Kernel estimation modelling and optimization of hybrid power system for a typical South African rural area

To increase the accessibility of electricity even to those rural sparsely scattered isolated rural regions, renewable energy seems to be a viable and sustainable option. Before investing in renewables in these areas, a feasibility study is of paramount importance starting with assessing and determining the amount of available solar irradiance and wind speeds for the area. In addition, a techno-economic feasibility study is of paramount importance to determine the most economical and sustainable standalone hybrid system. This research presents a study using a nonparametric kernel density estimation method to determine solar irradiance and wind speeds. In addition to this kernel determination method, the study performs a feasibility analysis using a hybrid renewable energy system that consists of two renewables with biodiesel and battery backup to supply the energy demands of a rural household in South Africa. The research commences with a literature review of several probability distribution functions (pdfs) commonly used in testing both solar irradiance and wind speeds. It established that not all sites can be defined by the same pdf and there is no science in selecting a distribution function but rather random testing of a range of functions. The parametric probability functions tested in this work are Gamma, Weibull, and Lognormal. The work then compares the performance of these parametric pdfs with the nonparametric kernel density estimation method which this study advocates for its application. In judging the performance and correctness of these pdfs, mean bias error (mbe) and root mean square error (rmse) are used as performance test criteria for the parametric probability distribution function. As for the nonparametric pdf which this research advocates for its use, an integral squared error, ISE is used for the presentation assessment with the conventional parametric normal distribution. From the results, it is observed with the proposed nonparametric kernel density estimator gives precise estimation and improved adaptableness, as opposed to the widely used conventional parametric distribution for both the use in solar irradiation and wind, speeds estimations. In addition, the research results demonstrated that the commonly used Epanechnikov and Gaussian KDE methods were the most adjustable methods for all seven tested stations. The second aspect of the study applies the tested data to design and perform a feasibility study of using a hybrid renewable energy system that consists of two renewables with biodiesel and battery backup to supply energy demands for a typical rural household. Thus, the study makes use of a simulation to design and determine an optimized hybrid renewable energy system for application in rural households. The energy resources considered for this standalone hybrid system are solar PV, wind, diesel generator, and a storage battery system. In performing the system simulation and optimization concerning economic viability, sustainability, energy efficiency, and environmental impact is carried out using the Hybrid Optimization Model for Electric Renewables (HOMER) simulation and optimization software tool. Concerning the results obtained, HOMER gave seven best-optimized systems. In breaking down the seven optimized results, four of the results were hybrid energy systems and three with only one energy resource. Moreover, from these results, three systems were pure green energy supplied and not utilizing any diesel generator (DG). The best-optimized system for this rural household consisted of PV/DG with an NPC of $ 72,720, while the system which utilized all resources available was second-ranked with an NPC of $ 79,272. The use of only renewable resources for this region was fourth-ranked with NPC of $ 86,760. The study demonstrates the feasibility and viability of having rural areas benefit from electricity access. Moreover, this study will contribute towards the strides of just energy transition envisaged by the country in solving the energy crisis currently being experienced.