A hardware algorithm for PAR reduction in smart home

Abstract

High quality demand side management has become indispensable in the smart grid infrastructure for enhanced energy reduction and system control. Most of the demand side management systems that existed were focusing on the interaction between utility company and its customers. So as a reason the Home Energy Management (HEM) systems plays a crucial role in realizing residential Demand Response (DR) programs in the smart environment. It provides a homeowner the ability to automatically perform smart load controls based on utility programs, customer's preference and load priority. This paper presents the hardware demonstration of the proposed HEM system for managing the end-use appliances. The proposed algorithm manages the household loads according to their preset priority and fixed the total household power consumption under certain limit. This work achieves the purpose of reducing electricity expense and clipping the peak-to-average ratio (PAR).

A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment

“…The hardware implementation of DR programs and cloud computing methods considering customer's preferences and load priority for energy management are presented [62,161]. A smart residential energy management system is designed for appliances and battery scheduling [162].…”

Analysis Application of Controllable Load Appliances Management in a Smart Home

“…With the help of a smart phone or a laptop, loads can be managed remotely to help the RC to control and manage the energy and equipment and, as a result, reduce the energy bill. Every load has a different type of operation, so it becomes necessary to separate the different type of loads into the critical loads and controllable loads [9].…”

Optimization models and algorithms for demand response in smart grid.

“…The method in [61] makes the homeowner to automatically perform smart load controls possible. Controls are based on utility programs, customer's preference and load priority .…”

“…Constraint (61) states that the battery storage can be discharged 2/3 of its full capacity during the high-demand window T 1 for user i. Constraint (62) states that the battery can only be charged during the low-demand period and constraint (63) calculates the energy consumption of charging battery for each time interval during low-demand times. Similarly, constraint (64) ensures that the battery can only be discharged during the high-demand window and constraint (65) calculates the amount of energy each battery can discharge to the grid at each time interval during high-demand window.…”

“…Amer et al [61] propose the algorithm that can manage the household loads according to end user's preset priority and fix the total household power consumption under certain limit. The method in [61] makes the homeowner to automatically perform smart load controls possible.…”