Relevance of Optimized Low-Scale Green H2 Systems in a French Context: Two Case Studies

Abstract

Hydrogen has been identified as a very promising vector for energy storage, especially for heavy mobility applications. For this reason, France is making significant investments in this field, and use cases need to be evaluated as they are sprouting. In this paper, the relevance of H2 in two storage applications is studied: a domestic renewable electricity production system connected to the grid and a collective hydrogen production for the daily bus refill. The investigation consists of the sizing of the system and then the evaluation of its performance according to several criteria depending on case. Optimizations are made using Bayesian and gradient-based methods. Several variations around a central case are explored for both cases to give insights on the impact of the different parameters (location, pricing, objective, etc.) on the performance of the system.Our results show that domestic power-to-power applications (case 1) do not seem to be competitive with electrochemical storage. Meanwhile, without any subsidies or incentives, such configuration does not allow prosumers to save money (+16% spendings compared to non-equipped dwelling). It remains interesting when self-sufficiency is the main objective (up to 68% of energy is not exchanged). The power-to-gas application (case 2, central case), with a direct use of hydrogen for mobility, seems to be more relevant according to our case study, we could reach a production cost of green H2 around 5 €/kg, similar to the 3–10 $/kg found in literature, for 182 houses involved. In both cases, H2 follows a yearly cycle, charging in summer and discharging in winter (long term storage) due to low conversion efficiency.

Usage of GAMS-based Digital Twins and Clustering to Improve Energetic Systems Control

“…The importance of Energy Management Systems (EMS) has increased over the years and is drilling down to individual systems, like individuals or groups of dwellings, or solar community. In a previous article [3] we have studied the opportunity of integrating energy storage technologies for such scales. In this article we will focus on the generation of H 2 in sufficient volume to refuel a bus on a daily basis.…”

“…This case is very similar to the one investigated in a previous work. Then, to get further details about final cost of hydrogen, self-sufficiency of the microgrid or physical models (apart from the wind turbine, the electrolyser and the compressor), the reader is invited to consult [3]. The same stands for the private homemade Python software used for simulation.…”

“…The evolution of the pressure P st in the stock evolves dynamically as a function of hydrogen production and consumption. The model is described in [3].…”

“…In this paper a collective production of hydrogen for a daily filling of a bus is considered. Following our previous work on the subject [3], the investigation consists of finding an optimal buy/sell rule to the grid, and the use of the energy with an additional objective: mobility. The dominant technique in the energy community is reinforcement learning, which is however difficult to use when the learning data is limited as in our study.…”

Usage of GAMS-Based Digital Twins and Clustering to Improve Energetic Systems Control

“…This usage fits into the European plan for hydrogen development [3] and some hydrogen buses are already in service in Europe [4]. Following our previous work on this case study [5], the investigation consists of finding an optimal buy/sell rule to the grid, and the use of the energy with an additional objective: mobility. The dominant technique in the energy community is reinforcement learning, which is however difficult to use when the learning data is limited, as in our study.…”