Indian agriculture is undergoing a gradual shift from dependence on human power and draft animal power (DAP) to mechanical power because maintenance of DAP and manual labor is becoming increasingly costly coupled with scarce availability of fodder and feed to animal. Hence mechanical power has become more economical and indispensable to meet targets of timeliness and efficient utilization of natural resources and input use. Intensive cultivation also requires mechanization. Use of high capacity and energy efficient farm implements are more important in changing climate scenario. This includes limited sowing (window) period available due to delayed monsoon or long dry spells between rainfall events to complete farm operations. It is also relevant after prolonged water logging or for limited period suitable for various intercultural practices such as weeding or harvesting. Farmpower availability from human and animal power sources has remained same or even reduced during past 20 years (0.24 Kw/ha in 1951 to 0.20 Kw/ha in 2009). Farmpower from tractors mechanical and electrical sources put together increased 20 fold in the same period (0.04 Kw/ha in 1950 to 0.93 Kw/ha in 2009) (Srinivasrao etal 2013).
The factors for strengthening of farm mechanization in the country may be numerous. Agricultural machinery and equipment industry comprises of a large number of segments even in the organized sector. Tractor industry is one of the most capital intensive industries in agricultural machinery with more than a half dozen major players in Punjabviz. Standard, Swaraj, Sonalika and Preet Tractors. More than 100 (95%) combine manufacturing industries of India are in Punjab. The other major parts of the industry are reapers, straw reapers, threshers, sprayers, sowing, planting and transplanting machines, rotavators, laser land levelers, disc harrows, cultivators, ploughs, horticultural equipments, diesel engines, irrigation pumps, chaff cutters and hand tools. PAU, Ludhiana has also established a large number of entrepreneurs and agro industries through product development and trainings, catering to whole of the country. Punjab State Agricultural Implements Manufacturers Association (PSAIMA) at state level and Tractors and Agricultural Machinery Manufacturers Association (TAMMA) of India were launched in 1989 and 2010 respectively.
Although the agricultural mechanization program in Riau Province has been critically accelerated in current years, its level of overall mechanization development is still relatively low. The development of farmmachinery, particularly in Kampar Region, always faces with some inherent drawbacks such as fragmented lands, poor buying capacity of farmers, poor technical knowledge of farmers about machines, limited access to the financial institution (bank), and inadequate business knowledge of machinery management. In the development process of mechanization, a large number of farm machines (power) are required to be accessed and used by farmers to mechanize their farm operations. The limited availability of farmpower also becomes a constraint factor for the growth of farm tools and implements . Therefore, it is essential to know the development of farm machines and how to use them for achieving rice production goals. This paper attempts to highlight the farmmachinery development and utilization system policies for small-scale rice farming in the Kampar Region, Indonesia.
The rapid depletion of conventional sources for power generation necessitates the need of renewable energy power plants. Renewable sources primarily wind and solar are available free of cost and counts for cleaner source of energy thereby reducing environmental concern. The potential of wind energy needs to be harnessed effectively for optimum power generation. Present research aims at comparison of wind power performance characteristics utilizing squirrel cage induction generator (SCIG) and doubly fed induction generator (DFIG) focusing on load flow analysis, active power at various wind speeds and reactive power analysis. The simulation and analysis pinpoints the suitable generator at various wind speeds to consummate for selection in a distinct wind farm. The evaluation consisted identical operating conditions and control schemes.
Controlled traffic farming (CTF) is a mechanization system in which tramlines and seed beds are distinctly and permanently separated to optimize conditions for trafficability with farmmachinery as well as soil conditions for crop growth. Recent studies (e.g., Antille et al., 2015a) have shown that CTF systems have the potential to either reduce nitrogen (N) fertilizer inputs without compromising crop yield or increase crop yield for the given fertilizer input. This is supported by studies showing enhanced structural conditions in soils established under CTF (e.g., McHugh et al., 2009) and by enhanced nutrient uptake in the absence of traffic compaction (e.g., Lipiec and Stępniewski, 1995). However, no detailed studies have been reported on the effects of traffic compaction on the actual yield-to-fertilizer response relationships from which optimum economic N application rates could be derived, particularly for subtropical edaphoclimatic conditions. Therefore, work was undertaken to: (1) Determine the effect of traffic compaction on the yield-to-nitrogen response of winter wheat crops, (2) Determine the effect of such compaction on fertilizer use efficiency and quantify differences in fertilizer-use efficiency for controlled and non-controlled traffic systems, N fertilizer formulation, and derive the most economic fertilizer application rate, and (3) Determine the changes in the crop’s gross margins under both traffic systems as a result of changes in the price of nitrogen fertilizers. This work also seeks to demonstrate that in terms of nitrogen use efficiency little can be gained from the use of enhanced fertilizer formulations (EEF) if soil conditions are such that crop agronomic performance cannot be optimized. This has practical implications for nitrogen management because much effort is being spent on optimizing the use of EEF, but no consideration has been given to the detrimental effects of traffic compaction on fertilizer use efficiency, with some exceptions (e.g., Tullberg et al., submitted).
Abstract: This project proposes a compensation strategy based on a particular CUPS device, the Unified Power Quality Compensator (UPQC). The control strategy of the Unified Power Quality Compensator device is to regulate the voltage in the Wind Farm, mitigate voltage fluctuations at grid side, manages active and reactive power in the series and shunt converters of the Unified Power Quality Compensator, and the exchange of power between converters through UPQC DC-Link. Simulations results show the effectiveness of the proposed compensation strategy for the enhancement of Power Quality and Wind Farm stability. In this project, a new compensation strategy implemented using an UPQC type compensator was presented, to connect SCIG based wind farms to weak distribution power grid. The simulation results show a good performance in the rejection of power fluctuation due to “tower shadow effect” and the regulation of voltage due to a sudden load connection. So, the effectiveness of the proposed compensation approach is demonstrated in the study case.
The selection of the power unit and the operating conditions (yield, moisture, soil type, terrain etc.) will also affect fuel use. This means that for similar tasks there can be a wide variation in fuel cost. For this reason, it is fair if the renter supplies or purchases fuel separately from the rental rate. A fuel cost estimate has been included based upon typical use and should be used only as a ball park indication of what fuel cost might be. Work Rate: Instantaneous work rates are easily calculated based upon the implement’s working width and its travel speed. However, in all field operations there is a difference between the instantaneous work rate and the average work rate accomplished over several hours. This is referred to as field efficiency. Field efficiency can vary greatly depending upon work conditions (field size and topography, soil or crop conditions, suitability of the equipment for the task and availability of support equipment). For this guide, a field efficiency of 80 per cent has been chosen and applied to all tasks.
In order to design the power factor corrector there are some few specifications which are required such as output voltage, output current, output power and also the main factor which is the efficiency.The power factor of an AC electrical power system is defined as the ratio of the real power flowing to the load to the apparent power in the circuit and is a dimentionless number between - 1 and 1.The devices for correction of the power factor may be at a central substation, spread out over a distribution system, or built into power- consuming equipment.In an electric power system, a load with a low power factor draws more current than a load with a high power factor for the same amount of useful power transferred.Power factor correction may be applied by an electric power transmission .In a proposed circuit of 200 WATTS power both the experimental and simulation results are carried out. Here in the AC input of the block diagram wind turbine in used as the input. Since it is an AC source wind turbine is directly connected to the push pull converter.
Each wind turbine in the farm has its own full operational envelope controller  that ensures the wind turbine follows its required operating strategy and remains in a safe operating condition through regulating rotor speed, torque and some loads. Since the wind farm controller requires each turbine to adjust its power output on request, the full envelope controller is modified by addition of a Power Adjusting Controller (PAC) . The PAC causes the turbine to adjust its generated power by a demanded amount relative to that dictated by the wind speed. As the PAC is essentially a feed forward controller, jacketing the full envelope controller, it does not compromise the operation of the full envelope controller, hence redesigning or retuning of the existing full envelope controller is not necessary. Furthermore, the PAC contains safeguards to prevent the turbine being driven into unsafe operating regions. The PAC is sufficiently fast acting to provide the turbine with a synthetic inertia response .
This paper takes a DFIG wind farm as an example, proposing a power allocation strategy based on nonlinear op- timization control algorithm, which aims at minimizing power loss in wind farm and power deviation between dispatching command and actual output. Specific objective function and constraint conditions are also given in this paper, and then simulation is conducted in a wind farm with 10 DFIGs as an example compared with tradi- tional control strategy results .
Each wind turbine in the farm has its own full operational envelope controller  that ensures the wind turbine follows its required operating strategy and remains in a safe operating condition through regulating rotor speed, torque and some loads. Since the wind farm controller requires each turbine to adjust its power output on request, the full envelope controller is modified by addition of a Power Adjusting Controller (PAC) . The summary of the PAC is included in Appendix A of this paper. As described in the appendix, the PAC causes the turbine to adjust its generated power by a demanded amount relative to that dictated by the wind speed. As the PAC is essentially a feed-forward controller, jacketing the full envelope controller, it does not compromise the operation of the full envelope controller. Hence, redesigning or retuning of the existing full envelope controller is not necessary. Furthermore, the PAC is sufficiently fast acting to provide the turbine with a synthetic inertia response [9, 10], but that usage of the PAC is not discussed in this paper.
But, in spite of ‘problem’ pervasiveness, or, perhaps, because of it, and to the best of my knowledge, there is not any problem theory exact enough to be used in mathematics. So we will define one from first principles. The result is presented in section “Problem Theory”. This theory uses just eight concepts: problem, freedom, condition, resolution, routine, trial, analogy, and solution. The theory will be evaluated later, so for now the reader should focus in getting an accurate view of each of the eight concepts. It is important to be aware of the distinction between ‘solution’ and ‘resolution’ that this theory makes: ‘solution’ is anything that satisfies the condition of the problem, while ‘resolution’ is the process of searching for solutions to the problem. The next section, “Problem Resolving”, is the core of the paper, but for anyone familiar with computing theory the bulk of the work was already done while presenting the problem theory. The aim of this section is to translate the eight concepts of the theory to mathematics. The first conclusion is that open expressions, also known as functions, are needed to translate problems to mathematics. And the last conclusion is that the whole power of Church’s lambda calculus, that is, a Turing complete or a computationally universal device, is needed to execute any possible resolution. This last conclusion, that should not be surprising for computing theorists, should instead serve to demonstrate the value of the problem theory presented in the previous section.
The study “Tractor Monitor 2011 – Sales excellence in farmmachinery sales using the example of tractors” faces this challenge and illustrates specific levers for optimization. Similar to the previous study of 2009, we have analyzed the tractor market in Germany, as a representative core segment and one of the world’s major markets. The aim of the study in 2011 was the detailed analysis of the sales processes of the six largest tractor manufacturers in Germany, as well as the identification of success factors and areas for action from the dealer and customer perspective. So-called “Best in Class” examples show already existing industry-approaches. The study focuses on “customer relationship management”, as well as on the sales phases “pre-purchase”, “sales advisory and purchase decision” and “order and delivery”.
The basic function of a power system stabilizer (PSS) is to add damping to the generator rotor oscillations by controlling its excitation using auxiliary stabilizing signals. To provide damping, the stabilizer must produce a component of electrical torque in phase with the rotor speed deviations. From the 1960s, PSSs are used to add damping to electromechanical oscillations . The PSS is an additional control system, which is often applied as a part of an excitation control system. The PSS is used to apply a signal to the excitation system, producing electrical torques to the rotor in phase with speed differences that damp out power oscillations. They perform within the generator's excitation system to create a part of electrical torque, called damping torque, proportional to speed change. The PSS represents in fig 1 consists of three blocks such as a gain block, a signal washout block, and a phase compensation block which has two blocks for lead-lag compensation. The phase compensation block provides the appropriate phase-lead characteristics to compensate for the phase lag between the exciter input and the generator electrical torque. The signal washout block acts as a high- pass filter with the time constant that allows the signal associated with the oscillations in rotor speed to pass unchanged[2, 7, 8]. The commonly used structure of the PSS is shown in Fig. 1 .
The University of California (UC) Davis designed and developed a small-scale rice husk gas producer for engine operation in mid 80’s . It employs a double-core, down-draft type, dual reactor for continuous operation with gas cleaning train in order to fuel engine. A 5-hp, single cylinder, gasoline engine was successfully operated on producer gas with a centrifugal pump for a period of 9 hrs. A small-scale, downdraft rice hull gas producer was also tested at UC Davis to determine its technical feasibility and to identify its optimal operating parameters . Their results showed that the power output of the engine at rated speed was 43% with brake thermal and overall system efficiencies of 16.8% and 9.4%, respectively. At PhilRice, a batch-type, dual core, downdraft gasifier reactor for pumping water was designed and tested in 2008 . The gasifier is a mobile unit equipped with wet scrubbers and dry packed-bed filters. Water can be pumped from an open source at a rate of 7.5 lps, with 1.3-m head using only 4 kgs of rice husk for a period of 1.35 hr. A rice husk gasification system for elec- tricity generation and for char production was developed at PhilRice in the mid of 2000’s . The gasifier as reported can generate 8 to 12 kW at a rice husk consumption rate of 20 to 30 kg per hour. Gas flow rate was measured at 30 to 40 cubic meter per hour. The char conversion rate was around 25%, depending on the operating condition of the gasifier.
The electric power generated by photovoltaic depends on the radiation of sunlight and the temperature generated so that the photovoltaic will have an average maximum energy level during the day. Photovoltaic that is used directly to generate electrical power will not be optimal because solar radiation is affected by the weather. A Maximum Power Point Tracker (MPPT) method on a photovoltaic system is required to harvest the sun's energy optimally. This method works by controlling the duty cycle on the switch converter thereby making the photovoltaic output power to operate at its maximum point. Hill Climbing algorithm is used as a power tracking algorithm embedded into the microcontroller. In this research used 2 photovoltaic 100 WP, Arduino Uno microcontroller and Boost converter to realize photovoltaic farm. Simulation results using a simulator program show that tracking the maximum potential power of 200 Wp photovoltaic can theoretically be implemented. For the potential value of photovoltaic power is 189.79 watts then this algorithm can detect 159.09 watt. In testing implementation using microcontroller found that by using Hill Climbing algorithm can reach 94.9 watt power from potency value of 113.68 watt photovoltaic.
integration of a single turbine with a Pelton runner using water hydraulics was introduced in Jarquin Laguna (2015), where a passive variable-speed strategy was proposed. How- ever, the addition and simulation of more turbines to the hy- draulic network was not included. In an effort to assess the trade-offs implied by the proposed hydraulic concept, this pa- per extends the time domain simulations to evaluate the per- formance and operational parameters of five turbines coupled to a common hydraulic network for a hypothetical wind farm with centralized electricity generation. In the first part of this work, an overview of the wind farm model is presented to- gether with the control strategy of the hydraulic components; the second part describes a case example where the results are compared with those of a typical wind farm based on conventional wind turbine generator technology.