Optimal load forecasting and scheduling strategies for smart homes peer-to-peer energy networks: A comprehensive survey with critical simulation analysis

The home energy management (HEM) sector is going through an enormous change that includes important elements like incorporating green power, enhancing efficiency through forecasting and scheduling optimization techniques, employing smart grid infrastructure, and regulating the dynamics of optimal energy trading. As a result, ecosystem players need to clarify their roles, develop effective regulatory structures, and experiment with new business models. Peer-to-Peer (P2P) energy trading seems to be one of the viable options in these conditions, where consumers can sell/buy electricity to/from other users prior to totally depending on the utility. P2P energy trading enables the exchange of energy between consumers and prosumers, thus provide a more robust platform for energy trading. This strategy decentralizes the energy market more than it did previously, opening up new possibilities for improving energy trade between customers and utility. Considering above scenarios, this research provides an extensive insight of P2P energy trading structure, procedure, market design, trading platform, pricing mechanism, P2P approaches, forecasting techniques, scheduling topologies and possible futuristic techniques, while examining their characteristics, pros and cons with the primary goal of determining whichever approach is most appropriate in a given situation for P2P HEMs. Moreover, an optimal and robust P2P HEMs load scheduling framework simulation model is also proposed to analyze the P2P HEMs network critically, thus paving futuristic technical research directions for the scientific researchers. With this cooperation, a new age of technological advancements ushering in a more intelligent, more interconnected, and reactive urban environment are brought to life. In this sense, the path to smart living entails reinventing the urban environment as well as how people interact with and perceive their dwellings in the larger framework of a smart city. Finally, this research work also provides a comprehensive overview of technical challenges in P2P HEMs in terms of load forecasting and scheduling strategies, their possible solutions, and future prospects.