A stochastic programming approach for the planning and operation of a power to gas energy hub with multiple energy recovery pathways

Abstract

There is a need for energy storage to improve the efficiency and effectiveness of energy distribution with the increasing penetration of renewable energy sources. Among the various energy storage technologies being developed, 'power-to-gas' is one such concept which has gained interest due to its ability to provide long term energy storage and recover the energy stored through different energy recovery pathways. Incorporation of such systems within the energy infrastructure requires analysis of the key factors influencing the operation of electrolyzers and hydrogen storage. This study focusses on assessing the benefits power-to-gas energy storage while accounting for uncertainty in the following three key parameters that could influence the operation of the energy system: (1) hourly electricity price; (2) the number of fuel cell vehicles serviced; and (3) the amount of hydrogen refueled. An hourly time index is adopted to analyze how the energy hub should operate under uncertainty. The results show that there is a potential economic benefit for the powerto-gas system if it is modeled using the two-stage stochastic programming approach in comparison to a deterministic optimization study. The power-to-gas system also offers environmental benefits both from the perspective of the producer and end user of hydrogen.