Evaluation of Optimization Algorithms for Customers Load Schedule
Diaba, Sayawu Yakubu; Elmusrati, Mohammed; Shafie-khah, Miadreza (2021)
Diaba, Sayawu Yakubu
Elmusrati, Mohammed
Shafie-khah, Miadreza
Editori(t)
Ao, S. I.
Castillo, Oscar
Douglas, Craig
Feng, David Dagan
International Association of Engineers (IAENG) Newswood Limited
2021
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022032925901
https://urn.fi/URN:NBN:fi-fe2022032925901
Kuvaus
vertaisarvioitu
©2021 International Association of Engineers (IAENG).
©2021 International Association of Engineers (IAENG).
Tiivistelmä
This paper introduces a novel concept for customer load scheduling in the Smart Grid (SG). The concept is based on the forthcoming internet of things (IoT). Approximate optimization algorithms are deduced for optimum customer load scheduling, maximization of electric power suppliers performance, and fairness in scheduling customers load. Using these approximate optimization algorithms as constraints, some loads are given priority. Other loads are scheduled in order to control the maximum demand load and electricity bills. To evaluate the effectiveness of the algorithms, we utilize the Mixed Integer Linear Programming (MILP). Simulations are carried out and the impact on reducing the peak-to-average power ratio (PAPR), the electricity bills, and ensuring fairness in customers load schedules are investigated. Simulation results establish that our algorithms significantly cut down on electricity bills, maximizes utility performance, and deliver fairness in customers load schedules.
Kokoelmat
- Artikkelit [2615]