911 resultados para Irrigation scheduling


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The visit highlighted the vital contribution of the inland fisheries sector to provision of basic food security within the uncleared area (farmers report very low consumption frequencies for all other fish or meat protein substitutes). A 30-mile system of Brackish water lagoons which demarcates the cleared and uncleared areas is the main source of retailed fish in the uncleared area. Second in importance is the inland tank fishery, where the bulk of production emanates from 17 major irrigation reservoirs. [PDF contains 29 pages]

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One of the critical problems currently being faced by agriculture industry in developing nations is the alarming rate of groundwater depletion. Irrigation accounts for over 70% of the total groundwater withdrawn everyday. Compounding this issue is the use of polluting diesel generators to pump groundwater for irrigation. This has made irrigation not only the biggest consumer of groundwater but also one of the major contributors to green house gases. The aim of this thesis is to present a solution to the energy-water nexus. To make agriculture less dependent on fossil fuels, the use of a solar-powered Stirling engine as the power generator for on-farm energy needs is discussed. The Stirling cycle is revisited and practical and ideal Stirling cycles are compared. Based on agricultural needs and financial constraints faced by farmers in developing countries, the use of a Fresnel lens as a solar-concentrator and a Beta-type Stirling engine unit is suggested for sustainable power generation on the farms. To reduce the groundwater consumption and to make irrigation more sustainable, the conceptual idea of using a Stirling engine in drip irrigation is presented. To tackle the shortage of over 37 million tonnes of cold-storage in India, the idea of cost-effective solar-powered on-farm cold storage unit is discussed.

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Real-time demand response is essential for handling the uncertainties of renewable generation. Traditionally, demand response has been focused on large industrial and commercial loads, however it is expected that a large number of small residential loads such as air conditioners, dish washers, and electric vehicles will also participate in the coming years. The electricity consumption of these smaller loads, which we call deferrable loads, can be shifted over time, and thus be used (in aggregate) to compensate for the random fluctuations in renewable generation.

In this thesis, we propose a real-time distributed deferrable load control algorithm to reduce the variance of aggregate load (load minus renewable generation) by shifting the power consumption of deferrable loads to periods with high renewable generation. The algorithm is model predictive in nature, i.e., at every time step, the algorithm minimizes the expected variance to go with updated predictions. We prove that suboptimality of this model predictive algorithm vanishes as time horizon expands in the average case analysis. Further, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance. Finally, we evaluate the algorithm via trace-based simulations.

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One of the most challenging problems in mobile broadband networks is how to assign the available radio resources among the different mobile users. Traditionally, research proposals are either speci c to some type of traffic or deal with computationally intensive algorithms aimed at optimizing the delivery of general purpose traffic. Consequently, commercial networks do not incorporate these mechanisms due to the limited hardware resources at the mobile edge. Emerging 5G architectures introduce cloud computing principles to add flexible computational resources to Radio Access Networks. This paper makes use of the Mobile Edge Computing concepts to introduce a new element, denoted as Mobile Edge Scheduler, aimed at minimizing the mean delay of general traffic flows in the LTE downlink. This element runs close to the eNodeB element and implements a novel flow-aware and channel-aware scheduling policy in order to accommodate the transmissions to the available channel quality of end users.

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The aim of this research study has been to design a gain scheduling (GS) digital controller in order to control the voltage of an islanded microgrid in the presence of fast varying loads (FVLs), and to compare it to a robust controller. The inverter which feeds the microgrid is connected to it through an inductance-capacitor-inductance (LCL) filter. The oscillatory and nonlinear behaviour of the plant is analyzed in the whole operating zone. Afterwards, the design of the controllers which contain two loops in cascade are described. The first loop concerns the current control, while the second is linked to the voltage regulation. Two controllers, one defined as Robust and another one as GS controller, are designed for the two loops, emphasizing in their robustness and their ability to damp the oscillatory plant behaviour. To finish, some simulations are carried out to study and compare the two kinds of controllers in different operating points. The results show that both controllers damp the oscillatory behaviour of the plant in closed loop (CL), and that the GS controller ensures a better rejection of current disturbances from FVLs.

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This paper deals with the resource allocation problem aimed at maximizing users' perception of quality in wireless channels with time-varying capacity. First of all, we model the subjective quality-aware scheduling problem in the framework of Markovian decision processes. Then, given that the obtaining of the optimal solution of this model is unachievable, we propose a simple scheduling index rule with closed-form expression by using a methodology based on Whittle approach. Finally, we analyze the performance of the achieved scheduling proposal in several relevant scenarios, concluding that it outperforms the most popular existing resource allocation strategies.

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The viability of integrating rice farming with fish culture was studied in ten (10) rice plots. The on-farm research was done during one rice-growing season starting May 2003. The rice variety used was IR 2793-80-1 while the fish species was the Nile tilapia, Oreochromis niloticus. The fish culture period lasted 77 days. An average fish production of 132.4 kg/ha was obtained. The mean recovery rate of tilapia was 43 per cent. Total rice yield from the fields stocked with fish was lower than from unstocked fields. The net returns were not significantly different.

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This report is a contribution to an assessment of the current status of agriculture in Cambodia, focusing on the linkages between agriculture and water, mainly in the form of irrigation. It seeks to view current government policies on agriculture and irrigation in the context of experiences on the ground, as communicated through the many field studies that cover varied aspects of performance in the agriculture sector and irrigation schemes. In an effort to identify future research areas, this review examines the status quo, and connects or disconnects with stated policy through a broad lens to capture strengths and challenges across crop production, irrigation management and post-harvest contexts. It places irrigation under scrutiny in terms of its value as a major area of government expenditure in recent years, and asks whether it presents the best potential for future gains in productivity, when compared with the prospects offered by investments in other aspects of agriculture. The fieldwork and review of current literature that form the basis of this report were undertaken at the request of, and partly funded by, the Australian Centre for International Agricultural Research (ACIAR). It is also intended to contribute knowledge to the CGIAR Research Program on Aquatic Agricultural Systems (AAS) led by WorldFish, who co-funded the activities.