مدیریت انرژی خانه هوشمند
Abstract
I. Introduction
II. Preliminaries
III. Proposed Home Energy Management Optimization Framework
IV. Numerical Examples
V. Conclusion
Authors
Figures
References
Abstract
This paper presents a new optimization algorithm for home energy management systems (HEMSs) in three-phase unbalanced low-voltage (LV) distribution networks. Compared with conventional HEMS optimization methods, which consider only the active power consumption scheduling for smart home appliances and distributed energy resources (DERs) (e.g., solar photovoltaic (PV) systems and energy storage systems (ESSs)), the novelty of the proposed approach is to consider: i) both active and reactive power consumption schedulings of home appliances and DERs, ii) realistic three-phase unbalanced LV distribution networks with voltage-dependent load models, and iii) voltage control using an on-load tap changer transformer and smart inverters of PV system and ESS at the households. The proposed HEMS optimization algorithm, which is formulated using mixed-integer linear programming, is tested in the modified CIGRE LV distribution network. Numerical examples demonstrate the performance of the proposed algorithm in terms of active/reactive power consumption, three-phase voltage magnitudes, and the total cost of electricity.
Introduction
As residential households consume approximately one third of the total electricity consumption [1], home energy management systems (HEMSs) have become an indispensable technology for the efficient and economical management of residential energy usage. The primary goal of the conventional HEMS is to reduce consumers’ electricity costs in their comfortable and preferred environments by scheduling the optimal energy consumption of smart household appliances (e.g., air conditioners and washing machines). Recently, emerging smart grid technologies including distributed energy resources (DERs) (e.g., rooftop solar photovoltaic (PV) and energy storage system (ESS)), advanced metering infrastructure with smart meters, and demand side management have enabled consumers to achieve more energy saving through the HEMSs equipped with these smart grid technologies [2]. A core technology for the conventional HEMS is the optimization method employed to conduct an economic load reduction and load shifting of smart household appliances in addition to the operation scheduling of the DERs (e.g., charge/discharge of the ESSs). However, the conventional HEMS optimization algorithm may calculate the incorrect and undesired energy consumption schedules for smart households due to the the following limitations. First, only the scheduling of active power consumption of household appliances and active power injection/absorption of the DERs is considered excluding reactive power consumption of appliances along with reactive power capability of the DERs.