The progressive increase in hydrogen technologies’ role in transport, mobility, electrical microgrids, and even in residential applications, as well as in other sectors is expected. However, to achieve it, it is necessary to focus efforts on improving features of hydrogen-based systems, such as efficiency, start-up time, lifespan, and operating power range, among others. A key sector in the development of hydrogen technology is its production, renewable if possible, with the objective to obtain increasingly efficient, lightweight, and durable electrolyzers. For this, scientific works are currently being produced on stacks technology improvement (mainly based on two technologies: polymer electrolyte membrane (PEM) and alkaline) and on the balance of plant (BoP) or the industrial plant (its size depends on the power of the electrolyzer) that runs the stack for its best performance. PEM technology offers distinct advantages, apart from the high cost of its components, its durability that is not yet guaranteed and the availability in the MW range. Therefore, there is an open field of research for achievements in this technology. The two elements to improve are the stacks and BoP, also bearing in mind that improving BoP will positively affect the stack operation. This paper develops the design, implementation, and practical experimentation of a BoP for a medium-size PEM electrolyzer. It is based on the realization of the optimal design of the BoP, paying special attention to the subsystems that comprise it: the power supply subsystem, water management subsystem, hydrogen production subsystem, cooling subsystem, and control subsystem. Based on this, a control logic has been developed that guarantees efficient and safe operation. Experimental results validate the designed control logic in various operating cases, including warning and failure cases. Additionally, the experimental results show the correct operation in the different states of the plant, analyzing the evolution of the hydrogen flow pressure and temperature. The capacity of the developed PEM electrolysis plant is probed regarding its production rate, wide operating power range, reduced pressurization time, and high efficiency.

This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices’ lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish.