Efficient Power Grid Management Using Sliced-Based Mechanism for Systematic Allocation of Solar Energy Resources: A Conceptual Framework - Khan, Habib Ullah; Khan, Sulaiman; Nazir, Shah (Frontiers in Energy Research, 2022)
The over-population and the limited energy resources have puzzled the government and private organizations to think about the providence of a non-stop energy resources to industries, hospitals, homes, and shopping malls to ensure normal routine activities. Some researchers put their efforts by generating energy from renewable energy resources (solar, fossil fuels, wind turbines, geothermal energy, and many others) to fulfill the needs of life. While some researchers worked on efficient utilization of the available energy resources to save the energy for future generations. Inspiring from the second approach, this research work has proposed a systematic allocation of energy resources using slice-based mechanism in smart grid environment. This research framework using a hybrid model comprises long short-term memory (LSTM), and support vector machine (SVM), where the LSTM classifies different energy requests (for allocation of energy resources) while the SVM accomplishes the statistical analysis (to estimate the amount of energy resources and time allocation). This need-based allocation of energy resources will not only assist in saving energy resources for future use, but it will also improve the life of power grid and other electric appliances (due to over-usage and burning). The applicability of this model is validated by testing it on a real-time scenario like a slice failure conditions, slice overflow conditions, huge number of requests and alternate slice allocation conditions. Furthermore, the incoming requests classification is also validate based on its accurate identification using confusion matrix, varying number of hidden layers, accuracy, and time consumption. The outperformance of the selected based on these scenarios and validation metrics reflects the applicability of this framework. Moreover, this framework will assist in reducing overbilling charges and energy savage for future generations due to its need-based allocation of energy resources assignment capabilities.