Thermometer approach-based energy distribution with fine calibration in a smart grid tree network

For the benefit of mankind, future technologies should be eco-friendly, eschew CO2, be capable of smart energy generation using renewable energy sources and be effective in raising the energy efficiency of individual users. This leads to the optimization of energy generation, distribution and utility at the user level, which helps in handling demand-side management (DSM) of the smart grid effectively. The energy distribution flow in a smart grid can be modeled as a smart grid tree network (SGTN). To promote the requirement of secondary energy generation using renewable energy sources at the customer level, secondary energy generated by the customer with a load demand is included in order to calculate the energy demand on the smart grid. Depending on the load request and demand, the energy is granted for various levels of child nodes in an SGTN using load weight (LW) and demand. In this paper, thermometer approach-based energy distribution with a load (TAEDL) is proposed in order to derive energy efficiency at various levels of the SGTN. The proposed technique is refined to attain maximum energy distribution efficiency and fairness using a thermometer approach with fine calibration (FC). The total energy distributed to the users, the number of satisfied users, the energy distribution efficiency, and the fairness index (FI) of the SGTN are evaluated at various levels. The simulation results show that the suggested technique outperforms in terms of energy distribution with fairness and initiates a revolutionary change in future smart grid technology. (C) 2018 Elsevier Ltd. All rights reserved.