Microgrids are becoming increasingly important for improving the dependability, stability, and quality of the electrical system, as well as for integrating renewable technologies. This paper describes a novel monitoring and alarm system that has been developed to optimize the operation and maintenance of microgrids. The system is unique in that it has been developed using open source software, including Node-RED, Home Assistant, Maria DB, and Telegram, and it allows for easy programming of alarms or warnings. Testing of the system has taken place within the CEDER microgrid and is capable of detecting faults in various components of the microgrid, such as generation units, storage systems, and loads. Upon detecting a fault, the system immediately sends a text message to the mobile phones of the microgrid operator or maintenance crew, enabling them to promptly address the problem. The software can also manage preventive maintenance of the microgrid by sending periodic reminders to the maintenance crew regarding necessary tasks.

This paper shows an experimental application case to convert a part of the grid formed by renewable generation sources, storage systems, and loads into a smart microgrid. This transformation will achieve greater efficiency and autonomy in its management. If we add to this the analysis of all the data that has been recorded and the correct management of the energy produced and stored, we can achieve a reduction in the electricity consumption of the distribution grid and, with this, a reduction in the associated bill. To achieve this transformation in the grid, we must provide it with intelligence. To achieve this, a four steps procedure are proposed: identification and description of the elements, integration of the elements in the same data network, establishing communication between the elements and the control system, creating an interface that allows control of the entire network. The microgrid of CEDER-CIEMAT (Renewable Energy Centre in Soria, Spain) is presented as a real case study. This centre is made up of various sources of generation, storage, and consumption. All the elements that make up the microgrid are incorporated into free software, Home Assistant, allowing real-time control and monitoring of all of them thanks to the intelligence that has been provided to the grid. The novelty of this paper is that it describes a procedure that is not reported in the current literature and that, being developed with Home Assistant, is free and allows the control and management of a microgrid from any device (mobile, PC) and from any place, even though not on the same data network as the microgrid.

The use of wind resources has always gone hand in hand with high wind speeds in open fields. This paper develops the decisions to be taken for the selection, installation, and connection of small wind turbines in peri-urban environments, where wind speeds are medium or low. The guidelines are detailed throughout the document, starting with the study of the wind resource, the selection of the turbine, installation, and real-time monitoring of production for integration into a micro power grid. The installation of small wind systems in places as close as possible to the point of demand makes it possible to achieve a reduction in the cost of the electricity bill. This is thanks to the instantaneous control of generation and demand at a particular level through the installation of software, in this case, Home Assistant. The novelty of this paper is the use of this software Home Assistant to integrate of a small wind turbine in a microgrid and its control system.

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In recent years, there has been an increasing commitment to give batteries a second life, as they are being consumed for different uses and the recycling methods are not defined. This work aims to show how a storage system based on disused Lithium Iron Phosphate (LFP) batteries has been recovered and integrated into the CE.D.E.R- CIEMAT smart microgrid over a period of ten years during which the operation of the system has been affected. During the recovery process, the cells have been classified according to their voltage, and a series of charge-discharge processes have been carried out on them at different voltages to determine their state of health and capacity. Once characterised, the system was assembled and commissioned with the appropriate cells. In addition, for the storage system, a Supervisory Control And Data Acquisition (SCADA) has been developed in Home Assistant for its integration into the CE.D.E.R.'s microgrid management system. This allows the microgrid to be managed more efficiently, storing surplus energy from distributed generation sources and discharging the stored energy during peak consumption periods to reduce peaks, reduce discharges to the distribution grid and reduce the cost of electricity bills.