The production of energy from water represents large amounts of clean and renewable energy. However, only 30% of this energy has been developed so far. Hydropower, particularly hydropower plants, is not only environmentally friendly but also economical, and operates more efficiently than any other renewable energy system. Hydropower plants are largely automated and have relatively low operating costs. The main components of the power system must be continuously monitored and protected to maintain the quality and reliability of the power source. This task is provided by the data collection, monitoring and protection system. Turbines must be protected not only by short circuits but also by abnormal conditions. The proposed protection has been designed to avoid damaging the original power (motor or turbine), this usually happens when the generator fails, and the machine operates as a synchronous motor connected to the power system. In this case, the generator becomes an active load, causing a rise in temperature and severe damage to the main turbine, and hence it becomes a need to quickly detect these conditions. This study proposes a new controller for Neuro-Fuzzy to prevent reverse power flow and to keep the quality and reliability of supply. Fuzzy system network has attracted various scientific and engineering researchers. The new feature of this work is to adjust the membership function as a reverse mechanism derived of the Fuzzy Logic Controller. The smart meter network is the basis of the smart grid. In this study, smart grid meters were implemented using ZigBee technology based on wireless sensor networks. The ZigBee network of wireless sensors due to its low battery, low power consumption, become more useful than other wireless communication systems to provide a high-performance measurement. This study shows the ZigBee network using the OPNET simulation. Depending on the performance, parameters were analysed to understand the operating characteristics of the star, tree, and mesh.Although neural networks implement to solve tuning problems, the fuzzy logic controller is intended to use structured knowledge in the form of rules [4,5].The combination of Fuzzy Logic and neural networks provides the ability to solve optimisation problems. This new method consolidates the established advantages of both approaches and avoids the limitations of both approaches. Control algorithms are used to prevent unexpected fluctuations in voltage and frequency. Smart grids use energy storage systems and communication networks to ensure total coordination between power generation and energy use. Reduce the energy loss of the network to minimise demand and energy costs [6][7][8]. A reliable, real-time information flow among parts of the network is critical to the success of the smart grid self-regulation process. There are many wireless standards for technical applications [9]. One of the most popular technologies is ZigBee wireless sensor network (WSN), which is distributed on the smart grid structure, which has a lot of equipment...