Regular Article

Modelling demand response in smart microgrid with techno and economic objective functions and improvement of network efficiency

¹ College of Mechanical and Electrical Engineering, Jiaxing Nanhu University, Jiaxing City, Zhejiang Province, 314000, China
² Beijing Institute of Technology, Zhuhai City, Guangdong Province, 519088, China
³ College of Information Engineering, Jiaxing Nanhu University, Jiaxing City, Zhejiang Province, 314000, China
⁴ Energy Systems Department, Ajman University, Ajman, United Arab Emirates

^* Corresponding author: karen6886@163.com

Received: 17 July 2024
Accepted: 16 September 2024

Abstract

This study introduces Incentive-Based Demand Response (IBDR) strategies aimed at reducing load. The initial strategy utilizes a price elasticity matrix, focusing on providing financial incentives to customers who reduce their energy consumption specifically during peak hours. The second IBDR policy is an optimization-based approach that involves customer willingness to deliver economic benefit both to themselves as well as the DIStribution COmpany (DISCO). The final restructured load demand is the base load demand minus the load curtailed by both the IBDR policies. Henceforth, generation cost minimization is percolated on the MG system for all three load models. Three case studies are performed for an exhaustive techno-economic analysis of the subject MG system. The study uses the recently created quick and easy Circle Search Algorithm (CSA) as its optimization tool. The generation cost was decreased from $25463 to $24969 and $24899 using IBDR1 and IBDR2 policies of load curtailment respectively. During IBDR1 80kW load was curtailed and the customers gained an incentive of $277 whereas using IBDR2 policy, 105kW of load was curtailed and the DISCO benefitted $211. The consumers also benefitted $500 in the process. Numerical results also show that CSA outperformed various optimization algorithms from the literature and ample algorithms implemented in the work. Central tendency measurements further support the reliability and effectiveness of CSA.