Mathematical Modelling Based Demand Response Analysis of Major Household Appliances

Abstract

This paper discusses the power consumption profile and demand response potential of home appliances in India. It includes WH (water heater), HVAC (Heating, ventilation, and air conditioning) system, cloth dryer, washing machine and critical appliances. Mathematical module of these appliances have been developed. Simulation results show that the water heater has highest demand response potential followed by cloth dryer, HVAC, and washing machine. Consumer life style and comfort is affected if DR (Demand Response) is applied in critical appliances. This paper provides an insight that how much DR can be performed for residential consumers.Arshad Mohammad received bachelor of engineering in electrical engineering and master in technology in electrical engineering with specialization in instrumentation and control from Aligarh Muslim University, Aligarh, India in 2013 and 2015 respectively. Currently he is pursuing PhD in power system. His research interest energy management and monitoring in smart home, smart grid and micro-grid. S.B Asgharreceived master in engineering from AMU in 1988. He has done his PhD from Baba sahib Ambedkar Bihar University in 2018. Now he is currently head of department in maulana azad college of engineering and technology.His research interest include renewable energy and power electronics.Imtiaz ashraf has done his B.sc engineering and M.sc engineering from Aligarh Muslim University. He has done his PhD from IIT Delhi. Presently he professor and chairman at department of electrical engineering. His research interest include renewable energy, micro grid planning, energy management and optimization.

A novel automated demand response control using fuzzy logic for islanded battery‐operated rural microgrids

“… $$$$\begin{equation}\ {{\bf{L}}}_{{\bf{sum}}} = {{\bf{F}}}_{\bf{a}}\ \ + {{\bf{M}}}_{\bf{o}} + {{\bf{L}}}_{\bf{i}} + {{\bf{T}}}_{\bf{v}}\end{equation}$$$$ $$$$\begin{equation}\ {{\bf{L}}}_{{\bf{win}}} = {{\bf{M}}}_{\bf{o}}\ \ + {{\bf{L}}}_{\bf{i}} + {{\bf{T}}}_{\bf{v}}\end{equation}$$$$where $${{\bf{L}}}_{{\bf{sum}}}$$ represents summer load, $${{\bf{L}}}_{{\bf{win}}}$$ is the winter load, $${{\bf{F}}}_{\bf{a}}$$ is the fan load, $${{\bf{M}}}_{\bf{o}}$$ is the Motor load, $${{\bf{L}}}_{\bf{i}}$$is the lighting load and $${{\bf{T}}}_{\bf{v}}$$ is the Television load. The total power consumption of these loads in summer and winter can be expressed as [24], $$$$\begin{equation}\ {\bf{P}}{\ }_{{{\bf summer}}} = \mathop \sum \limits_1^{\bf{K}} {{\bf{P}}}_{{\bf{ck}}}\ \ \end{equation}$$$$…”

“…where L sum represents summer load, L win is the winter load, F a is the fan load, M o is the Motor load, L i is the lighting load and T v is the Television load. The total power consumption of these loads in summer and winter can be expressed as [24],…”

“…Therefore, an effective energy management system is required to manage the energy utilization in microgrids. The proposed energy management system by authors in [24] consists of supervisory control based on fuzzy logic to control the battery State of Charge (SoC) and the hydrogen level. This energy management system is composed of a control system that minimizes the utilization cost of the hybrid system [24].…”

Towards the Optimal Performance of Washing Machines Using Fuzzy Logic

“…A smart timer was used in the WM to indicate the time consumed by each cycle of operation and state the type of clothes the individual wants 2 Scientific Programming to wash. Even when the running time (T n ) is less than the required set time (T max ), the WM will turn ON, and when the required time and running time become equal, the dryer of the WM will turn OFF as represented in equation ( 3) [8][9][10].…”