Vishnu Prasad

Scheduling of Cascaded Hydro Power System: A New Self Adaptive Inertia Weight Particle Swarm Optimization Approach

The scheduling of hydro electric system means to optimize the generation of hydro units from available water resources so as to maximize total benefits of hydro energy satisfying various constraints. This problem becomes more complex when the hydro plants are in the cascade pattern. The scheduling of cascaded hydro system should be in such way that water discharge from upstream plant can be effectively utilized at downstream plant satisfying all operational constraints. Particle swarm optimization (PSO) algorithm has successfully applied for such problems. Most of the existing improved Particle Swarm Optimization (PSO) algorithms have been suffered from premature convergence. To overcome this problem, New Self Adaptive Inertia Weight Swarm Optimization (NSAIW_PSO) with special function is adopted for scheduling of hydro power plants in this paper. This approach is applied on a real operated cascaded hydroelectric system located in state Madhya Pradesh, India. The results from presented approach are critically compared with that of Linearly Decreasing Inertia Weight (LDIW_PSO) method and found to give better solution.

Performance Evaluation of Hydraulic Francis Runner at Different Blade Stagger

The runner of turbine extracts energy from flowing water and hence plays great role in efficiency of turbine. The design of runner is based on many assumptions as the flow behavior is affected by many design parameters. Hence it is customary to assess the flow behavior in runner space for its efficient design. In this paper, numerical simulation of Francis turbine space has been carried out for four variants of runner with different blade stagger values at three guide vane openings. The local and global hydrodynamic parameters for runner and turbine are computed and the effect of stagger on these parameters at different turbine operating regime is studied.

Bathymetric Mapping of Bhopal City Lower Lake Using IRS-P6: LISS-4 Imagery and Artificial Neural Network Technique

Bathymetry is the studies of underwater depth of a lake or ocean floors. Implementing bathymetric survey is expensive, time consuming and laborious process because it involved in the measurements for depth at point of the large area; it can be reduced using remote sensing techniques. The depth may be determined from the satellite images by establishing the correlation between lake depth and spectral reflectance of the image. Artificial Neural Network (ANN) techniques were used in this context has an advantage of the depth estimation possibility, without refining the depth causing scattering from environmental factors (e.g. bottom material and vegetation). In this research work, investigations have been done on the usage of the empirical models for depth determination and also on the suitability of bands. Least squares regression analysis has failed to produce desired result. ANN based Cascade Forward (CF) back propagation model was tested for single and multi band. Its result showed that using multiband (2&3) has produced comparatively better results than the classical regression analysis. The validation is performed by the various standard statistical tests such as Chi-square, t test and Mean Absolute Percentage error. Linear regression plot of measured depth and actual depth were also plotted.

Performance Analysis of Axial and Mixed Flow Turbines: A Comparative Study

The reaction turbines have application for very wide range of hydro power projects. Turbine is the most important component of hydro power plant. Its cost varies 15-35% of the total cost of hydropower project. The analysis of flow behavior of turbine under various operating conditions for cost effective design of the turbine is utmost importance. The model testing of turbine gives overall performance of turbines based on global parameters. This approach is very costly and time consuming. The computational fluid dynamics compliments experimental and theoretical approach by providing an alternate cost effective means of simulating real turbulent flow. In the present paper, the numerical flow simulation of axial and mixed flow turbine has been carried out to study the effect of operating conditions on the local and global parameters of turbine. The simulation results for efficiency and output bear close comparison with experimental results.