No abstract

In this paper we propose the design and economic evaluation of the water pumping systems for rice cultivation using solar energy, gasoline fuel and compare both systems. The design of the water and gasoline engine pumping system were evaluated. The gasoline fuel cost used in rice cultivation in an area of 1.6 acres. Under same conditions of water pumping system is replaced by the photovoltaic system which is composed of a solar panel, a converter and an electric motor pump which is compose of a direct current (DC) motor or an alternating current (AC) motor with an inverter. In addition, the battery is installed to increase the efficiency and productivity of rice cultivation. In order to verify, the simulation and economic evaluation of the storage energy battery system with batteries and without batteries are carried out. Finally the cost of four solar pumping systems was evaluated and compared with that of the gasoline pump. The results showed that the solar pumping system can be used to replace the gasoline water pumping system and DC solar pump has a payback less than 10 years. The systems that can payback the fastest is the DC solar pumping system without batteries storage system. The system the can payback the slowest is AC solar pumping system with batteries storage system. However, VAC motor pump of 220 V can be more easily maintained than the motor pump of 24 VDC and batteries back up system can supply a more stable power to the pump system.

No abstract

No abstract

Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. Any small error in the initial condition will lead to forecast errors that grow with increasing forecast time. The methods of ensemble forecasting are developed to generate a representative sample of the possible future states of a dynamical system. For an efficient ensemble forecasting, the initial perturbations to the control analysis should adequately sample the possible analysis errors. The analysis cycle is similar to a breeding cycle, which acts as a nonlinear perturbation model upon the evolution of the real atmosphere. This paper proposes a breeding method for generating ensemble perturbations that can effectively represent the uncertainties in the observed meteorological data. In order to simulate the possible states of northeast monsoon over Southeast Asia under the influence of global warming, selected data from the Intergovernmental Panel on Climate Change (IPCC) are used for testing the generation of initial perturbations in the breeding process by integration of a shallow water model. The results from this research showed the effectiveness of the breeding method in generating ensemble perturbations for short-range weather forecast.