Operational Scheduling of Household Appliances by Using Triple-Objective Optimization Algorithm Integrated with Multi-Criteria Decision Making

Dhiaa Halboot Muhsen (), Haider Tarish Haider, Yaarob Al-Nidawi and Ghadeer Ghazi Shayea
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Dhiaa Halboot Muhsen: Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq
Haider Tarish Haider: Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq
Yaarob Al-Nidawi: 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

Sustainability, 2023, vol. 15, issue 24, 1-24

Abstract: Load scheduling is a key factor in demand side management (DSM), which manages available generation capacity with regard to the required demand. In this paper, a triple-objective load scheduling optimization problem (LSOP) is formulated for achieving optimal cost and peak demand as well as minimum customer inconvenience. A Henry gas solubility optimization (HGSO) algorithm that is based on multi-objective is used for solving LSOP. The proposed HGSO offers a set of compromise solutions that represent the tradeoff between the three objectives of the formulated problem. A set of all compromise solutions from the dominant Pareto front is achieved first, and then ranked by using MCDM so as to optimally sort these solutions. An entropy weighting method (EWM) is then used for computing the weights of various criteria that dominate the LSOP and is provided as a technique for ordering preferences by similarity to achieve the ideal solution (TOPSIS) so as to rank the sorted solutions. Two types of end-users are considered so as to show the effectiveness of the proposed LSOP: non-cooperative and cooperative users. The results of the proposed load scheduling method show the significance of the proposed method for both the cooperative and non-cooperative end-users. The proposed method achieves a cost of energy of R50.62 as a total cost of energy consumed by four non-cooperative end-users. The cost of energy for the cooperative end-users is found to be R47.39. Thus, saving in the energy cost unit is found to be around 5.5% by using the proposed method; moreover, the peak demand value is reduced by 9.7% when non-cooperative end-users becomes cooperative.

Keywords: load management; demand response; smart grid; multi-objective optimization; entropy weighting method; HGSO; TOPSIS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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