In this study, we employ an optimization model to optimally design a self-sufficient, independent of any imports and exports, hydrogen infrastructure for Austria by 2030. Our approach integrates key hydrogen technologies within a detailed spatial investment and operation model – coupled with a European scale electricity market model. We focus on optimizing diverse infrastructure components including trailers, pipelines, electrolyzers, and storages to meet Austria's projected hydrogen demand. To accurately estimate this demand in hourly resolution, we combine existing hydrogen strategies and projections to account for developments in various industrial sectors, consider demand driven by the transport sector, and integrate hydrogen demand arising from its use in gas-powered plants. Accounting for the inherent uncertainty linked to such projections, we run the analysis for two complementary scenarios. Our approach addresses the challenges of integrating large quantities of renewable hydrogen into a future energy system by recognizing the critical role of domestic production in the early market stages. The main contribution of this work is to address the gap in optimizing hydrogen infrastructure for effective integration of domestic renewable hydrogen production in Austria by 2030, considering sector coupling potentials, optimal electrolyzer placement, and the design of local hydrogen networks.

Renewable energy sources (RES) can provide valuable flexibility potential for multiple markets and grid services in the future. In this paper, the focus lies on the development of algorithms for an optimal dispatch and bidding of a RES-based virtual power plant (VPP) by considering current short-term and balancing market conditions in Austria, as well as a proposed redispatch market. Specifically, different pricing and bidding strategies for a redispatch market are compared and their feasibility is analyzed. The attractiveness of different pricing models and remuneration mechanisms for redispatch, as well as the influence of the redispatch call probability on the bidding behavior of the VPP, is investigated. The simulation of the bidding behavior is carried out using linear optimization techniques. The paper describes the algorithms as well as the assumptions for market rules in redispatch, balancing and short-term electricity markets. The results show that the probability to be activated for redispatch and thus the required incentives depend highly on the location of the plant. Pre-curtailment of the plant to offer positive redispatch is not recommended as the prices would need to be set at up to 200–300% of the day-ahead price.