Influence of high-resolution data on accurate curtailment loss estimation and optimal design of hybrid PV–wind power plants

Abstract

Hybrid photovoltaic (PV) - wind power plants (HyPPs), i.e., where the PV and wind systems are co-located and share the Point of Interconnection (POI) with the grid, have recently attracted more attention. This trend is driven by the expected reduced capital and operational expenditures achieved through, e.g., shared land and POI infrastructure for HyPPs compared to two individual PV and wind installations. However, if the POI is underdimensioned relative to the PV and wind capacities, the generation from either or both of the assets must at times be curtailed, unless mitigated by solutions like energy storage. This curtailment might lead to income losses. Moreover, as HyPPs typically are designed using wind and PV generation data on hourly resolution, the actual curtailment losses can be underestimated. This might in turn lead to HyPP designs which are techno-economically sub-optimal.

In this study, a comparative analysis is conducted to analyze how the curtailment and income loss estimations for HyPPs, as well as the techno-economic optimal HyPP topologies, are impacted by varying the input data time resolution. One year of site measured PV and wind power generation data on 5 s resolution from an existing HyPP located in Eastern Germany are used as basis for the study. For a HyPP topology with an undersized POI, where the installed capacities of the POI, PV, and wind systems are all equal, the curtailment losses are estimated to be 1.45%, 1.43% and 1.09% using the 5 s, 1 min and 1 h resolution datasets, respectively. Moreover, using the 1 h instead of the 1 min dataset leads to a 1.86% overestimation of the total Net Present Value (NPV) for this HyPP topology. As the shares of the PV and wind systems increase relative to the POI capacity, the differences in the estimation of the curtailment losses and NPVs between the high- and low-resolution datasets become more significant.