A review of IoT enabled intelligent smart energy management for photovoltaic power forecasting and generation

Renewable energy has emerged as one of the most reliable and widely accepted approaches to address the rising global energy requirements. Among these, solar power development requires focused attention on both maintenance strategies and application methods. To enhance solar energy utilization, Internet of Things (IoT)-enabled monitoring frameworks have been designed, allowing real-time collection and analysis of solar parameters for predicting efficiency and ensuring stable electricity generation. A major concern in demand-side energy regulation lies in utilizing renewable sources effectively while keeping costs manageable and minimizing unnecessary consumption. Hence, careful planning of renewable resource integration is essential. Advanced energy management platforms play a crucial role in supervising energy distribution, especially in scenarios where heavy dependence on the grid exists. The complexities and opportunities introduced by expanding grid networks can be efficiently managed through cloud-based technologies. This work emphasizes the practical application of energy management systems in both industrial operations and academic research, treating them as key stakeholders in the energy sector. The investigation offers a detailed evaluation of IoT applications in photovoltaic power systems and highlights the promising future avenues available to researchers. These include developing new benchmarks to measure IoT performance and refining existing systems through innovative approaches. Furthermore, there is an increasing demand for comprehensive studies on intelligent energy frameworks in smart infrastructures. Such research is critical to advancing IoT-driven applications and sustaining continuous progress in this domain. • An integrated operational mechanism is needed in the energy sector to balance power supply and demand effectively. • Smart Energy Management Systems with low cost, high efficiency, and reliable power-negotiation algorithms are essential. • A smart grid initiative with an IoT-based energy management framework is required to monitor consumer-level usage. • Optimization methods must be assessed to identify cost-effective and computationally efficient demand-side solutions. • Accurate power generation forecasting is required to enable proper scheduling and efficient energy management.