Optimal Investment Portfolio of Thyristor- and IGBT-based Electrolysis Rectifiers in Utility-scale Renewable P2H Systems
Yangjun Zeng, Yiwei Qiu, Liuchao Xu, Chenjia Gu, Yi Zhou, Jiarong Li, Shi Chen, Buxiang Zhou
TL;DR
This paper tackles the economic optimization of mixed rectifier configurations (MRs) in utility-scale renewable power-to-hydrogen (ReP2H) systems. It develops a two-stage stochastic programming framework with weighted information gap decision theory (W-IGDT) and solves it via Progressive Hedging (PH) to jointly plan electrolyzer deployments, rectifier types, and reactive-power resources under renewable and hydrogen-price uncertainty. The key findings show that MR configurations can boost revenue by up to 13.78% compared with uniform rectifier designs, with a near-elimination of separate reactive-power compensation when the MRTs are optimally coordinated; a 3:1TR:IGBT-R ratio emerges as the economically favorable mix under current costs. The work provides actionable guidance for industrial planning and demonstrates scalability to large systems, highlighting the importance of coordinating active and reactive power flows for improved capital efficiency in ReP2H operations.
Abstract
Renewable power-to-hydrogen (ReP2H) systems require rectifiers to supply power to electrolyzers (ELZs). Two main types of rectifiers, insulated-gate bipolar transistor rectifiers (IGBT-Rs) and thyristor rectifiers (TRs), offer distinct tradeoffs. IGBT-Rs provide flexible reactive power control but are costly, whereas TRs are more affordable with lower power loss but consume a large amount of uncontrollable reactive power. A mixed configuration of rectifiers in utility-scale ReP2H systems could achieve a decent tradeoff and increase overall profitability. To explore this potential, this paper proposes an optimal investment portfolio model. First, we model and compare the active and reactive power characteristics of ELZs powered by TRs and IGBT-Rs. Second, we consider the investment of ELZs, rectifiers, and var resources and coordinate the operation of renewables, energy storage, var resources, and the on-off switching and load allocation of multiple ELZs. Subsequently, a two-stage stochastic programming (SP) model based on weighted information gap decision theory (W-IGDT) is developed to address the uncertainties of the renewable power and hydrogen price, and we apply the progressive hedging (PH) algorithm to accelerate its solution. Case studies demonstrate that optimal rectifier configurations increase revenue by at most 13.78% compared with configurations using only TRs or IGBT-Rs, existing project setups, or intuitive designs. Under the optimal portfolio, reactive power compensation investment is nearly eliminated, with a preferred TR-to-IGBT-R ratio of 3:1.