A new home energy management algorithm with voltage control in a smart home environment

Elma, Onur; Selamoğulları, Ugur Savaş

doi:10.1016/j.energy.2015.08.094

Cited by 57 publications

(16 citation statements)

References 20 publications

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“…Appliances are classified based on the priority given by users to each load regardless of the day of the week and the time of the day in which are used. In [16], an algorithm for Distributed Energy Resources (DER) is proposed to reduce power consumption and minimize appliances execution shifts and turn off actions based on the priority class they belong to. Consequently, customer comfort is evaluated as the minimization of appliances turn-off operations, but no profiling is considered for different user types.…”

Section: Related Workmentioning

confidence: 99%

Smart Home Energy Management Including Renewable Sources: A QoE-driven Approach

Pilloni

Floris

Meloni

et al. 2016

IEEE Trans. Smart Grid

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Smart Home Energy Management (SHEM) systems can introduce adjustments in the working period and operations of home appliances to allow for energy cost savings, which can however affect the Quality of Experience (QoE) perceived by the user. This paper analyses this issue and proposes a QoEaware SHEM system, which relies on the knowledge of the annoyance suffered by users when the operations of appliances are changed with respect to the ideal user's preferences. Accordingly, a number of profiles describing different usages are created in the design phase. At the deployment stage, users behavior and annoyance are registered to assign one of these profiles per appliance. The assigned profile is then exploited by the QoE-aware Cost Saving Appliance Scheduling and the QoE-aware Renewable Source Power Allocation algorithms. The former is aimed at scheduling controlled loads based on users profile preferences and electricity prices. The latter reallocates appliances' operations whenever a surplus of energy is available by Renewable Energy Sources (RES). Experimental results demonstrate that the annoyance perceived by users is severely diminished with respect to a QoE-unaware strategy, at the expenses of only a limited reduction in energy saving.

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Section: Related Workmentioning

confidence: 99%

Smart Home Energy Management Including Renewable Sources: A QoE-driven Approach

Pilloni

Floris

Meloni

et al. 2016

IEEE Trans. Smart Grid

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“…For example, the research in [17] has shown a 20% reduction in household consumption by controlling voltage of appliances. Two different voltage control modes have been analyzed.…”

Section: Reduction Of Electricity Billsmentioning

confidence: 99%

“…Most recent studies, such as [17] and [18], have determined that one of the main objectives is to reduce energy costs for residential users. By optimizing the price and consumption profile in real time, or intervals of 5, 10 or 15 minutes, a reduction of the impacts produced by the charge of EVs at home is achieved.…”

Section: Reduction Of Electricity Billsmentioning

confidence: 99%

Home energy management systems and electric vehicles: challenges and opportunities

Junquera¹,

García-Villalobos²,

Zamora³

et al. 2017

REPQJ

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Abstract. Currently, residential users consume more electric energy during peak hours, mainly between 15h and 22h when the electricity prices are normally higher. Additionally, electric vehicle (EV) users tend to charge their vehicles at the same hours, increasing the impact on residential distribution networks. As a solution to these problems, a home energy management system (HEMS) can be used to decrease household energy demand at peak hours and reduce the impact of charging EVs in residential distribution networks. Additionally, HEMS can manage renewable energy sources and energy storage systems (ESS) to charge EVs in an efficient way.The aim of this paper is to analyse the different aspects and concepts related to home energy usage and residential charging of EVs, as well as presenting the challenges and opportunities of HEMS together with vehicle-to-home (V2H) concept. Key wordsHome energy management systems vehicle to home, electric vehicle, demand response, electric appliance.

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“…In [31], a bi-level optimization problem was formulated to quantify the impact of demand response (DR) from a HEMS on the voltage profile. A HEMS algorithm based on voltage control was proposed to maximize consumers' comfort level by controlling household passive loads [32]. In [33], considering voltage-dependent load models, demand response mismatch (DRM) (i.e., an active power mismatch between the scheduled and actually achieved DR) was introduced, and the MINLP optimization problem was formulated to minimize the DRM.…”

Section: Introductionmentioning

confidence: 99%

Smart Home Energy Management in Unbalanced Active Distribution Networks Considering Reactive Power Dispatch and Voltage Control

Mak

Choi

2019

IEEE Access

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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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A new home energy management algorithm with voltage control in a smart home environment

Cited by 57 publications

References 20 publications

Smart Home Energy Management Including Renewable Sources: A QoE-driven Approach

Smart Home Energy Management Including Renewable Sources: A QoE-driven Approach

Home energy management systems and electric vehicles: challenges and opportunities

Smart Home Energy Management in Unbalanced Active Distribution Networks Considering Reactive Power Dispatch and Voltage Control

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