Citation

Ahmed, Rasel and Tan, Wooi Nee and Gan, Ming Tao and Yip, Sook Chin (2025) Two-Stage Load Scheduling Optimization for Balancing Demand-Side and Supply-Side Objectives. In: Conference Proceedings - 2025 IEEE International Conference on Environment and Electrical Engineering and 2025 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2025, 15 July 2025 - 18 July 2025, Chania, Crete.

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Abstract

Load scheduling problem which shifts residential appliances from peak to off-peak periods to improve grid efficiency, typically uses an objective function in the optimization model that aims to minimize electricity costs as an incentive to encourage users' participation. The optimization often prioritizes the users' perspectives while neglecting the needs of utility providers in maximizing the peak-to-average ratio or minimizing the peak load. The proposed joint demand-supply optimization model aims to incorporate the objectives of both conflicting parties to achieve a compromised solution that satisfies the demand-side interest in lower electricity costs while also meeting the supply-side objective of reducing peak load. This is achieved by introducing a balancing weight in the objective function, which represents the weightage assigned to each party during the optimization process. Simulation results of various scenarios demonstrate that the proposed model successfully produces the optimal residential appliances schedules that lies between the minimum electricity costs (from the users' perspective) and the minimum peak load (from the utility provider's perspective). The proposed model successfully provides balanced solutions that pave the possibility for implementation in Demand-Side Management.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Cost minimization, demand-side management, joint demand-supply optimization, linear programming, load scheduling, peak load minimization
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Nurin Syazwani Azmi
Date Deposited:	07 Nov 2025 06:47
Last Modified:	07 Nov 2025 06:47
URII:	http://shdl.mmu.edu.my/id/eprint/14775

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