River Basin, as well as the resulting agricultural non-point source pollution and related ecological risks using market surveys, data analysis, and the Soil and Water Assessment Tool. Neonicotinoid use in the basin was estimated at 1361 t in 2019, of which 83.1 % was used in agriculture. After application, approximately 99.1 t neonicotinoids were transported to the Pearl River, accounting for 7.2 % of the total applied. Estimated aquatic concentrations of neonicotinoids showed three seasonal peaks. Several distinct groups of neonicotinoid chemicals can be observed in the Pearl River, as estimated by the model. An estimated 3.9 % of the neonicotinoids used were transported to the South China Sea. Based on the present risk assessment result, several neonicotinoids posed risks to aquatic organism. Therefore, the use of alternative products and/or reduced use is deemed necessary. This study provides novel insights into the fate and ecological risks of neonicotinoid insecticides in large-scale watersheds, and underscores the need for greater efficiency of use and extensive environmental monitoring.

The disappearance of pollution havens under unified environmental regulation: evidence from China’s pig industry

ABSTRACT Since 2014, China has implemented a unified environmental regulation policy for the livestock industry. With unified environmental regulations across provinces, does the phenomenon of ‘pollution havens’ still exist? To address this question, this paper examines spatial variations among provinces and their spillover effects on the pig industry using data on environmental regulations and pig production panels. The results indicate that: (1) Environmental regulation policies are gradually converging across regions. (2) Under unified environmental regulation, the existence of ‘pollution havens’ in the pig industry is no longer evident. As national regulations become stronger, increasing local regulatory intensity will not affect the number of pig farms in neighboring areas nor lead to significant emigration of such farms. (3) In cases where there are inter-regional variations in environmental regulations, large-scale farmers may relocate to neighboring areas with less stringent regulations; however, under unified environmental regulation, neither small nor large-scale farmers will migrate.

Technical Efficiency and Allocative Efficiency of Beef Cattle Fattening in the Content of Digital Economy: An Empirical Study Based on Survey in China

This study applies data envelopment analysis (DEA) to gauge technical efficiency and allocative efficiency in China’s beef cattle-fattening industry using survey data. The Tobit model considers the salient determinants that drive these efficiencies. The results indicate that (1) large-scale farms exhibit robust TE and pure technical efficiencies (PTE), whereas scale efficiencies (SE) diverge significantly between large and medium-sized operations. The cost efficiency (CE) of smaller farms lags behind their larger counterparts, with the latter displaying greater revenue efficiencies (RE) and profit efficiency (PE). (2) The influence of identical factors on the efficiency of beef cattle fattening production can vary, sometimes antithetically, across different scales. Local policy interventions must be differentiated according to farm type and size. (3) The unique context of China’s national conditions and the status quo of livestock farming render the dual implementation of environmental regulations and technological subsidies less viable for Chinese beef cattle farms. These entities should prioritize production over technological innovation and advancement. Policymakers should adopt strategies such as targeted skill/technological training for farm managers at particular scales of operation. This could represent a critical trajectory to augment the efficiency of beef cattle production and increase beef yield in China.

Assessment of information dissemination channels for the adoption of integrated pest management among large-scale farmers in Uasin Gishu, Kenya

Assessment of information dissemination channels for the adoption of integrated pest management among large-scale farmers in Uasin Gishu, Kenya

Advanced nutrient monitoring: Cost-effective cerium ion detection with smart device integration

This research is critically important for large-scale poultry farming, where vigilant monitoring is necessary to assess nutrient levels in poultry feed. Detecting cerium in poultry feed through colorimetric techniques is crucial for evaluating nutrient intake, feed quality, animal health, and broader environmental impacts. This study significantly contributes to ongoing research and monitoring efforts, aiding in maintaining an optimal mineral balance and enhancing chicken quality and overall poultry performance. The study utilized Alizarin Red dye (AR), both individually and in combination with Eriochrome Black T (EBT), to identify the presence of cerium ions. Various experimental conditions such as pH, concentration, temperature, and specificity were thoroughly examined. The UV-Vis absorption spectra indicated that the average minimum detectable limit for cerium ions is approximately 5 ppm, with a detection range of 0.2–3 mM. Additionally, a cost-effective paper-based sensor and a portable colorimetric method for detecting cerium ions were innovatively designed. This paper-based sensor ensures precise detection at room temperature, demonstrating high sensitivity and selectivity. The detection system was integrated with smart devices, enabling the swift capture of Red, Green, and Blue (RGB) values for practical real-time applications. This integration allows for rapid on-site identification of cerium ions. The introduction of this affordable, accurate, and portable colorimetric method for monitoring cerium ions represents a promising advancement in developing accessible tools within this field.

Knowledge, Attitudes, and Practices of Antibiotic Use among Small-, Medium-, and Large-Scale Fish Farmers of the Stratum II of the Volta Lake of Ghana.

Antibiotic residue in food products and the resulting antibiotic-resistant bacteria represent a significant global public health threat. The misuse of antibiotics is a primary contributor to this issue. This study investigated the knowledge, attitudes, and practices (KAP) regarding antibiotic use among cage fish farmers on Ghana's Volta Lake. We conducted a cross-sectional survey with 91 cage fish farmers across three scales: small, medium, and large. A semi-structured questionnaire complemented by personal observations provided comprehensive data. We used several statistical methods for analysis: Pearson Chi-Square and Spearman correlation tests to examine relationships and trends among variables, logistic regression to analyze variable interactions, and Cronbach's alpha to check internal consistency. Additionally, Kendall's coefficient was used to rank challenges, utilizing STATA and SPSS for these calculations. The survey revealed that 58.55% of cage fish farmers earn an average of 10,000 USD annually, with 35.16% having over 16 years of experience. From the survey, all sampled populations admitted to antibiotic applications in their farming operation. Knowledge of antibiotic types was mainly influenced by peers (46.15%), with tetracycline being the most recognized and used. There was a significant reliance on the empirical use of antibiotics, with 52.75% of farmers using them based on personal experience and 40.66% without a prescription. When initial treatments failed, 41.76% of the farmers would change or combine drugs. Older farmers (over 51 years) and those with tertiary education demonstrated significantly better KAP scores regarding antibiotic use. Strong correlations were also found among knowledge, attitudes, and practices in antibiotic usage. The findings indicate a need for improved education on antibiotic use among fish farmers to reduce misuse and enhance awareness of the potential consequences. This study provides foundational data for designing interventions to address these issues in the context of cage fish farming on Volta Lake.

Material flow analysis of heavy metals in large-scale cattle farms and ecological risk assessment of cattle manure application to fields

This study bridges the knowledge gap pertaining to the pathways of heavy metal accumulation and migration within the industrial chain of large-scale cattle farms. Two such farms in Shaanxi serve as a basis for our exploration into Zn, Cu, Cr, Pb, As, and Cd dynamics. Employing material flow analysis complemented by predictive models, we evaluate the potential ecological risks of arable soil from heavy metal influx via manure application. Our findings indicate that Zn and Cu predominate the heavy metal export from these operations, composing up to 60.00%–95.67% of their total content. Predictive models based on 2021 data reveal a potential increase in Cd soil concentration by 0.08 mg/kg by 2035, insinuating a reduced safe usage period for cattle manure at less than 50 years. Conversely, projections from 2022 data point towards a gradual Cu rise in soil, reaching risk threshold levels after 126 years. These outcomes inform limitations in cattle manure utilisation strategies, underscoring Cu and Cd content as key barriers. The study underscores the criticality of continuous heavy metal surveillance within farm by products to ensure environmental protection and sustainable agricultural practices.

Metagenomic approach revealed the mobility and co-occurrence of antibiotic resistomes between non-intensive aquaculture environment and human

BackgroundAquaculture is an important food source worldwide. The extensive use of antibiotics in intensive large-scale farms has resulted in resistance development. Non-intensive aquaculture is another aquatic feeding model that is conducive to ecological protection and closely related to the natural environment. However, the transmission of resistomes in non-intensive aquaculture has not been well characterized. Moreover, the influence of aquaculture resistomes on human health needs to be further understood. Here, metagenomic approach was employed to identify the mobility of aquaculture resistomes and estimate the potential risks to human health.ResultsThe results demonstrated that antibiotic resistance genes (ARGs) were widely present in non-intensive aquaculture systems and the multidrug type was most abundant accounting for 34%. ARGs of non-intensive aquaculture environments were mainly shaped by microbial communities accounting for 51%. Seventy-seven genera and 36 mobile genetic elements (MGEs) were significantly associated with 23 ARG types (p < 0.05) according to network analysis. Six ARGs were defined as core ARGs (top 3% most abundant with occurrence frequency > 80%) which occupied 40% of ARG abundance in fish gut samples. Seventy-one ARG-carrying contigs were identified and 75% of them carried MGEs simultaneously. The qacEdelta1 and sul1 formed a stable combination and were detected simultaneously in aquaculture environments and humans. Additionally, 475 high-quality metagenomic-assembled genomes (MAGs) were recovered and 81 MAGs carried ARGs. The multidrug and bacitracin resistance genes were the most abundant ARG types carried by MAGs. Strikingly, Fusobacterium_A (opportunistic human pathogen) carrying ARGs and MGEs were identified in both the aquaculture system and human guts, which indicated the potential risks of ARG transfer.ConclusionsThe mobility and pathogenicity of aquaculture resistomes were explored by a metagenomic approach. Given the observed co-occurrence of resistomes between the aquaculture environment and human, more stringent regulation of resistomes in non-intensive aquaculture systems may be required.4-S8N7kaEyTj6WBvQ6hX9pVideo

The Types of Water Conflicts in an Irrigation System in Northern Mexico: Conflict as a Negative Link in Social Network Analysis

We used social network analysis (SNA) to identify the types of water-related conflicts between the users and members of the institutional arena of the Rio Mayo Irrigation District (RMID) within the ancestral territory of the Yoreme Mayo indigenous group in Sonora, northeastern Mexico. We combined ethnography with an analysis and visualization of bimodal networks that consisted of 118 users and their connections to the institutional arena’s 30 identified social actors who influence water management. Using a clustering algorithm, we identified four types of conflicts: (1) disputes between small- and large-scale farmers over (i) irrigation water and (ii) payments for water rights and land rental; (2) the struggle by large-scale farmers against the upper level of the water hierarchy, to obtain more water; (3) struggles by rural indigenous women against water providers, to conserve indigenous vernacular systems of managing water for domestic use; and (4) a “conflict” that turned out to be merely a structural remnant of the algorithm. We conclude that land- and water-grabbing in the RMID mainly affect indigenous small-scale farmers and that the combination of SNA and a clustering algorithm can identify the types of natural resource-related conflicts that might go undetected by other methodologies. However, SNA should in some cases be accompanied by a qualitative methodology.

Enhancing Wind Farm Efficiency Through Active Control of the Atmospheric Boundary Layer’s Vertical Entrainment of Momentum

In contemporary wind farm design, the primary focus has traditionally been on reducing wake interference to optimize energy capture from horizontal wind flows. However, with the scaling up of wind farms, their interaction with the Atmospheric Boundary Layer (ABL) evolves, making vertical entrainment the main mechanism for the exchange of momentum and energy. This study introduces a methodical approach to augment the efficiency of large-scale offshore wind farms by actively controlling this vertical entrainment of momentum within the ABL. The strategy involves the precise engineering of advection fluxes to alter wind flow dynamics, utilizing turbines as effective vortex generators, toward a process of ”regenerative wind farming.” This setup aims to create a vorticity and vertical flux system akin to those observed in highly unstable ABLs. Expanding upon previous studies that focused on single Vertical Axis Wind Turbines (VAWTs), our research explores the implementation of multi-rotor systems equipped with lift-generating wings. These systems are designed to exert forces perpendicular to the prevailing wind direction, thus creating trailing vortices and directing the flow orthogonally for improved vertical advection. This research is part of a comprehensive investigative framework that combines experiments and multifidelity simulations. The current study extends those findings to wind farm simulations, aiming to assess the impact of ABL control on a full wind farm scale. The first part of the work validates an established analytical wind farm performance model against real wind farm data for thirty-one wind farms in the North Sea and Baltic Sea. The results confirm the predicted trend of decreased performance with increased wind farm size and density. The model is used to calculate the performance of a wind farm for varying regimes of vertical entrainment due to the creation of large-scale circulatory systems. The results are compared against 3D vortex simulations of the full wind farm in ”regenerative wind farming” mode. Our results demonstrate a notable improvement in wind speeds at the turbine hub height and the potential to double the feasible density of wind farms without compromising efficiency compared to traditional setups. These findings suggest a promising pathway towards a more sustainable and profitable future in wind energy, achieved through the strategic manipulation of ABL momentum, regenerating the energy in the wind farm.

Optimizing Wind Farm Efficiency through Active Yaw Control: A Neural Network-Aided Game Theory Approach

This research investigates the potential of a game-theoretic-based Active Yaw Control (AYC) strategy to enhance power generation in wind farms. The proposed AYC strategy in this study replaces traditional look-up tables with a trained Artificial Neural Network (ANN) that determines the optimal yaw misalignment for turbines under time-varying atmospheric conditions. The study examines a hypothetical 3x2 rectangular arrangement of NREL 5-MW wind turbines. The FAST.Farm simulation tool, utilizing the dynamic wake meandering (DWM) model, is employed to assess both the power performance and structural load on the wind turbines. When tested with two different inflow directions and ambient turbulence (10%), the AYC strategy demonstrated a maximum increase in total power output of 2.6%, although it affected individual turbines differently. It also exhibits an increase in some structural loads, such as tower-top torque, while some components experience a slight reduction in load. The results underscore the effectiveness of the ANN-guided game-theoretic algorithm in improving wind farm power generation by mitigating the negative impact of wake interference, offering a scalable and efficient method for optimizing large-scale wind farm. However, it is essential to evaluate the overall impact of AYC on wind farm efficiency in terms of both Annual Energy Production (AEP) and structural loading under various atmospheric conditions.