http://erepository.uonbi.ac.ke/handle/11295/10313 Tue, 28 Apr 2026 15:12:58 GMT 2026-04-28T15:12:58Z http://erepository.uonbi.ac.ke/handle/11295/155090 Optimal Load Shedding Scheme for a Model Renewable Energy Micro-Grid. Musyoka, Paul M; Musau, Peter; Nyete, Abraham Optimization of demand control in renewable energy micro-grids involves developing load shedding schemes and searching for the most optimum. With climate change campaign in favor of renewable energy micro-grids or integration to national grids, the stability of the systems becomes more unpredictable. Its therefore justified, technically and economically, to optimize both unit commitment plans to track the load curve closely and design load-shedding schemes that attain the voltage and frequency limits, while retaining maximum load on the grid. The study shows that through load-shedding, renewable energy micro-grids can be operated in the stable state at the expense of loads during times of severe power imbalances. Optimization of the load-shedding using PSO-GA technique ensure optimum amount of load is shed from the grid with each possible load shedding scheme getting evaluated first and selection of most effective scheme with priority for loads is accomplished. Wed, 01 Jan 2020 00:00:00 GMT http://erepository.uonbi.ac.ke/handle/11295/155090 2020-01-01T00:00:00Z http://erepository.uonbi.ac.ke/handle/11295/155089 Coherent Swing Under-Frequency Transient Stability for Renewable Sources Islanded Micro-Grid. Musyoka, Paul M; Musau, Peter Moses; Nyete, Abraham Renewable Energy Sources micro-grids experience operational challenges due the unpredictable weather patterns, requiring continuous demand control schemes, which are detrimental to both customers and the micro-grid operator. Optimal unit commitment plans coupled with a synthetic inertia system, that is, distributed renewable energy storage (DRES), are considered to lower power imbalances and thus contributing to frequency transient stability. This research models a renewable energy micro-grid with solar PV, wind turbine, hydro and a geothermal power plant. The transient stability study during times of severe power imbalances shows the micro-grid is unstable during such a time. Particle swarm optimization is developed to commit the units in an optimal scheme that considers load flow power losses and DRS in a multi-objective function. This improves the control and operation of the micro-grid, minimizing frequency fluctuations caused by power imbalance, at times of severe shortage of generation from intermittent renewable sources. Wed, 01 Jan 2020 00:00:00 GMT http://erepository.uonbi.ac.ke/handle/11295/155089 2020-01-01T00:00:00Z http://erepository.uonbi.ac.ke/handle/11295/101630 A hybrid MRI method based on denoised compressive sampling and detection of dominant coefficients Kiragu, Henry; Mwangi, Elijah; Kamucha, George In this paper, a hybrid method for acquisition and reconstruction of sparse magnetic resonance images is presented. The method uses conventional spin echo Magnetic Resonance Imaging (MRI) with only a few Phase-encoding steps to obtain the dominant k-space data coefficients. The rest of the k-space data coefficients are estimated using Compressive Sampling (CS). The compressive sampling part of the algorithm uses a random matrix to sample the vectorized k-space data of the image at a sub-Nyquist rate followed by reconstruction of the Discrete Wavelet Transform (DWT) coefficients of the k-space data using Orthogonal Matching Pursuit (OMP). The DWT coefficients are then transformed into the Discrete Fourier Transform (DFT) domain and denoised prior to combination with the dominant DFT coefficients obtained using conventional MRI to yield the whole k-space of the reconstructed image. The reconstructed k-space data is finally transformed into the reconstructed image using inverse DFT. Computer simulation results show that the proposed procedure yields better results than other conventional CS-MRI methods in terms of Peak Signal to Noise Ratio (PSNR) and Structural SIMilarity (SSIM) index. Tue, 01 Aug 2017 00:00:00 GMT http://erepository.uonbi.ac.ke/handle/11295/101630 2017-08-01T00:00:00Z http://erepository.uonbi.ac.ke/handle/11295/98217 Climate And Meteorology Ng'anga, J.k. Thu, 01 Dec 1988 00:00:00 GMT http://erepository.uonbi.ac.ke/handle/11295/98217 1988-12-01T00:00:00Z