Multi-User Optimal Load Scheduling of Different Objectives Combined with Multi-Criteria Decision Making for Smart Grid

Yaarob Al-Nidawi (), Haider Tarish Haider, Dhiaa Halboot Muhsen and Ghadeer Ghazi Shayea
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Yaarob Al-Nidawi: Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq
Haider Tarish Haider: Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq
Dhiaa Halboot Muhsen: Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq
Ghadeer Ghazi Shayea: College of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10001, Iraq

Future Internet, 2024, vol. 16, issue 10, 1-23

Abstract: Load balancing between required power demand and the available generation capacity is the main task of demand response for a smart grid. Matching between the objectives of users and utilities is the main gap that should be addressed in the demand response context. In this paper, a multi-user optimal load scheduling is proposed to benefit both utility companies and users. Different objectives are considered to form a multi-objective artificial hummingbird algorithm (MAHA). The cost of energy consumption, peak of load, and user inconvenience are the main objectives considered in this work. A hybrid multi-criteria decision making method is considered to select the dominance solutions. This approach is based on the removal effects of criteria (MERECs) and is utilized for deriving appropriate weights of various criteria. Next, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method is used to find the best solution of load scheduling from a set of Pareto front solutions produced by MAHA. Multiple pricing schemes are applied in this work, namely the time of use (ToU) and adaptive consumption level pricing scheme (ACLPS), to test the proposed system with regards to different pricing rates. Furthermore, non-cooperative and cooperative users’ working schemes are considered to overcome the issue of making a new peak load time through shifting the user load from the peak to off-peak period to realize minimum energy cost. The results demonstrate 81% cost savings for the proposed method with the cooperative mode while using ACLPS and 40% savings regarding ToU. Furthermore, the peak saving for the same mode of operation provides about 68% and 64% for ACLPs and ToU, respectively. The finding of this work has been validated against other related contributions to examine the significance of the proposed technique. The analyses in this research have concluded that the presented approach has realized a remarkable saving for the peak power intervals and energy cost while maintaining an acceptable range of the customer inconvenience level.

Keywords: MEREC; load scheduling; smart grid; demand response; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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