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Technical and economic analysis of home energy management system incorporating small-scale wind turbine and battery energy storage system

机译:结合小型风力发电机和电池储能系统的家庭能源管理系统的技术经济分析

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Home energy management system (HEMS) is an important problem that has been attracting significant attentions in the recent years. However, the conventional HEMS includes several shortcomings. The conventional HEMSs mainly utilize battery energy storage system (BESS) to deal with energy uncertainties. But they only ascertain optimal charging-discharging pattern for BESS and the power and capacity of BESS are not optimally determined. Furthermore, most of the HEMSs are modeled as a mixed integer linear programming (MILP) including linearization and relaxations. Additionally, considering all possible operating conditions for home has not been adequately addressed in the existing HEMSs. The possible operating conditions are (i) receiving energy from the main grid (i.e., purchasing energy), (ii) sending energy to the utility grid (i.e., selling energy), (iii) working on standalone mode as disconnected from the network (i.e., net-zero energy building). As a result, current paper deals with these existing challenges at the same time. This paper presents HEMS including small-scale wind turbine, BESS, load curtailment option, and fuel cell vehicle. The introduced HEMS not only determines optimal charging discharging pattern for BESS, but also specifies optimal capacity and optimal rated power of the BESS at the same time. The proposed HEMS is expressed as a mixed integer nonlinear programming (MINLP) and solved by cultural algorithm as an effective Meta-heuristic optimization algorithm. All three operating conditions are considered for home. Output power of wind unit is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to deal with uncertainties. Results emphasize on the feasibility and usefulness of the introduced HEMS. (C) 2017 Elsevier Ltd. All rights reserved.
机译:家庭能源管理系统(HEMS)是一个重要的问题,近年来已引起人们的极大关注。然而,传统的HEMS包括一些缺点。传统的HEMS主要利用电池能量存储系统(BESS)来处理能量不确定性。但是,它们仅确定用于BESS的最佳充放电模式,而不能最佳地确定BESS的功率和容量。此外,大多数HEMS被建模为包括线性化和松弛的混合整数线性规划(MILP)。另外,在现有的HEMS中没有充分考虑到考虑家庭的所有可能的操作条件。可能的操作条件是(i)从主电网接收能量(即购买能源),(ii)向公用电网发送能量(即出售能源),(iii)在与网络断开连接的情况下以独立模式工作(即净零能耗建筑)。结果,当前的论文同时解决了这些现有挑战。本文介绍了HEMS,包括小型风力涡轮机,BESS,减载选项和燃料电池汽车。引入的HEMS不仅可以确定BESS的最佳充电放电模式,而且可以同时指定BESS的最佳容量和最佳额定功率。提出的HEMS表示为混合整数非线性规划(MINLP),并通过文化算法求解,作为有效的元启发式优化算法。所有三个工作条件都考虑在家中使用。利用高斯概率分布函数(PDF)对风力发电机组的输出功率进行建模,并应用蒙特卡洛模拟(MCS)来处理不确定性。结果强调了引入的HEMS的可行性和实用性。 (C)2017 Elsevier Ltd.保留所有权利。

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