A Survey on Home Energy Management <s> I. INTRODUCTION <s> Abstract This paper proposes a review of the scientific literature on electric load management (ELM). Relevant topics include the smart grid, demand-side management, demand-response methods, and peak load reduction. The evaluation is performed by a systematic literature review (SLR) and an evaluation of the recent advances in the state of the art. The analysis is based on the classification of 200+ papers, considering the covered topics/problems, assumptions, constraints, and the proposed methods. Statistical results show a growing interest in ELM in the last few years, and a fast obsolescence of older results. A lack of common benchmarking frameworks has been detected. <s> BIB001 </s> A Survey on Home Energy Management <s> I. INTRODUCTION <s> Abstract This paper classifies and discusses the energy flexibility improvement strategies for demand responsive control in grid-interactive buildings based on a comprehensive study of the literature. Both supply and demand sides are considered. The flexibility measures range from renewable energy such as photovoltaic cells (PV) and wind to heating, ventilation, and air conditioning (HVAC) systems, energy storage, building thermal mass, appliances, and occupant behaviors. Currently, owing to the highly developed smart appliances and sensing communication techniques, DR is considered as an essential measure for improving energy flexibility in buildings without much additional investment. With the help of advanced demand response (DR) control strategies and measures, buildings can become more flexible in terms of power demand from the power grid. In this way, buildings achieve a better ability to balance differences in energy supply and demand. Furthermore, a synergistic approach with various measures is advisable, e.g., the use of energy storage technologies with PV and passive DR methods. This paper summarizes the measures for improving the flexibility of commercial and residential buildings, and develops a systematic methodology framework to evaluate energy demand flexibility in buildings. <s> BIB002 </s> A Survey on Home Energy Management <s> I. INTRODUCTION <s> Abstract This paper discusses an experimental study of the home appliances scheduling problem that incorporates realistic aspects. The residential load scheduling problem is solved while considering consumer’s preferences. The objective function minimizes the weighted sum of electricity cost by earning relevant incentives, and the scheduling inconvenience. The objective of this study is five-fold. First, it sought to develop and solve a binary integer linear programming optimization model for the problem. Second, it examined the factors that might affect the obtained schedule of residential loads. Third, it aimed to test the performance of a developed optimization model under different experimental scenarios. Fourth, it proposes a conceptual definition of a new parameter in the problem, the so-called “flexibility ratio”. Finally, it adds a data set for use in the literature on the home appliance scheduling problem, which can be used to test the performance of newly-developed approaches to the solution of this problem. This paper presents the results of experimental analysis using four factors: problem size, flexibility ratio, time slot length and the objective function weighting factor. The experimental results show the main and interaction effects, where these exist, on three performance measures: the electricity cost, inconvenience and the optimization model computation time. <s> BIB003
Energy is an essential resource to life and all living organisms. In current days, electrical energy plays a vital role in human lifestyle, powering key infrastructures and services. Fossil fuels still account for the production of the majority of worldwide consumed electricity. According to the United States Energy Information Administration  , in 2018, fossil fuels ensured 62% of primary electricity production in the United States. Unlike clean and renewable alternative sources such as wind or solar, fossil-fuel exploitation has a strong environmental impact as a result of green house gas (GHG) emissions, global warming and health hazards. In addition, its current consumption surpasses natural regeneration, resulting in an inevitable depletion of resources, if other sources or options are not exploited. The associate editor coordinating the review of this manuscript and approving it for publication was Ayaz Ahmad . These concerns have fostered not only the search for alternative, renewable and clean energy sources, but also the awareness regarding energy efficiency and sustainability. In the last few years, the traditional power grid has been reshaped into an intelligent, highly reliable and fully automated infrastructure, paving the way to the so-called ''smart'' grid paradigm. This new power grid model supports the deployment and integration of distributed generation and storage resources, namely of renewable nature. It relies heavily on smart appliances and two-way communication channels linking the utility and consumers. This makes possible realtime coordination and dynamic optimisation of grid operation and resources  . At demand-side, smart homes incorporate digital sensing and communication devices, which allow for continuous consumption monitoring, intelligent appliance control and communication with the utility and grid. Smart homes are a key element to the operation and effectiveness of smart VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ grids, not only by supporting optimised management to grid resources and infrastructures, but also by contributing to energy efficiency. Buildings are responsible for around 40% of worldwide energy consumption BIB002 , which is expected to significantly increase over the next few years BIB003 . As such, efficiency improvements, implemented at global scale, can mitigate this trend, reducing energy consumption, wastage, costs and environmental hazards associated with generation. In the last few years, there has been a growing interest in home energy management systems (HEMSs). They provide the means for automated and intelligent control of smart home appliances. HEMSs target efficient energy management, contributing to preserving finite fossil fuel resources, while lowering energy consumption, wastage and costs. The conceptualisation of HEMSs involves several aspects, including their definition, characterisation and overall architecture, as well as their underlying purpose in household environments. Optimisation-based techniques are extensively employed within HEMSs. They enable appliance allocation under dynamic objectives and constraints. In BIB001 this trend is highlighted, calling for further research to address HEMSs specific needs, in particular concerning scalability, model complexity and uncertainties. Intrinsically linked to the characterisation of HEMSs are: (i) their in-operation goals, including minimising the overall energy bill, reducing carbon emissions, or achieving a given target load profile, just to name a few; (ii) the strategies employed to achieve such goals, in particular how to schedule individual appliances or deciding upon which unnecessary loads should be turned off; (iii) managing household appliances; (iv) how they are individually modelled. This paper provides a comprehensive review with respect to HEMSs, including an outlook on these systems and closely-related topics. Approaches aiming at household appliance modelling, scheduling strategies, operational and residential objectives and constraints are discussed. In addition, the incorporation of residential load uncertainties into HEMSs is also covered. Two main contributions are provided in this work. Firstly, a thorough review on recent HEMS developments is presented, including operational goals and strategies to meet them, household appliance management policies, incorporation of uncertainty in HEMSs' decision making, performance metrics, and common attack targets and corresponding counter-measures. Secondly, an updated literature list on HEMSs is included, which to some extent can be regarded as gateway to the most relevant and updated bibliography on the field. The remainder of this paper is organised as follows. In Section II HEMSs are defined, characterised and contextualised within the smart grid digital paradigm. Centralised and distributed energy management schemes are discussed, as well as the most recent advances regarding the integration of plugged-in electric vehicles on the digital grid. Section III introduces the main approaches to energy saving in buildings. Section IV presents a literature categorisation regarding household appliances included in HEMSs infrastructures. Common managed appliances are presented, along with adopted strategies to model their behaviour and dynamics, including in-operation dynamics and uncertainties. Section V is devoted to appliance scheduling, being discussed common techniques, scheduling criteria and constraints. Section VI focuses on cyber attack vectors and counter-measures for HEMSs, while Section VII describes some of the challenges this field is facing, along with prospective research directions. Finally, Section IX concludes the survey.