Value maximization of grid-connected Hybrid Power Systems using ground-gen Airborne Wind Energy

Abstract

Airborne wind energy (AWE) is a wind energy technology in the development phase consisting of tethered kites that reach high altitudes consisting of relatively stable wind speeds. While no company has yet reached the point of commercial viability, a variety of AWE technology concepts and designs have been under development and are currently at low- to intermediate technology readiness levels. When AWE systems are grid-connected a power smoothing element is needed to smooth the oscillating power output of the system for the grid. In this thesis, a framework for modeling a grid-connected hybrid power system (HPS) consisting of AWE and batteries participating in the day-ahead market (DAM) has been developed in the MATLAB environment. The framework incorporates an existing AWE performance and cost model with power smoothing performance, battery degradation, and DAM storage arbitrage. Multiple use case scenarios are evaluated to test the economic performance of multiple configurations of the HPS. These scenarios are; an AWE system with an ultracapacitor (UC); an AWE system with batteries; a battery system operating in DAM arbitrage and an AWE system with batteries operating in DAM arbitrage. The configurations were evaluated using multiple performance metrics, primarily the internal rate of return (IRR) as a metric for economic performance. A simulation of the HPS participating in storage arbitrage was then used to determine the economic viability of using the battery system for both power smoothing and arbitrage. The arbitrage behavior of the storage system was determined by a heuristic selling logic model developed to simulate the combined use of a storage system for power smoothing and arbitrage. The arbitrage logic is based on price volatility and power smoothing constraints.

The battery power smoothing system resulted in significantly lower system cost overall and consequently an increase in profitability (IRR of 12.37%) compared to the more expensive UC power smoothing configuration (IRR of 10.20%). The HPS configuration with batteries used for power smoothing combined with arbitrage showed a marginal increase in economic performance with an IRR of 12.43%. This showed a potential value increase of the system when using excess capacity arbitrage but not at a significant rate.