Martin Bischoff

Hard uncertainties in multiobjective layout optimization of photovoltaic power plants

Abstract This paper describes how to treat hard uncertainties defined by so-called uncertainty maps in multiobjective optimization problems. For the uncertainty map being set-valued, a Taylor formula is shown under appropriate assumptions. The hard uncertainties are modeled using parametric set optimization problems for which a scalarization result is given. The presented new approach for the solution of multiobjective optimization problems with hard uncertainties is then applied to the layout optimization of photovoltaic power plants. Since good weather forecasts are difficult to obtain for future years, weather data are really hard uncertainties arising in the planning process. Numerical results are presented for a real-world problem on the Galapagos island Isabela.

Optimized Pattern Design for Photovoltaic Power Stations

The task of planning photovoltaic (PV) power plants is very challenging . The decision makers have to consider the local weather conditions, the land area’s topography, the physical behavior of the technical components and many more complex aspects. We present an approach for optimizing one variant of the way routing problem for PV plants. We formulate the problem as an Integer Program (IP) which can be solved by standard solvers. In addition, we reformulate the IP as a maximum independent set problem on interval graphs. This graph-theoretic problem can be solved in polynomial time. Using the latter approach, we are able to generate a variety of solutions with different angles for the ways with little effort of time.