Evaluating Strategic Day-ahead Scheduling of Power-to-Hydrogen Facilities in Power Systems with Pervasive Renewable Energy Integration

Increasing reliance on renewable-based power generation in power systems has attracted widespread interest from countries around the globe. Nevertheless, accommodating an increased share of them necessitates heightened flexibility. Therefore, it is essential to tackle the matter of flexibility within power systems through both technical and economic perspectives. In this regard, a primary challenge confronting power systems equipped with substantial renewable integration pertains to the alleviation of grid congestion arising from the massive injection of renewable-driven generators. Despite that grid upgrading provides a potential remedy for congestion mitigation, this approach entails a prolonged timeline and significant financial expenditure, accompanied by environmental concerns. Consequently, alternative approaches are required to enhance grid flexibility. Hence, this paper specifically seeks to address an in-depth exploration of the decision-making process undertaken by strategic operators of power-to-hydrogen (P2H) facilities in adjusting their plant's day-ahead scheduling strategies according to the price signals received from the grid operator. In this model, the P2H unit's operator establishes its most effective strategies for the day ahead. This includes purchasing electricity from the power system, engaging in the ancillary service market, selling hydrogen in the hydrogen market as well as unlocking the potential revenue of by-products. Meanwhile, the Transmission System Operator (TSO) holds the responsibility of ensuring that the power generation and consumption of various grid participants adhere to security limits. Additionally, the TSO computes the Locational Marginal Price (LMP) across distinct grid nodes. This LMP acts as a pricing signal, incentivizing users to adjust their power output patterns in a manner that reduces congestion and enhances overall flexibility. Therefore, the model in this paper is structured as a bi-level programming framework. The upper level includes the P2H plant's optimal day-ahead scheduling, while the lower level encompasses the TSO's optimal power flow (OPF) mathematical problem. In the lower level, LMP for each hour are calculated and conveyed to the upper level. Consequently, the strategic P2H operator refines its optimal determinations. The applicability of the proposed model is illustrated by a case study in Denmark which involves a significant number of wind turbines. The valuation of diverse flexibility offerings, including ancillary service provision and congestion alleviation by the P2H facility, is carefully assessed. Furthermore, the study investigates the potential influence of introducing price signals within the electricity grid on the optimal operation of the P2H plant as well as its implications for participating in other energy carriers’ markets. The findings derived from this paper hold significant promise and offer practical insights for various stakeholders involved. For P2H plant owners, the outcomes provide clear direction regarding the extent to which strategic decision-making, coupled with price signals like LMP, can yield additional profits, thus spurring increased investment in such facilities. Furthermore, grid operators can assess the potential success of introducing price incentives to activate P2H units for delivering flexibility solutions.