## 6 Future Directions
* Blockchain: In a smart grid environment, plenty of problems emerge that are related to the security of the distributed data in various sections of smart grids. The data management of a centralized server-based storage system can cut the cost but sacrifice the security and privacy of protecting the ledger (system data) [114]. This can be mitigated by the use of blockchain distributed ledger technology, where data can travel from one node to the other in a secure way. Integrity, transparency, provenance, and trustworthiness can be achieved by blockchain Hyperledger-enabled modular infrastructure through continuously simulating distributed node transactions, including energy-related data management logs. Additionally, blockchain technology is also useful for authentication issues, while the development of a blockchain platform for smart grids and microgrids can be a significant contribution in commercialization. In general, smart grids can benefit from the use of blockchain and distributed ledger technologies for secure and transparent data management. These technologies can be used for data integrity verification, secure transaction recording, and identity management within the smart grid system [115]. Blockchain is a powerful technology that can greatly improve smart grids' resistance to cyberattacks. By offering decentralized, unchangeable ledgers for data transactions, blockchain can safeguard smart grids. This ensures the integrity of control systems by making it harder for attackers to change or modify grid data. From the perspective of authentication and access control, blockchain makes it possible for safe, transparent authentication procedures to be enacted, which guarantee that only authorized individuals and devices may access grid systems, lowering the possibility of unauthorized access. Blockchain's distributed ledgers minimize the possibility of a single point of failure. The grid keeps working even if one node is compromised or attacked since the other nodes keep operating [116; 117]. * Artificial Intelligence-Enabled Machine Learning: AI-enabled machine learning (ML) approaches, such as supervised, semi-supervised, and unsupervised learning, can be used to analyze the lack of efficiency and reliability in smart grids. By enabling ML developments and tailoring operational executions and reactions to needs, it will be possible to broaden the scope of the dynamic monitoring and controlling of smart grid technologies. Furthermore, the combination of artificial intelligence and power distribution technology establishes an entirely novel approach for the development of the real-time generation, control, distribution, and monitoring of electric power supplies. Machine learning can also be efficient in smart grid automated vulnerability assessments, gathering threat intelligence and predicting threats and risks. In addition, machine learning and artificial intelligence can be used in real time to detect and mitigate security issues. Integrating AI-powered security solutions with cryptographic approaches may become a smart grid security trend [107]. AI is a potent instrument that can greatly improve smart grid security against cyberattacks. Artificial intelligence (AI) can monitor and analyze enormous volumes of grid data in real time in anomaly detection, spotting odd patterns that can point to possible vulnerabilities or cyberattacks. By detecting new threats and vulnerabilities, machine learning algorithms may anticipate and proactively reduce cyber risks from the standpoint of predictive threat modeling, enabling quicker incident reaction times. Intrusion detection systems with AI capabilities are able to continuously scan the grid for suspicious activity. For example, AI systems can promptly identify and notify security teams if an intruder modifies power flow data in an attempt to interfere with operations.