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Renewable energy represents the most reliable and widely recognized solution for meeting the escalating global energy demands. The optimization of solar energy generation necessitates a strong focus on predictive maintenance and advanced deployment methodologies. To enhance solar power utilization, Internet of Things enabled solar monitoring systems have been proposed for real-time data acquisition and analytics, facilitating performance forecasting and ensuring consistent power output. A critical challenge in demand-side energy management lies in optimizing the integration of renewable resources while maintaining cost efficiency and minimizing energy losses. Therefore, strategic planning for the integration of renewable energy sources is imperative. Intelligent energy management systems play a pivotal role in optimizing energy distribution, particularly in scenarios with high grid dependency. Cloud computing infrastructures address the complexities and scalability challenges posed by expanding smart grids, enabling real-time data processing and adaptive energy control mechanisms. This study explores the practical implementation of energy management system in industrial settings and research domains, both of which serve as key stakeholders in advancing smart energy solutions. A comprehensive review of internet of things applications in photovoltaic power generation highlights key research objectives and technological developments in the field. The evolving landscape of internet of things driven innovations presents numerous research opportunities, including the formulation of performance evaluation metrics and the development of novel optimization techniques. Additionally, the growing emphasis on energy management within intelligent architectural frameworks underscores the necessity for deeper investigations into adaptive control strategies and system interoperability. This ongoing research is essential for driving advancements in internet of things enabled energy solutions and enhancing the efficiency of smart grid ecosystems. • In the energy sector, there is a need for an integrated co-operative operational mechanism taking into account of power supply and demand entity to reduce the mismatch. • The power management operational task seeks for the development of inexpensive and efficient Smart Energy Management System (SEMS). Further, deployment of power negotiating algorithms with reliable communication capability is essential to reduce the overall power consumption and hence, minimize the electricity cost. • A comprehensive initiative in smart grid is essential, which includes energy management framework associated with an IoT environment that monitors and visualizes power consumption at the consumer premises. • Optimization techniques are to be evaluated to find the cost effective and computationally efficient approach for the given demand side consumer constraints. • Accurate prediction of power generation or power availability is required for Proper scheduling mechanism.
Rao et al. (Fri,) studied this question.