A Survey on the Influence of Blockchain and Neural Network Technologies on Smart Grid Systems

Energy transactions benefit from blockchain technology because it creates an independent system that provides secure data protocols and protects against unauthorised alterations of information while strengthening protection. Multipurpose blockchain tools let traders conduct secure peer-to-peer energy exchanges, and they can run automated networks while diminishing dependence on central control systems. Small and distributed energy control methods decrease infrastructure vulnerability by shielding it from cyber threats while creating a tamperproof network, which builds modern energy security and visibility. Organisations use advanced machine learning algorithms to study historical and real-time data to optimise energy distribution, identify consumption patterns, and detect anomalies. The predictive models enable better decision-making through preventive maintenance plans, reduced energy losses, and optimised distribution of electricity loads in the grid system. The research investigates detailed implementations of predictive models that unite neural networks and blockchain technology into a system that builds up smart grid functions. These technologies form a synergistic relationship that enables smart automation systems along with continuous real-time monitoring and boosted operational efficiency. The study investigates actual blockchain-based energy market examples alongside case studies on predictive maintenance carried out through AI and decentralised power trading platforms. The research results show that integrating blockchain with neural networks can enhance smart grid security and reliability while also supporting the development of a sustainable and adaptable energy system. Through their resolution of scalability problems and regulatory requirements as well as computational limits, these technologies establish future frameworks for smart power networks of the next generation. The survey findings create a basis for researchers to use for advancing energy informatics and smart grid innovation in the future.