An Evolutionary Approach to Geo-Planning of Renewable Energies

Abstract

Renewable energy sources are getting more and more important in many industrial nations. As their behavior and effectiveness often depends on their location, the employment of geo-planning and geo-optimization strategies improves their value. A geo-planning process must consider multiple aspects and different requirements resulting in a constrained optimization problem. In this work, we introduce a new optimization approach for geo-planning based on evolutionary strategies. For this sake, we adapt evolutionary operators and employ deterministic parameter control. We define an experimental setting for wind turbines with different potentials, constraints, and wake effects. In the experimental part of this work, we first show the behavior of the approach on toy settings. Extended settings with real-world geographical data, ground mounted solar power plants, and political conditions demonstrate the flexibility and extensibility of the approach.