# On Hybrid Nanogrids Energy Management Systems--An Insight into Embedded Systems
## 1 Introduction
EMS for buildings describes some techniques for modeling occupant comfort as well as for load management, especially those that are modifiable over time or over the duration of use [40; 41]. Other work aims to increase the energy efficiency of a building by satisfying the needs of the occupants [42]. A rule-based, real-time EMS for the development of integrated microgrids has been proposed by [PERSON] et al. [43]. They describe a rule-based power control algorithm that can switch between grid supply, load shedding, battery charging and discharging, and PV limit modes. The choice of procedures is based on battery SOC, time-of-use tariff, and load generation imbalance. PV power, load demand, and the reference DC bus voltage are used as inputs in the PI controller to determine the load generation imbalance, which stabilizes the DC bus voltage. Battery backup and the main grid compensate for this imbalance. [PERSON] et al. [44] suggested a hierarchical framework for a grid-connected microgrid with optimal energy management and vehicle-to-grid operation in order to guarantee its stability at the first level and its profitable operation at the second level. Energy trading with the main grid, maximizing the use of renewable energy, and managing the operation of electric vehicles and batteries are all part of the economic operation of the microgrid. Experimental verification of the performance of the proposed method is also provided. To achieve efficient energy management within residential microgrids, [PERSON] et al. [45] proposed a model that aims to minimize operating costs. This model takes into account energy trading expenses, penalties associated with adjustable load shedding, battery wear costs for electric vehicles, and a notion related to electric vehicle range anxiety. The loads considered include critical, adjustable, and shiftable categories. Range anxiety in the context of electrical vehicles is defined as the fear of running out of battery charge before reaching the intended destination. The study explores three scenarios based on risk levels within the range anxiety concept to assess the trade-off between microgrid operating costs and the average state of charge (SOC) of EV batteries. In the field of electric vehicles, EMS is mainly used to reduce energy consumption, and the only performance criterion is the gain in autonomy [46]. For the maritime sector, many studies address dedicated EMS for ships [47]. Many constraints related to the stand-alone maritime environment and the management of renewable energy are often implemented (such as the balance between energy production and demand, hardware limitations of the generators and storage systems used, voltage and frequency balance of the grid, environmental limitations, and navigation constraints). The literature on EMS for buildings primarily focuses on devices connected to an electrical grid [48]. The combination of multiple sources and loads in buildings is similar to the constraints found in stand-alone systems. However, there is limited research on stand-alone systems, particularly in the context of embedded systems. Factors such as uncertainties and risk assessment, operational flexibility and reliability, comfort level monitoring, and user behavior are not typically developed for an embedded system. As such, this paper presents an assessment of the advancements and challenges in the field of hybrid nanogrid EMS. Section 2 provides an overview of nanogrid architectures and technologies. Section 3 provides a review of different nanogrid EMS strategies based on the various solution approaches used by the authors and their main limitations. Energy storage systems are discussed in Section 4, followed by future directions.