Structural Optimization of Solar Driven Energy and Desalination Systems

Abstract

Planning and dimensioning of desalination plants is usually done by engineers based on an estimation of the capacity of makeup water that is needed for a certain site. Planning a solar- powered system of water and energy supply is complicated and requires a lot of experience from the executing engineer. Optimization methods can support the process of planning complex energy and water supply systems in many ways. Structural optimization is a way to determine an optimized size and configuration for a given task. In this paper a methodology is presented that allows for structural optimization of energy and water supply systems with a focus on a high share of solar energy use. The methodology has been implemented using a software framework that contains functionality for modelling, simulating, optimizing and analyzing energy and water supply systems. Based on load profiles for energy and water as well as technical and economical parameters of the components, a linear optimization is carried out in order to calculate an optimized structure of the system. Furthermore the optimization calculates the capacities of the desalination and energy conversion components and an optimized mode of operation depending on the primary energy prices and solar yield. The methodology uses a MILP algorithm to solve the optimization problem based on linear component models. The linear optimization is coupled with an algebraic equation solver to allow solving of nonlinear equations as well, thus forming a hybrid simulation and optimization algorithm.