scholarly journals Analysis of the Effects of the Home Energy Management System from an Open Innovation Perspective

2018 ◽  
Vol 4 (3) ◽  
pp. 31 ◽  
Author(s):  
EungSuk Park ◽  
BoRam Kim ◽  
SooHyun Park ◽  
Daecheol Kim
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Electricity Consumption ◽  
Electric Power Consumption ◽  
Energy Management System ◽  
Home Energy Management ◽  
Home Energy Management System

The Home Energy Management System (HEMS) is a system for the efficient electric power consumption of each household. It can provide real-time electricity cost information according to electricity consumption, and households can immediately control their consumption of electricity. In this study, we analyzed the effects of the HEMS on the stability of demand for electric power. To do this, we analyzed the causal relationship between the amounts of electric power generation and consumption, from the system dynamics perspective. From the analysis, we found that in the current structure, the fluctuation of the quantity of demand became large due to the time delay in households recognizing the electric bill and adjusting their electric power consumption. However, when the HEMS was introduced, it could be seen that electric power demand remained stable since consumers could see their electricity bill in real-time and could manage their electricity consumption by themselves.

Operation Scheduling of Household Load, EV and BESS Using Real Time Pricing, Incentive Based DR and Peak Power Limiting Strategy

2018 ◽  
Vol 20 (1) ◽  
Author(s):  
Sandeep Kakran ◽  
Saurabh Chanana
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Cost Reduction ◽  
Management System ◽  
Peak Power ◽  
Base Case ◽  
Energy Management System ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Home Energy Management System

Abstract Demand response (DR) programs have become powerful tools of the smart grids, which provide opportunities for the end-use consumers to participate actively in the energy management programs. This paper investigates impact of different DR strategies in a home-energy management system having consumer with regular load, electric vehicle (EV) and battery-energy storage system (BESS) in the home. The EV is considered as a special type of load, which can also work as an electricity generation source by discharging the power in vehicle-to-home mode during high price time. BESS and a small renewable energy source in form of rooftop photovoltaic panels give a significant contribution in the energy management of the system. As the main contribution to the literature, a mixed integer linear programming based model of home energy management system is formulated to minimize the daily cost of electricity consumption under the effect of different DR programs; such as real time price based DR program, incentive based DR program and peak power limiting DR program. Finally, total electricity prices are analysed in the case studies by including different preferences of the household consumer under mentioned DR programs. A total of 26.93 % electricity cost reduction is noticed with respect to base case, without peak limiting DR and 19.93 % electricity cost reduction is noticed with respect to base case, with peak limiting DR.

scholarly journals Study on Smart Home Energy Management System Based on Artificial Intelligence

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yunlong Ma ◽  
Xiao Chen ◽  
Liming Wang ◽  
Jianlan Yang
Keyword(s):  
Energy Management ◽  
Management System ◽  
Smart Home ◽  
Electricity Consumption ◽  
Optimal Scheduling ◽  
Energy Sources ◽  
Energy Management System ◽  
Home Energy Management ◽  
New Energy ◽  
Home Energy Management System

With the increase of household electricity consumption and the introduction of distributed new energy sources, more attention has been paid to the issue of optimizing the cost of electricity purchase for household customers. An effective way to deal with these problems is through home energy management system (HEMS). In this paper, a model of home energy management is presented to optimize the home energy mix. The operation of home electricity consumption devices, distributed generation systems, and energy storage devices, as well as the charging and discharging of electric vehicles, are all considered. HEMS is a self-regulating system that can accommodate fluctuations in tariffs and home electricity consumption. The structure and the optimal scheduling algorithm of HEMS are introduced. The smart grid and demand response, smart home, new energy generation, energy storage, and other related technologies are discussed. Furthermore, the optimal scheduling of power consumption devices and energy sources in the HEMS and future development directions are explained and analyzed. A framework of HEMS is presented on the basis of advanced metering infrastructure (AMI). The framework adopts a local information management terminal as the core of data storage and scheduling in the home. Based on the timely purchase of electricity from the grid and the generation of electricity in combination with PV systems, an optimized simulation model for the scheduling of a new home energy management system is established. In addition, the application prospects of artificial intelligence in the HEMS are overviewed.

scholarly journals Air Conditioning for Smart Home Energy Management System

2018 ◽  
Vol 7 (4.35) ◽  
pp. 487
Author(s):  
A. Ashraf ◽  
M. Faisal ◽  
K. Parvin ◽  
Pin Jern Ker ◽  
M. A. Hannan
Keyword(s):  
Energy Management ◽  
Management System ◽  
Electricity Consumption ◽  
End Users ◽  
Energy Utilization ◽  
Energy Management System ◽  
Air Conditioner ◽  
Home Energy Management ◽  
Home Energy Management System ◽  
Advanced Metering

Smart load management system with an advanced metering infrastructure operates to monitor the electricity consumption by the load and transferring data to the utility grid. It has direct benefit to the end-users by managing the load. This system has incorporated with home appliance for achieving the goal of home energy management system (HEMS) such as efficient energy utilization of house by avoiding the wastage. Efficient loading system can strengthen the efficient power utilization and thus can save the economy greatly. Air conditioner (AC), thermostat associated with a room were selected for this purpose as they have the high demand of electricity consumption. This study mainly focuses on developing the mathematical model and simulate it for the considered home appliances to assess the trend of electricity consumption. Research proved that, considering the ambient temperature developed model can provide the specific instructions for automatic controlling of the appliances which will save the electricity consumption and utility bill of end-users compare to the manual operation of the system. Matlab /Simulink software was used to implement and justify the model.

scholarly journals Demand response program for smart grid through real time pricing and home energy management system

2021 ◽  
Vol 11 (5) ◽  
pp. 4558
Author(s):  
Shibily Joseph ◽  
E. A. Jasmin
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Energy Management ◽  
Demand Response ◽  
Management System ◽  
Peak Load ◽  
Energy Management System ◽  
Home Energy Management ◽  
Real Time Pricing ◽  
Home Energy Management System

Aim of demand response (DR) programs are to change the usage pattern of electricity in such a way that, beneficial to the consumers as well as to the distributors by applying some methods or technology. This way additional cost to erect new energy sources can be postponed in power grid. Best method to implement demand response (DR) program is by influencing consumer through the implementation of real time pricing scheme. To harness the benefit of DR, automated home energy management system is essential. This paper presents a comprehensive demand response system with real time pricing. The real time price is determined after considering price elasticity of various classes of consumers and their load profiles. A real time clustering algorithm suitable for big data of smart grid is devised for the segmentation of consumers. This paper is novel in its design for real time pricing and modelling and automatic scheduling of appliances for home energy management. Simulation results showed that this new real time pricing method is suitable for DR programs to reduce the peak load of the system as well as reducing the energy expenditure of houses, while ensuring profit for the retailer.

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