An Online Peak Shaving Controller for Optimized Power-Electronic Converter Lifetimes in Turbine Array Generation Systems

Wind and hydrokinetic turbines play an essential role in the transition to carbon-free electricity generation, and improving the economics of turbine systems can accelerate this change. Recognizing that operational costs represent a significant share of the total generation costs, researchers have proposed methods for optimizing the turbine system maintenance while considering the impact of power-electronic converter lifetime on the maintenance costs. This work considers how peak-shaving can be applied to turbine units across an array to exchange energy generation for prolonged power-electronic converter lifetimes and reduced maintenance visits. This work proposes an online peak shaving controller (PSC) that finds the optimal peak-shaving actions by minimizing a function of the predicted levelized cost of energy (LCOE). This real-time minimization of LCOE via a model predictive control style framework ensures the PSC is economically beneficial to the system. The PSC simulates the turbine system with different peak-shaving actions over a prediction horizon, then calculates LCOE considering the power-electronic converter lifetimes and turbine array energy generation. A hardware test demonstrates the real-time peak-shaving action leveraged by the PSC, while a simulation case study for a wind turbine array demonstrates the economic benefit offered over the array's full lifecycle.