Day Ahead Real Time Pricing and Critical Peak Pricing Based Power Scheduling for Smart Homes with Different Duty Cycles

Energies

Adnan Ahmed¹  Nadeem Javaid¹  Mahmood Ashraf²  Sohail Iqbal³ 

[1] Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan;Department of Computer Science, Federal Urdu University of Arts, Science and Technology, Islamabad 44000, Pakistan;School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad 44000, Pakistan;

关键词: smart grid;    DSM;    HEMS;    day-ahead pricing;   

DOI  :  10.3390/en11061464

来源: DOAJ

【 摘 要 】

In this paper, we propose a demand side management (DSM) scheme in the residential area for electricity cost and peak to average ratio (PAR) alleviation with maximum users’ satisfaction. For this purpose, we implement state-of-the-art algorithms: enhanced differential evolution (EDE) and teacher learning-based optimization (TLBO). Furthermore, we propose a hybrid technique (HT) having the best features of both aforementioned algorithms. We consider a system model for single smart home as well as for a community (multiple homes) and each home consists of multiple appliances with different priorities. The priority is assigned (to each appliance) by electricity consumers and then the proposed scheme finds an optimal solution according to the assigned priorities. Day-ahead real time pricing (DA-RTP) and critical peak pricing (CPP) are used for electricity cost calculation. To validate our proposed scheme, simulations are carried out and results show that our proposed scheme efficiently achieves the aforementioned objectives. However, when we perform a comparison with existing schemes, HT outperforms other state-of-the-art schemes (TLBO and EDE) in terms of electricity cost and PAR reduction while minimizing the average waiting time.

【 授权许可】

Unknown