Hybridization of Solar Energy with Wind Energy Through Design Space Approach

Abstract

Conventional fuel resources or fossil fuels are rapidly depleting and are not sufficient to meet the future growing energy demand. In addition to that such resources cause pollution and arises the effect of greenhouse, which is alarming the environmental concerns. Thus sustainable and non-pollutant alternate source of energy is required. The solar energy and wind energy are the major renewable energy sources which have the potential to meet the energy demand. However there is a disadvantage to employ them independently, such as unpredictable nature and availability. This situation arise the need of hybridization of these two renewable sources of energy. A hybrid system of solar energy and wind energy will overcome the disadvantages, as both the resources have complementary nature. In this thesis, a methodology for optimal sizing of stand-alone photovoltaic-wind battery system for remote electrification receiving abundant sunshine and wind velocity is proposed. The purpose of proposed methodology is to suggest the design space and optimization of photovoltaic-wind battery system. The methodology incorporates different design constraints to identify all possible design. The design space approach was originally proposed for sizing of the system with known resource and demand. The design space is represen- ted on photovoltaic array area vs battery capacity by taking average solar insolation on different constant loads and varying load demand of a village. It has been observed that minimum as well as maximum battery capacity for a given solar insolation, wind velocity, load demand, collector area and wind turbine rating exists. Similarly minimum collector area and wind turbine rating are calculated on given solar insolation, wind velocity profile, loads demand and battery capacity. A sizing curve is plotted to understand the feasible and non-feasible region of the system. The sizing curve presents the combinations of the photovoltaic array ratings and the corresponding minimum battery capacities capable of meeting the Specified load and is plotted on an array rating vs. battery capacity diagram. System optimization is also presented to calculate annual life cycle cost, annualized cap- ital cost and capital recovery factor etc. the minimum array area, wind turbine rating and battery capacity will act as selection criteria to optimize the system configuration for different reliability levels.