Home Energy Management System Concepts, Configurations, and Technologies for the Smart Grid

Abstract

Home energy management systems (HEMSs) help manage electricity demand to optimize energy consumption and distributed renewable energy generation without compromising consumers' comfort. HEMSs operate according to multiple criteria, including energy cost, weather conditions, load profiles, and consumer comfort. They play an increasingly ubiquitous role in energy efficiency through the reduction of electricity consumption within residential and commercial smart grids. This paper presents a comprehensive review of the HEMS literature with reference to main concepts, configurations, and enabling technologies. In doing so, it also provides a summary of HEMS computing trends and popular communication technologies for demand response applications. The ensuing survey offers the reader with an overall overview of current and future trends in HEMS solutions and technologies. INDEX TERMS Home energy management system, demand response, smart technologies, integrated wireless technology, intelligent scheduling controller. I.

Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes With Energy Storage

“…The set point, T t S , for the EWH determines the required ON and OFF switching and the resultant power flow according to (2) - (4).…”

“…Due to such technological advancements, smart homes can enhance energy efficiency, and improve both stability and reliability by allowing owners to regulate electricity usage [1]- [3]. They can also change the operations of utilities by minimizing both energy usage and peak demand in the residences [4]- [7].…”

Event‐triggered load frequency control of smart grids under deception attacks

“…Substituting (8) into (2) we have that the initial state model (2) of the multi-area power system with LFC can be rewritten as the following ACE -dependent time-delay model…”

A Permissioned Blockchain System to Reduce Peak Demand in Residential Communities via Energy Trading: A Real-World Case Study

“…where, {P M IN BESS , P M AX BESS } are the minimum and maximum power limits, P BESS (k) is the instantaneous power requirement, {SoC M IN BESS , SoC M AX BESS } are the minimum and maximum SoC limits, SoC BESS (k) is the current SoC, χ is a binary variable that represents 1 for charging mode and 0 otherwise, and {η CH , η DIS } are the charging and discharging efficiencies, respectively. On the other hand, an EV is modeled as a unidirectional load, as seen in (5).…”

“…Thus, the presence of a HEMS transforms a home into a smart home, which is capable of autonomously controlling the DERs of the homeowner to achieve energy savings. However, a significant limitation of HEMS' is that they typically provide local control of a single home, and they do not have observability of the entire residential community [5]. This leads to uncoordinated operation of DERs within the community, which may result in major increases in peak demand and overloading of transformers when EVs and BESSs are charging coincidentally [6].…”