Journal of Economics and Technology in Education
JETE, Vol. 1, No. 1, 2026, pp.120-129.
Print ISSN 3105-2711; Online ISSN: 3105-272X
Journal homepage: https://www.jetejournal.com
DOI: https://doi.org/10.64058/jete260111dnpmc
Abstract: This study investigates the electricity price game problem in demand response by analyzing how real-time electricity price optimization influences both grid revenue and user demand. A Stackelberg game framework is adopted to characterize the leader–follower interaction between the grid operator and electricity users. User demand behavior is modeled using a Logistic demand response function, which captures the nonlinear relationship between price signals and load adjustment. To ensure practical applicability, grid operational constraints and electric vehicle (EV) charging constraints are incorporated through penalty terms, and the resulting constrained optimization problem is solved using the Sequential Least Squares Programming (SLSQP) algorithm. Demand elasticity coefficients, which critically affect optimization outcomes, are estimated using both historical load data and external commercial data. Comparative experiments are conducted to evaluate how different elasticity coefficients influence pricing results and load regulation performance. The results demonstrate that iterative Stackelberg-based optimization can effectively balance grid revenue and load stability, while elasticity coefficients derived from local load data yield better alignment with actual demand behavior. These findings provide theoretical and practical support for real-time electricity pricing strategies.
Keywords: Demand response; Real-time electricity pricing; Stackelberg game; Demand elasticity; Electric vehicle charging; SLSQP optimization
Author Biographies: Yin Xuanyi, undergraduate student, University of Liverpool, major in EEE, E-mail:1463485621@qq.com. Liu Run (Corresponding author), Professor of the School of Petroleum and Natural Gas Engineering, Changzhou University, Ph.D. Supervisor. Research interests: EEE. E-mail: 458011663@qq.com.
标题：面向电价机制协同优化的配电网规划方法
摘要：本研究通过分析实时电价优化如何同时影响电网收益和用户需求，研究了需求响应中的电价博弈问题。采用Stackelberg博弈框架来刻画电网运营商与电力用户之间的领导者—跟随者互动关系。用户需求行为采用Logistic需求响应函数进行建模，该函数能够描述价格信号与负荷调整之间的非线性关系。为确保研究具有实际应用价值，在模型中通过惩罚项引入了电网运行约束和电动汽车（EV）充电约束，并利用序列最小二乘规划（Sequential Least Squares Programming，SLSQP）算法求解由此形成的约束优化问题。需求弹性系数是影响优化结果的重要参数，本研究利用历史负荷数据以及外部商业数据对其进行估计。通过对比实验分析不同弹性系数对电价结果及负荷调节性能的影响。研究结果表明，基于迭代Stackelberg博弈的优化方法能够有效平衡电网收益与负荷稳定性，而基于本地负荷数据获得的弹性系数与实际需求行为具有更好的匹配度。研究结果为实时电价制定策略提供了理论依据和实践参考。
关键词：需求响应；实时电价；Stackelberg博弈模型；需求弹性系数；电动汽车充电约束；序列最小二乘规划（SLSQP）算法
作者简介：尹宣懿，本科生，利物浦大学，电气与电子工程（EEE）专业。电邮：1463485621@qq.com。刘润（通讯作者），常州大学石油与天然气工程学院教授，博士生导师。研究方向：电气与电子工程（EEE）。电邮：458011663@qq.com。
Received: 29 Jan 2026 / Revised: 20 Apr 2026 / Accepted: 25 Apr 2026 / Published online: 30 Apr 2026 / Print published: 30 May 2026.
