Farms In Denmark Research Articles

Wind farm power optimization using system identification

The wake effect reduces the total power production of wind farms. This paper presents a method for wind farm power optimization through wake effect reduction. The proposed method optimizes the yaw angle offsets and de-rating settings of all turbines to maximize total power generation. The optimization approach is gradient-based, with gradients at each iteration obtained through system identification using field test data, eliminating the need for physical models. In system identification, test signal design, model estimation and model validation problems are solved in a systematic manner; in the gradient-based optimization, in order to achieve fast convergence, methods for initial value and initial step-size determination, variable step-size iteration and iteration termination are developed. The method is verified using the FLORIS wind farm model developed by National Renewable Energy Laboratory (NREL), USA. The studied wind farm consists of 80 wind turbines configured similarly to the Horns Rev I offshore wind farm in Denmark. The result of the developed optimization method is highly consistent with those obtained using FLORIS's built-in optimization tool.

A registry-based comparative analysis of antibiotic usage reporting for adult cattle on Danish dairy farms

BackgroundAntimicrobial resistance (AMR) is a significant global health concern, necessitating the monitoring of antimicrobial usage (AMU). However, there is a lack of consensus on the standardized collection and reporting of AMU data in the veterinary field. In Denmark, the Danish Cattle Database (DCDB) contains treatment information on animal level, which allows counting of number of treatments carried out, used daily doses (UDD). The Danish VetStat database (VetStat) contains information on veterinary medicinal prescriptions at farm level and uses fixed standard doses of each product to calculate number of daily treatments, animal daily doses (ADD). This study aimed to compare two different numerators, UDD and ADD, used to describe AMU on Danish cattle farms, and estimate their correlation.ResultsRoutinely collected registry data from conventional dairy farms in Denmark for 2019 were used, including a total of 2,197 conventional dairy farms. The data from VetStat and the DCDB were aggregated and analysed, and treatment frequencies (TF) were calculated for both UDD and ADD, adjusting for farm size. Spearman correlation analysis and Bland–Altman plots were employed to assess the relationship and agreement between TF for ADD and UDD, respectively.The results showed a high correlation between TF for ADD and UDD for most prescription groups, i.e., groups used to categorise antibiotics based on target organs. An exception is found for the Udder prescription group, where a systematic underreporting of UDD compared to ADD was observed. This discrepancy may be due to combination treatments, and potential missing or grouped registrations in the DCDB.ConclusionsOur UDD and ADD comparison yields valuable insights on farm-level AMU. We observe strong correlations between UDD and ADD, except for udder treatments, where some farms report only 1/3 UDD compared to ADD, indicating potential underreporting. Further investigations are needed to understand the factors contributing to these patterns and to ensure the accuracy and completeness of recorded information. Standardizing AMU data collection and reporting remains crucial to tackle the global challenge of AMR effectively.

290 Commercial farm evaluation of enzymatically processed soybean meal in lactating sows

Abstract Hyper prolific sows have a high nutritional demand during lactation to produce sufficient milk for their large litters. To meet those requirements, it is common practice to include increased levels of soybean meal (SBM) in lactation diets. Which, considering the amino acid profile of SBM is a good source of protein at a reasonable cost. However, SBM cannot be digested and absorbed very rapidly in the gastrointestinal tract due to the presence of anti-nutritional factors (ANF), like trypsin inhibitors. As most lactation diets are supplemented with synthetic amino acids the incorporation of slowly digestible protein sources causes an asynchrony in release of amino acids into the blood stream. Enzyme-treated soybean meal (ESBM) is a protein source in which ANF are removed and it has been found to be a fast digestible protein source (Bible et al., 2023). It is therefore expected that the replacement of a proportion of SBM by ESBM will result in improved productivity of lactating sows. To test this hypothesis, hyper prolific sows (n = 1,078; Danbred) were enrolled on a commercial farm in Denmark. Data were collected from January 2023 through June 2023. Sows were fed their normal lactation diet from January to March (CON). Then, sows were fed a diet containing ESBM. There was a one for one replacement rate of ESBM for SBM meal. The inclusion rate of ESBM was 3%. The replacement increased the total crude protein level of the diet by less than 0.3%. It should also be noted the ESBM was fed during the summer months, which was uncommonly hot for the area. Sows fed ESBM had 0.2 more pigs per litter born alive than CON sows (19.7 vs. 19.5 pigs, respectively). Sows fed ESBM also weaned 0.1 more pigs than CON sows (16.8 vs. 16.7 pigs, respectively). There was a 5% increase in ESBM sows serviced before d 7 compared with CON sows (82 vs. 77%, respectively). Farrowing rate increased by 1.5% when sows were fed ESBM (88.9 vs. 87.4%, respectively). When pigs per sow per year was calculated, there was an increase of 0.6 pigs per sow by feeding ESBM (37.1 vs. 36.5 pigs, respectively). This on-farm experiment resulted in a 3 to 1 return on investment by feeding ESBM. First indications were that the replacement of SBM with 3% of ESBM can increase sow productivity even in hyper prolific sows. However, more research is needed to further evaluate effects of feeding enzyme-treated soybean meal to sows to see if this increased nutritional support also can help to mitigate negative effects of lactation stress on sow lifetime productivity.

Self‐paced learning long short‐term memory based on intelligent optimization for robust wind power prediction

AbstractGiven the unpredictable and intermittent nature of wind energy, precise forecasting of wind power is crucial for ensuring the safe and stable operation of power systems. To reduce the influence of noise data on the robustness of wind power prediction, a wind power prediction method is proposed that leverages an enhanced multi‐objective sand cat swarm algorithm (MO‐SCSO) and a self‐paced long short‐term memory network (spLSTM). First, the actual wind power data is processed into time series as input and output. Then, the progressive advantage of self‐paced learning is used to effectively solve the instability caused by noisy data during long short‐term memory network (LSTM) training. Following this, the improved MO‐SCSO is employed to iteratively optimize the hyperparameters of spLSTM. Ultimately, a combined MO‐SCSO‐spLSTM model is constructed for wind power prediction. This model is validated with the data of onshore wind farms in Austria and offshore wind farms in Denmark. The experimental results show that compared with the traditional LSTM prediction method, the proposed method has better prediction accuracy and robustness. Specifically, in the onshore and offshore wind power prediction experiments, the proposed method reduces the minimum MAE by 5.44% and 4.96%, respectively, and reduces the MAE range by 4.45% and 17.21%, respectively, which could be conducive to the safe and stable operation of power system.

Improved marketing strategy of a hybrid renewable plant integrated with gravitational energy storage: Techno-economic analysis and multi-objective optimization

The intermittent nature of renewable energy sources, which could negatively impact the stability of the electricity grid and the economic viability of the technologies, has intensified concerns about their extensive contributions to the national energy systems' electricity supply. Energy storage systems have become increasingly relevant as a means for securing grids' stability with high shares of renewables. The purpose of this study is to investigate the potential of utility-scale gravitational energy storage as a ‘bidding strategy facilitator in the day-ahead market’ for renewable energy plants. With this ultimate goal, the size of the storage unit is not necessarily very large compared to the peak production capacity of the plant. This is in favor of the cost-effectiveness of the power plant due to today's unsupportive electricity pricing and market regulations for justifying large-scale energy storage systems. The gravitational energy storage system is assumed to accompany a PV farm in Denmark, just as a sample case study. The system is designed, sized, and planned for the optimal marketing strategy of the PV plant using rigorous techno-economic modeling and optimization techniques. According to preliminary findings, a 100 MWP PV plant with 5 MWh storage capacity can be built with a capital expenditure of $126.96 million, at a discounted payback period of 10.6 years, and reduced annual penalties of over 94.5 %.

Genetic parameters for early piglet weight, litter traits and number of functional teats in organic pigs.

Knowledge remains limited on genetic variation and genetic correlations for traits in sows and piglets that are reared in an organic or outdoor setting. Here, we estimated genetic variance components for individual piglet weight, litter weight, litter size traits, and number of functional teats in a pig population raised under outdoor organic conditions. Data were collected from the largest organic multiplier farm in Denmark. Individual piglet weight was recorded at birth and on day 10. Number of live and dead piglets were recorded at birth, day 4, and day 11. Mean and total litter weight were calculated based on the individual weight of living piglets at birth and on day 10. The estimated heritability was highest for the number of functional teats (0.49), mean weight of a litter at birth (0.33) and on day 10 (0.25). In contrast, heritability was lowest for litter size traits (0.04-0.08) and piglet weight (0.06-0.07). Maternal heritability was much higher for individual piglet weight than direct heritability. The results showed that selection for higher mean weight results in smaller litters. Also, selection for individual birth weight of piglets results in heavier piglets at 10days. In conclusion, this study confirmed that there is genetic variation in individual piglet weight, litter traits, and number of functional teats in organically and outdoor-reared pigs.

Reducing milking frequency from 3 to 2 times daily in early lactation: effects on milk production, health and body condition.

The objective of this experiment was to investigate the effect of reducing early lactation milking frequency on milk yield and persistency through lactation and early lactation fat mobilization, measured by body condition score (BCS) and BHB in milk. We hypothesized that milking cows twice per day in early lactation before milking them 3 times per day for the remaining lactation would cause less fat mobilization in early lactation, a lower peak milk yield but improved persistency throughout lactation compared with milking cows 3 times per day for the entire lactation. The experiment took place on 2 commercial dairy farms in Denmark. All cows calving in a period of nine months (n = 239) in their current first and later parities were randomly allocated at dry-off to 1 of 3 treatments based on expected calving date. The treatments were (1) cows milked 2 times per day for 1 week after calving, (2) cows milked 2 times per day for 4 weeks after calving and (3) cows milked 2 times per day for 7 weeks after calving. All cows were then milked 3 times per day for the remaining lactation. Milk yield peaked 3.3 and 3.6 d later and milk yield persistency improved with 18 and 19 g per day when cows were milked 2 times per day for 4 and 7 weeks, respectively, compared with milking 2 times per day for 1 week after calving. We found a significant highest milk BHB in treatment 2, but the underlying effect of milking cows 2 times per day for 4 weeks compared with 1 or 7 weeks was unclear. In conclusion, we did not confirm our hypothesis that milking cows 2 times per day compared to 3 times in early lactation would reduce fat mobilization and reduce peak yield. We did, however, find an improved milk yield persistency, which partially offset a numerical reduction in peak yield, and hence there was no significant effect of reducing early lactation milking frequency on total lactation (305 DIM) milk yield.

Data synchronization for gas emission measurements from dairy cattle: A matched filter approach

Methane emissions from enteric fermentation in dairy cows make a substantial contribution to the greenhouse gas problem. Sniffer approaches represent a popular low-cost, mobile technology for cow gas emission measurement in industrial installations owing to their providing reliable emission estimates. Despite its advantages, the sniffer approach often yields data inconsistencies during automated acquisition due to unsynchronized clocks between sniffers and associated automatic milking machines, leading to uncertainty in the linking of each animal’s data with methane emission records. Given the constantly growing demand for large-scale methane emission measurements for genetic studies, sniffer installations are expected to increase, making the need for an efficient solution to the data synchronization issue prescient. A novel approach for handling the synchronization problem was developed in this study based on matched filter theory. The approach was verified on gas emission data from multiple commercial dairy farms in Denmark. The results were analyzed and discussed in terms of accuracy and general characteristics of computational performance irrespective of a specific software implementation. The present findings support the conclusion that the presented matched filter-based approach is robust, applicable to the problem of cattle gas emission data synchronization, and convenient for automated data processing.

Animal welfare measured at mink farms in Europe

Although the welfare of farm mink has been debated for decades, the status at mink farms has not previously been reported. Likewise, little is known about the variation in housing conditions and animal responses between mink farms, although relevant for identifying key opportunities and challenges. We present for the first time comparable data on animal welfare at mink farms across the European continent, sampled by impartial assessors, trained in the standardised WelFur-Mink protocol including 22 indicators. The assessment was based on three visits – one in each annual production season – on 2104 farms in 23 European countries, evaluating a representative sample of 90–120 cage units per assessment during 2017–19. Based on the aggregated scores for the four Welfare Quality® principles 1. Good feeding, 2. Good housing, 3. Good health and 4. Appropriate behaviour, the farms reaching certification were categorised as ‘Unacceptable’ (none), ‘Acceptable’ (0.8%), ‘Good’ (71.7%) or ‘Best’ (27.5%) current practice. To our knowledge, WelFur is the first full-scale implementation of Welfare Quality®-based assessment protocols in an entire continent. Although most assessed farms ended in the second-best category, the variation in results between farms allows for ample improvement in the welfare of mink. In general, farms in Denmark together with farms in Poland, the Netherlands, Lithuania, Italy, Finland and Sweden appeared relatively close in the average score of the 12 criteria and represented more than 90% of 2104 farms. Particularly the farming situation under the principle Good housing fulfilled the WelFur goals, which we suggest reflects a high degree of standardisation of mink housing systems, aligned with the current legislation, and a lack of scientific studies of alternatives outperforming the current cage units with nest boxes. The lowest aggregated scores were for the principle Appropriate behaviour for which the criterion ‘Expression of social behaviours’ contributed with the lowest scores. This result reflects mainly variable management for the weaning procedures and the use of group housing during parts of the annual production year of mink. All the relatively low scoring criteria had a moderate to high variance between mink farms, indicating challenges displaying some variation. The farms that did well in each of the 22 indicators illustrate what is possible on commercial farms. This situation paves the way for using high-scoring farms as inspiration and incentive for improving the mink welfare on low-scoring farms.

The COVID-19 pandemic from a One Health perspective

The "One Health" approach is essential to better understand and manage a pandemic of animal origin. Sensitive geopolitical considerations seem to hamper the investigations into the origin of the pandemic, but everything points to the Rhinolophus bat as the starting point of this devastating pandemic. Through a phenomenon of reverse zoonosis, several hundred cases of contamination of animals by SARS-CoV-2 have been identified worldwide, involving about twenty species of mammals. The virus has also passed from animals to humans in the case of infected mink farms in Denmark or through contact with hamsters in Hong Kong. For the development of vaccines and treatments and to help detect COVID-19 in train stations or airports, the animal has confirmed its role as a valuable auxiliary resource for humans in the fight against the pandemic.

Heterogeneity in willingness to pay for the location of offshore wind power development: An application of the willingness to pay space model

Preferences for developing 3600 MW offshore wind farms in Denmark are estimated based on data from a choice experiment. The variation in willingness to pay for the location of offshore wind power development at 8, 12, 18, or 50 km from shore is analysed as a function of gender, age, education, income, wind turbine viewshed, and beach visits. With a willingness to pay space mixlogit model, we find that willingness to pay varies significantly as a function of the age, income level, viewshed to offshore wind farms, and beach visit frequency of the respondents.

Maternal Dietary Nitrate Supplementation Lowers Incidence of Stillbirth in Hyper Prolific Sows under Commercial Circumstances.

Simple SummaryOver recent decades, the number of piglets and, therefore, the number of stillborn piglets per litter have been increasing. Blood and oxygen supply are crucial for piglets to survive the birth process. Blood flow might be increased through vasodilation by dietary nitrate supplementation, which is known in sports nutrition to increase endurance. The current study evaluated the effects of nitrate supplementation to sows on the incidence of stillbirth at a commercial farm. In total, 120 sows received either a control diet or a diet containing 0.1% of calcium nitrate from approximately 5 days until 4 days after farrowing. The number of piglets born alive, stillborn, or that died from birth to weaning were recorded. Piglets were weighed at birth, after cross-fostering, 24 h after cross-fostering, at 3 days of age, and at weaning. Placentas were collected after expulsion and were visually scored on redness. No effect of nitrate supplementation to the sow was found on placental redness, piglet weights, and growth or incidence of death after being born. Dietary nitrate supplementation decreased the stillbirth percentage from 9.9 to 7.4%, making it a potential approach to decrease stillbirth.The objective of the current experiment was to investigate whether or not maternal dietary nitrate supplementation, a nitric oxide (NO) precursor, could reduce piglet losses under commercial circumstances. In the current experiment, 120 hyper prolific gilts and sows (Landrace x Yorkshire: Danbred) on a commercial farm in Denmark received either a control lactation diet or a lactation diet containing 0.1% of calcium nitrate (containing 63.1% of nitrate) from approximately 5 days pre-farrowing until day 4 of lactation. The number of piglets born total, alive, and stillborn, as well as birth weights, weights after cross-fostering (approximately 1 day of age), 24 h after cross-fostering, day 3 of age, and at weaning was recorded. Placentas of sows were collected after expulsion and scored on redness. No effect of nitrate supplementation was found on piglet weight, piglet growth, placental redness score, and pre-weaning mortality during lactation. Maternal dietary nitrate supplementation decreased stillbirth percentage with 2.5% (9.9 vs. 7.4%; p = 0.05). It can be concluded that maternal dietary nitrate supplementation shows the potential to decrease the incidence of stillbirth in hyper prolific sows.

Differences between the productivities of organic and conventional dairy farms in Denmark

Abstract The study compares the productivity change over time of organic and conventional dairy farms in Denmark between 2011 and 2018 using data envelopment analysis, and aims to identify which technology is superior. Productivity changes and the differences between organic and conventional frontiers in each year for observations from each group are calculated for each technology separately using the Malmquist Productivity Index and its components. Then, a recently developed permutation test is used to analyse the statistical significance of the results. The analysis identifies volatility in the (economic) production possibilities, which is likely related to changes in milk prices caused by geopolitical events, which the conventional technology seems to be more susceptible to. Furthermore, the organic technology on average became superior for conventional farms in 2015. Farm level analysis identifies characteristics of the input–output mix of the farms, indicating whether a farm could benefit from conversion to the other technology.

Avian influenza overview August – December 2020

Between 15 August and 7 December 2020, 561highly pathogenic avian influenza (HPAI) virus detections were reported in 15EU/EEA countries and UK in wild birds, poultry andcaptive birds, with Germany (n=370), Denmark (n=65), the Netherlands (n=57) being the most affected countries.The majority of the detections have been reported in wild birds(n=510), primarily in barnacle goose, greylag goose, andEurasian wigeon. Raptors have also been detected infected, particularly common buzzard. The majority of the birds had been found dead or moribund,however, there are also reports ofHPAI virus infection in apparently healthy ducks or geese.A total of 43 HPAI outbreaks were notified in poultry;with signs of avian influenza infection being observed in at least 33 outbreaks;the most likely source of infection was indirect contact with wild birds. Three HPAI virus subtypes, A(H5N8) (n=518), A(H5N5) (n=17) and A(H5N1) (n=6),and four different genotypes were identified, suggesting the occurrence of multiple virus introductions into Europe.The reassortant A(H5N1) virus identified in EU/EEA countries has acquired gene segments from low pathogenic viruses and is not related to A(H5N1) viruses of e.g. clade 2.3.2.1c causing human infections outside of Europe. As the autumn migration of wild waterbirds to their wintering areasin Europe continues, and given the expected local movements of these birds, there is still a high risk of introduction andfurther spread ofHPAI A(H5) viruses within Europe.The risk of virus spread from wild birds to poultry is high and Member States should enforce in ‘high risk areas’ of their territories the measures provided for in Commission Implementing Decision (EU) 2018/1136.Detection of outbreaks in breeder farms in Denmark, the Netherlands and United Kingdom, highlight also the risk of introduction via contaminated materials (bedding/straw) and equipment.Maintaining high and sustainable surveillance and biosecurityparticularly in high‐risk areas is of utmost importance. Two human cases due to zoonoticA(H5N1) and A(H9N2) avian influenza virus infection were reportedduring the reporting period. The risk for the general population as well as travel‐related imported human cases are assessed as very low.

New measurement technique for ground acoustic impedance in wind farm

Ground acoustic impedance is important in the prediction of sound propagation. In this paper, a new measurement technique is developed based on the Image Source method. Two set-ups are used. Set-up 1 consists of a speaker at a height of 0.5 m and two microphones at heights of 0.2 m (or 0.3 m) and 0.5 m with a separation distance of 1.75 m between the speaker and microphones. Set-up 2 has a double separation distance and almost double heights of 0.5 m and 1 m. The impedance measurements were performed at grass-ground and soft soil-ground after harvest in two different wind farms in Denmark. The findings are: (1) The Nordtest method works in Set-up 1, but gives inconsistent results in Set-up 2. (2) The new method gives consistent results in both set-ups. (3) The flow resistivity obtained with an impedance model can only be used with that specific impedance model, and it becomes inaccurate when used with other impedance models. (4) The determination procedure of flow resistivity is suggested to work with any impedance model. (5) A relation between the flow resistivity obtained with the one-parameter model of Delany and Bazley and that obtained with the four-parameter model of Attenborough is derived.

Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.

Competitiveness of Polish dairy farms in the European Union

This article analyses the competitiveness of dairy farms in Poland in relation to selected EU countries. The competitive advantage of dairy farms was evaluated and compared based on remuneration for family labour. Two variants of the above indicator were calculated: (1) Remuneration for family labour (FL1) as the relationship between farm net income and the farmer’s unpaid labour input, and (2) Remuneration for family labour (FL2) as the relationship between farm net income minus the opportunity costs of own land and capital to the farmer’s unpaid labour input. The calculations were performed based on EU FADN (European Union Farm Accountancy Data Network) data for an average dairy farm in 2005, 2010 and 2016. The study revealed the highest average remuneration for family labour (FL1) in Irish and German dairy farms. The value of the second indicator (FL2) was also highest in Germany, followed by France. The analysis produced interesting results regarding dairy farms in Denmark and the Netherlands which were characterised by the highest scale of production in the evaluated period (high net value added), but very low farm incomes and remuneration for family labour. The study revealed that Polish dairy farms were characterised by average competitiveness relative.

An Improved Power Control Approach for Wind Turbine Fatigue Balancing in an Offshore Wind Farm

Increasing maintenance costs will hinder the expansion of the wind power industry in the coming decades. Training personnel, field maintenance, and frequent boat or helicopter visits to wind turbines (WTs) is becoming a large cost. One reason for this cost is the routine turbine inspection repair and other stochastic maintenance necessitated by increasingly unbalanced figure loads and unequal turbine fatigue distribution in large-scale offshore wind farms (OWFs). In order to solve the problems of unbalanced fatigue loads and unequal turbine fatigue distribution, thereby cutting the maintenance cost, this study analyzes the disadvantages of conventional turbine fatigue definitions. We propose an improved fatigue definition that simultaneously considers the mean wind speed, wind wake turbulence, and electric power generation. Further, based on timed automata theory, a power dispatch approach is proposed to balance the fatigue loads on turbines in a wind farm. A control topology is constructed to describe the logical states of the wind farm main controller (WFMC) in an offshore wind farm. With this novel power control approach, the WFMC can re-dispatch the reference power to the wind turbines according to their cumulative fatigue value and the real wind conditions around the individual turbines in every power dispatch time interval. A workflow is also designed for the control approach implementation. Finally, to validate this proposed approach, wind data from the Horns Rev offshore wind farm in Denmark are used for a numerical simulation. All the simulation results with 3D and 2D figures illustrate that this approach is feasible to balance the loads on an offshore wind farm. Some significant implications are that this novel approach can cut the maintenance cost and also prolong the service life of OWFs.

Integrated genome-wide investigations of the housefly, a global vector of diseases reveal unique dispersal patterns and bacterial communities across farms

BackgroundHouseflies (Musca domestica L.) live in intimate association with numerous microorganisms and is a vector of human pathogens. In temperate areas, houseflies will overwinter in environments constructed by humans and recolonize surrounding areas in early summer. However, the dispersal patterns and associated bacteria across season and location are unclear. We used genotyping-by-sequencing (GBS) for the simultaneous identification and genotyping of thousands of Single Nucleotide Polymorphisms (SNPs) to establish dispersal patterns of houseflies across farms. Secondly, we used 16S rRNA gene amplicon sequencing to establish the variation and association between bacterial communities and the housefly across farms.ResultsUsing GBS we identified 18,000 SNPs across 400 individuals sampled within and between 11 dairy farms in Denmark. There was evidence for sub-structuring of Danish housefly populations and with genetic structure that differed across season and sex. Further, there was a strong isolation by distance (IBD) effect, but with large variation suggesting that other hidden geographic barriers are important. Large individual variations were observed in the community structure of the microbiome and it was found to be dependent on location, sex, and collection time. Furthermore, the relative prevalence of putative pathogens was highly dependent on location and collection time.ConclusionWe were able to identify SNPs for the determination of the spatiotemporal housefly genetic structure, and to establish the variation and association between bacterial communities and the housefly across farms using novel next-generation sequencing (NGS) techniques. These results are important for disease prevention given the fine-scale population structure and IBD for the housefly, and that individual houseflies carry location specific bacteria including putative pathogens.

Bidding strategy for trading wind energy and purchasing reserve of wind power producer – A DRL based approach

Wind power producers (WPP) are punished when take part in the short-term electricity market due to the inaccuracy of wind power prediction. The profit loss can be partially offset by strategic reserve purchasing. Due to the uncertainty of real-time wind power production, the reserve capacity price and the highly dynamic price regulation, it is difficult to determine the quantity of reserve to purchase, which might have a great impact on the profit of WPP. This paper investigates the possible influence on the revenue of WPP if they take part in both the energy and reserve market. This problem is first formulated as a Markov decision process (MDP). After that, the asynchronous advantage actor-critic (A3C) method is used to take care of this problem. Several agents are applied to explore the action space simultaneously. Neural networks are applied to fit the policy function and value function, which are trained against each other to learn the optimal dynamic bidding strategy from historical data by constantly trial and error. Simulation results of a wind farm in Denmark validate that the profit loss of the WPP can be significantly reduced when the A3C algorithm is used for bidding strategy formulation when WPP participate in both the energy and reserve market.