Towards Optimal Solar Tracking: A Dynamic Programming Approach

Abstract

The power output of photovoltaic systems (PVS) increases with the use of effective and efficient solar tracking techniques. However, current techniques suffer from several drawbacks in their tracking policy: (i) they usually do not consider the forecasted or prevailing weather conditions; even when they do, they (ii) rely on complex closed-loop controllers and sophisticated instruments; and (iii) typically, they do not take the energy consumption of the trackers into account. In this paper, we propose a policy iteration method (along with specialized variants), which is able to calculate near-optimal trajectories for effective and efficient day-ahead solar tracking, based on weather forecasts coming from on-line providers. To account for the energy needs of the tracking system, the technique employs a novel and generic consumption model. Our simulations show that the proposed methods can increase the power output of a PVS considerably, when compared to standard solar tracking techniques.

Energy- and Cost-Efficient Pumping Station Control

“…Apart from the deterministic effects of water flow and pumping station actions, the state transition is influenced by rainfall and energy price development. It is imaginable that there could be correlations between these (Panagopoulos, Chalkiadakis, and Jennings 2015), which an analysis of 10 years of historical data confirms (Kanters 2015). We therefore propose a method of simulation that preserves these correlations.…”