Reliability estimation and comparison of stand-alone pv-generated house with grid-connected house
Reliable modern energy is essential to raising the living standards for an expanding worldwide population. The concept of renewable energy is a priority because of insufficient minerals and fossil fuels being used by conventional sources. The reliability of these renewable sources is a challenging task. Renewable energy requires more reserves and storage, and its generation is affected by weather, the seasons, and geographical location. Solar photovoltaic (PV) power generation is one of the major renewable sources of energy. If a house is fully dependent upon energy generated from solar PV sources and is not connected to the grid, then that house is referred to as a stand-alone PV-generated house. The purpose of this thesis is to compare the reliability of a stand-alone PV-generated house with the reliability of a grid-connected house. The PV generation system in a house includes PV panels, charge controller, battery, inverter, and wiring system. A grid-connected house simply has a cable connected to a nearby distribution system. First, the size of the PV system for a specific geographical location is estimated by taking the average load of a house. Then the size of the PV panel, charge controller, battery, and inverter are estimated. Reliability of the inverter, wiring system, and charge controller are estimated using the failure rate of their internal individual electronics components. Since they have an insignificant aging effect, exponential distribution is used to estimate their reliability. The battery has a time-dependent failure rate, and its failure increases with aging; therefore, the Weibull distribution approach is used to estimate the failure and reliability of the battery. Similarly, because of the significant aging effect on PV panels, the Weibull distribution is applied to their estimated failure rate. Finally, the overall failure rate of the system is used to estimate the average interruption duration in a year. That value is compared with the system average interruption duration index (SAIDI) of the distribution system.