2021/10/14 by Farhat Iqbal, Shafiq Ur Rehman, Iqbal, Farhat +4
Engineering · #Electric Power System Optimization #FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE) #Optimal Power Flow Distribution #Smart Grid Energy Management
paper · pdf · doi:10.48550/arxiv.2111.14634
openalex publication_date 2021/10/14 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Stability and protection of the electrical power systems are always of primary concern. Stability can be affected mostly by increase in the load demand. Power grids are overloaded in peak hours so more power generation units are required to cope the demand. Increase in power generation is not an optimal solution. With the enlargement in Smart grid (SG), it becomes easier to correlate the consumer demand and available power. The most significant featutre of smart grid is demand response (DR) which is used to match the demand of available electrical energy and shift the peak load into off peak hours to improve the economics of energy and stability of grid stations. Presently we used Genetic algorithm (GA) to schedule the load via real time pricing signal (RTP). Load is categorized depending on their energy requirement, operational constraint and duty cycle. We conclude that GA provides optimal solution for scheduling of house hold appliances by curtailing overall utilized energy cost and peak to average ratio hence improving the load profile.