Optimal Design of Solar Energy Systems With Uncertain Data

Abstract

The technical and economic characteristics of optimized solar energy systems can be expressed in a concise mathematical expression and this expression manipulated to show the dependence of total system cost on variables such as collector cost and efficiency, weather data, or the cost of the backup fuel. The lack of certain knowledge of future weather, fuel prices, and system performance implies that a system optimized, with respect to an assumed set of these data, may not be optimal with respect to the realities of operation. This formulation demonstrates clearly how the life cycle costs of the system increase as a result of errors in estimating various system parameters; in most cases, the costs of errors are not large over their expected ranges. In particular, most solar energy systems designed to satisfy a given load (that is, having a given nameplate capacity) should be optimized for the best weather they may encounter, and this design used wherever the systems are economically viable, as it is likely that the savings due to standardization will outweigh the relatively small costs of being imperfectly optimized.