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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. INDEX TERMS Home energy management, smart household appliance, three-phase unbalanced distribution system, reactive power dispatch, voltage control, voltage dependent load.

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This paper proposes a hierarchical look-ahead framework to conduct conservation voltage reduction (CVR) when distributed energy resources such as solar photovoltaic (PV) systems and energy storage systems (ESSs), and demand response programs are integrated into distribution systems. With the increasing deployment of PV systems in distribution systems, their frequently varying power output due to cloud movements could have a detrimental impact on the consumer's voltage quality, consequently leading to degraded CVR performance. A two-level CVR framework for the coordination of an on-load tap changer (OLTC), capacitor banks (CBs), and the smart inverters of PV systems/ESSs is presented, in which these elements operate to reduce the voltage profile along the distribution feeder at different temporal scales. At the global level, the operations of the OLTC and the CBs are scheduled every hour to achieve the best CVR performance in an optimization problem using mixed-integer linear programming. When voltage violations occur rapidly, the smart inverters of PV systems and ESSs help to maintain a lower voltage profile every second based on the proposed piecewise droop control functions at the local level. A simulation study is carried out in an IEEE 33-bus distribution system with an OLTC, CBs, PV systems, and ESSs, and our results demonstrate the advantages of the proposed approach in terms of voltage level and energy savings. Furthermore, the impact of demand reduction on the proposed approach is quantified, and we verify that a higher demand reduction yields more energy savings in the proposed framework.