Survey on Load Forecasting in Smart Grid

  • Pushpa, Sanjeev Indora
Keywords: Smart Grid, Load Forecasting, Energy Management, Machine Learning


Every country economic growth is directly linked to its electricity system, network and accessibility, even though electricity became the essential part of daily life in this modern world. The global electricity consumption for residential and business purposes has therefore seen an immense increase. On the other hand, electricity prices have continued to fluctuate over the last few years, not to mention the inadequacy of electricity generation to reach global demand. As a solution to this, various studies targeted at forecasting future demand for electrical energy for residential purposes will allow electricity generators, distributors and suppliers to make plans effectively and encourage energy conservation among customers. The smart grid is a grid that is consistent, convenient, and versatile. Electricity is empowered by an instantaneous two-way supply of energy information. To enable consumers to have more control over energy outcomes, the energy industry must successfully manage energy supply and transmission. However, since the beginning of electricity generation, load forecasting has been one of the key issues facing the energy business

How to Cite
Pushpa, Sanjeev Indora. (2022). Survey on Load Forecasting in Smart Grid. Design Engineering, (1), 1124-1133. Retrieved from