基于epsilon约束的家庭能源管理系统自调度多目标模型

M. Javadi, M. Lotfi, G. Osório, Abdelrahman Ashraf, A. E. Nezhad, M. Gough, J. Catalão
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引用次数: 33

摘要

家庭能源管理系统(HEMS)的自调度是活跃终端用户减少电费最感兴趣的问题之一。在考虑终端用户灵活性的前提下,采用需求响应方案(DRP)降低电费。该问题被视为一个多目标优化问题。第一个目标函数是最小化每天的账单,第二个目标函数是最小化关于家电插电时间的不适指数(DI)。本文采用分时电价(Time-of-Use tariff, ToU),将用户的灵活负荷从高峰时段转移到非高峰时段,从而减少用户的电费支出。在这种情况下,最终用户必须改变他们的能源消耗,这给最终用户带来了一定程度的不适。因此,本文提出了一个两阶段模型来处理上述目标函数。该模型以标准混合整数线性规划(MILP)的形式表示,并采用epsilon约束方法求解该问题。由约束多目标框架得到的Pareto前被馈送到模糊满足法中进行最终方案选择。这些结果表明,通过向用户提供最优解的帕累托集,他们更了解情况,可以做出更适合自己偏好的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Multi-Objective Model for Home Energy Management System Self-Scheduling using the Epsilon-Constraint Method
Self-scheduling of Home Energy Management Systems (HEMS) is one of the most interesting problems for active end-users to reduce their electricity bills. The electricity bill reduction by adopting Demand Response Programs (DRP) considering the flexibility of the end-users is addressed in this paper. The problem is addressed as a multi-objective optimization problem. The first objective function is the minimization of the daily bill, while the second objective aims to minimize the Discomfort Index (DI) regarding shifting the home appliances plugging-in time. The Time-of-Use (ToU) tariff is adopted in this paper and therefore, the end-users can benefit from shifting their flexible loads from peak hours to the off-peak hours and this reduces their bills, accordingly. In this case, the end-users have to change their energy consumption which imposes a level of discomfort on the end-users. Therefore, a two-stage model is proposed in this paper to deal with the mentioned objective functions. The proposed model is represented as standard mixed-integer linear programming (MILP) and for solving this problem the epsilon-constraint method is adopted in this study. The obtained Pareto front from the epsilon-constraint multi-objective framework is fed to the fuzzy satisfying method for final plan selection. These results show that by providing the Pareto set of optimal solutions to the user, they are more informed and can make decisions that better suit their preferences.
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