Designing a Biogas Plant for an Educational and Scientific Livestock Complex

To design biogas plants, it is necessary to have accurate data about the properties and biogas productivity of the available substrates. Reference data should not be used because the performance of the same substrate can vary significantly. In this research,chicken, horse, sheep and rabbit manure from one of the farms inthe Belgorod region of Russia were analyzed, and the parameters of a biogas station for the processing of this raw material were calculated.The biogas yield of the substrates was determined using the Hohenheim Biogas Yield Test. It was found that the specific biogas yield from the droppings of broilers, laying hens, rabbits, sheep, and horses, and from corn silage were, respectively, 456, 363, 390, 189, 116 and 618 ml/g оDM. The methane content in the biogas was 58.00, 58.50, 57.00, 62.00, 65.00 and 53.60%, respectively. In most cases, the obtained results differed significantly from the data presented in publications of other researchers and reference books.The biogas plant parameter calculations were made according to generally accepted equations, taking into account the characteristics of the studied substrates. Based on the results, it can be concluded that to dispose of the animal excrement of this farm, it is necessary to build a biogas plant with a bioreactor of volume 102.2 m3 and an engine with a power of 12 to 31 kW. The planned output of electric and thermal energy would be 246.19 and 410.27 kWh/day, respectively. Keywords: Hohenheim Biogas Yield Test, rabbit manure, horse dung, sheep manure, chicken droppings, biogas yield of substrates

Adjustment of the PID Gains Vector Due to Parametric Variations in the Plant Model in Terms of Internal Product

The tuning of the gains of a controller with proportional-integral-derivative (PID) actions has been prevalent in the industry. The adjustment of these gains in PID controllers is often determined by classical methods, such as Ziegler-Nichols, and trial and error. However, these methods fail to deliver satisfactory performance and often do not meet specific project demands because of the inherent complexity of industrial processes, such as plant parameter variations. To solve the tuning problem in highly complex industrial processes, a controller adjustment method based on the internal product of PID terms is proposed, and a propagation matrix (PM) is generated by the numerator coefficients of the plant transfer function (TF). In the proposed method, each term of the PID controller is influenced by each of the numerator and the denominator coefficients. Mathematical models of practical plants, such as unloading and resumption of bulk solids by car dumpers and bucket wheel resumption, were employed to evaluate the proposed method. The obtained results demonstrated an assertive improvement in the adjustment gains from PID actions, thereby validating it as a promising alternative to conventional methods.

Design of Sliding Mode Observer Based Controller of Single-Phase Induction Motor

Single-phase induction motors are simple in construction, cheap in cost, reliable and easy to repair and maintain. Many controllers were designed to control the speed of a single-phase induction motor, but they are sensitive to plant parameter variations and disturbances. Speed control with very less transient response requires non-linear and robust control methods. Sliding mode control is one of the robust control techniques which is insensitive to disturbances. Here we propose a higher order sliding mode (SM) observer-based controller for a single-phase induction motor. The applied control depends on the dynamic model of the induction motor. The controller is structured by applying a blend of input linearization strategy and higher order sliding mode calculation with consistent estimation of rotor speed and stator currents, which limits the vulnerabilities continuously and lessen the chattering phenomenon in the control effort exertion utilizing a super twisting algorithm.

Load Frequency Control Optimization using PSO Based Integral Controller

This paper presents Automatic Generation Control (AGC) of a power system using integral controller. In the present day power systems, it has become absolutely essential to maintain the quality of the power generated indicating the need of a robust system that can handle parameter uncertainties neglecting disturbances. Although,extensive research has been done in thisarea, design of an efficient and robust system still remains one of the important issues that need to be addressed. Hence in this paperan integral controller has been designed for a singlearea thermal power system without reheat turbine. The optimum controller gain is obtained by Particle Swarm Optimization (PSO) based on Integral of Absolute Error (IAE) and Integral of Square Error (ISE) criterion. The second part of the investigation includes robustness testing of the designed controller against different load conditions and plant parameter variations. The results obtained are compared to those obtained by other control methodologies presented in the recent literature. The results of the simulation validate the superiority of the approach in terms of improvement in the transient response and robustness to plant parameter variations.

Automatic Generation Control using Genetic Algorithm Based PID Controller

In this paper Automatic Generation Control (AGC) of a single-area thermal power plant without reheat turbine is introduced using a Proportional Integral Derivative (PID) controller. The gains of the controller are optimized using Genetic Algorithm (GA). The problem of tuning the PID controller is formulated as optimization problem with constraints on proportional, derivative and integral gains. The proposed algorithm uses Darwin’s law of natural selection and survival of the fittest to reach the optimal solution. The simulation results confirm the system’s ability to retain frequency while handling sudden load disturbances. The second part of the investigation includes robustness testing of the system against plant parameter variations. The results are verified and the system performance is found to be robust against parameter uncertainties

PENGARUH MEDIA TANAM DAN NUTRISI TERHADAP PERTUMBUHAN DAN HASIL TANAMAN SELADA KEPALA RENYAH (Lactuca sativa var. capitata) SECARA HIDROPONIK

Study aims to determine the effect of planting media and nutrients on the growth and yield of crispy lettuce (Lactuca sativa var. Capitata) hydroponically and to determine the best planting media and types of nutrients on the growth and yield of crispy lettuce (Lactuca sativa) var. capitata) hydroponically. This research uses factorial experimental design in CRD. The first factor is 3 planting media (coffee husk charcoal, rice husk charcoal and rock wool). The second factor is 3 nutrients (organic, AB mix and organic + inorganic). There are 9 combinations of planting media and nutrition for the growth of crispy lettuce head planting. Each combination is randomized before being tested, to determine the order of testing. Each combination is done 3 times. The results of observations and average calculation of plant parameter data at the 4th week after transplanting showed the result that there was no effect of the planting media and nutrients on the growth and yield of lettuce. Likewise with the results of analysis of variance (ANOVA) showed that there was no real effect on plant parameters.