A Modular Framework for Optimal Load Scheduling under Price-Based Demand Response Scheme in Smart Grid

Processes

Ammar Ali¹  Noor Islam²  Khurram Saleem Alimgeer³  Ghulam Hafeez⁴  Salman Ahmad⁴  Muhammad Usman⁴ 

[1] Emerging Sciences, Peshawar 25124, Pakistan;;Department of Electrical Engineering, CECOS University of IT &Department of Electrical Engineering, University of Engineering and Technology, Mardan 23200, Pakistan;Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 44000, Pakistan;

关键词: smart grid;    demand response;    load scheduling;    home energy management;    enhanced differential evolution;    hybrid gray wolf-modified enhanced differential evolutionary algorithm;   

DOI  :  10.3390/pr7080499

来源: DOAJ

【 摘 要 】

With the emergence of the smart grid (SG), real-time interaction is favorable for both residents and power companies in optimal load scheduling to alleviate electricity cost and peaks in demand. In this paper, a modular framework is introduced for efficient load scheduling. The proposed framework is comprised of four modules: power company module, forecaster module, home energy management controller (HEMC) module, and resident module. The forecaster module receives a demand response (DR), information (real-time pricing scheme (RTPS) and critical peak pricing scheme (CPPS)), and load from the power company module to forecast pricing signals and load. The HEMC module is based on our proposed hybrid gray wolf-modified enhanced differential evolutionary (HGWmEDE) algorithm using the output of the forecaster module to schedule the household load. Each appliance of the resident module receives the schedule from the HEMC module. In a smart home, all the appliances operate according to the schedule to reduce electricity cost and peaks in demand with the affordable waiting time. The simulation results validated that the proposed framework handled the uncertainties in load and supply and provided optimal load scheduling, which facilitates both residents and power companies.

【 授权许可】

Unknown