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Methodology of development of intellectual energy efficient system of control of temperature-humidity regime in industrial heat
Methods of improving the quality of regulation of technological parameters by combining various intelligent control algorithms in one automation system, which helps to reduce energy costs by 10-13%, are analyzed. It has been established that heating and ventilation systems have the highest energy consumption for indoor buildings (on average, more than 4,000 m3 of natural gas and almost 1,000 kWh of electricity are consumed per day for heating and ventilation in an industrial greenhouse. Correlation analysis of links between external disturbances and energy costs that ensure compliance with the technology of plant production, confirmed the hypothesis of conditions of uncertainty in the operation of industrial greenhouses are formed by random disturbances, incomplete information about the biological component, with linear correlation coefficients not exceeding r<0.35. both for forecasting energy costs and for the formation of energy efficient management strategies. Based on the use of fuzzy logic methods and genetic algorithm, models for finding and using optimal parameters of PI controller settings adapted to changes in the operating conditions of the automation system have been developed and studied. This provides better regulation in conditions of uncertainty, the time of regulation, over-regulation is reduced by two to three times. To create an energy-efficient microclimate management system in industrial greenhouses, operating in conditions of uncertainty, a neural network model for predicting the energy consumption of natural gas and electricity has been developed. The input parameters of the neural network forecasting model are: the value of external and internal air temperatures of the greenhouse, the value of relative humidity, the solar radiation absorbed by the greenhouse and the level of carbon dioxide in the greenhouse. The outputs of the forecasting model are the values of natural gas and electricity costs. The structural and functional scheme of the temperature and humidity control automation system in industrial greenhouses has been improved by combining intelligent algorithms for stabilizing the operation of technological equipment at the lower management level and optimizing energy costs by forecasting them at the upper level. The introduction of such a system saves up to 13% on natural gas for heating and up to 10% on electricity.
Determination of the Impact of Extruded Soybean Press Cake on Rearing and Health Indices of Piglets
The study was conducted to evaluate the alternative to imported soybean meal—extruded soybean press cake—in feeding weaning pigs. The experiment was carried out with 20 35-day-old weaned pigs weighing about 8.8 kg, divided into 2 groups (10 pigs in each) differing in the main protein source: group I—control, solvent-extraction soybean meal, group II— extruded soybean press cake. The feed mixtures were iso-protein and iso-energetic. After 35 days of feeding, the pigs were slaughtered. The samples of blood, intestinal tissue and digesta, meat, and back fat were collected for analyses. Replacement of soybean meal with extruded soybean press cake in the weaners’ diet had no statistically significant effect on growth performance and feed utilization. Histomorphometry analysis of the intestines did not indicate any harmful changes. The soybean press cake did not affect the sum of volatile fatty acids in the large intestine, but the ammonia concentration was lower in the distal colon (p ≤ 0.05). It was found that the extruded soybean press cake in the feed significantly affected the fatty acid profile (p ≤ 0.05) of meat and back fat, increasing the amount of PUFAs; however, no negative impact on the durability of meat and back fat during storage was noted. In conclusion, the study confirmed the possibility of completely replacing solvent-extraction soybean meal with extruded soybean press cake in the feeding of weaned pigs.