scholarly journals Home Energy Management System Incorporating Heat Pump Using Real Measured Data

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2937 ◽  
Author(s):  
Cao ◽  
O’Rourke ◽  
Lyons ◽  
Han
Keyword(s):  
Energy Management ◽  
Heat Pump ◽  
Measured Data ◽  
Management Systems ◽  
End User ◽  
Energy Management Systems ◽  
Comfort Levels ◽  
Home Energy Management ◽  
The Cost ◽  
User Comfort

The demand for electricity has been rising significantly over the past years and it is expected to rise further in the coming years due to economic and societal development. Smart grid technology is being developed in order to meet the rising electricity requirement. In order for the smart grid to perform its full functions, the Energy Management Systems (EMSs), especially Home Energy Management Systems (HEMS) are essential. It is necessary to understand the energy demand of the loads and the energy supply either from the national grid or from renewable energy technologies. To facilitate the Demand Side Management (DSM), Heat Pumps (HP) and air conditioning systems are often utilised for heating and cooling in residential houses due to their high-efficiency power output and low CO2 emissions. This paper presents a program for a HEMS using a Particle Swarm Optimisation (PSO) algorithm. A HP is used as the load and the aim of the optimisation program is to minimise the operational cost, i.e., the cost of electricity, while maintaining end-user comfort levels. This paper also details an indoor thermal model for temperature update in the heat pump control program. Real measured data from the UK Government’s Renewable Heat Premium Payment (RHPP) scheme was utilised to generate characteristic curves and equations that can represent the data. This paper compares different PSO variants with standard PSO and the unscheduled case calculated from the data for five winter days in 2019. Among all chosen algorithms, the Crossover Subswarm PSO (CSPSO) achieved an average saving of 25.61% compared with the cost calculated from the measured data with a short search time of 1576 ms for each subswarm. It is clear from this work that there is significant scope to reduce the cost of operating a HP while maintaining end user comfort levels.

scholarly journals A Case Study of Socially-Accepted Potentials for the Use of End User Flexibility by Home Energy Management Systems

2020 ◽  
Vol 13 (1) ◽  
pp. 132
Author(s):  
Christian Pfeiffer ◽  
Markus Puchegger ◽  
Claudia Maier ◽  
Ina V. Tomaschitz ◽  
Thomas P. Kremsner ◽  
...  
Keyword(s):  
Energy Management ◽  
Management System ◽  
Management Systems ◽  
System Support ◽  
Energy Management System ◽  
Energy Management Systems ◽  
Sample Area ◽  
Home Energy Management ◽  
Support Optimization ◽  
Home Energy Management System

Due to the increase of volatile renewable energy resources, additional flexibility will be necessary in the electricity system in the future to ensure a technically and economically efficient network operation. Although home energy management systems hold potential for a supply of flexibility to the grid, private end users often neglect or even ignore recommendations regarding beneficial behavior. In this work, the social acceptance and requirements of a participatively developed home energy management system with focus on (i) system support optimization, (ii) self-consumption and self-sufficiency optimization, and (iii) additional comfort functions are determined. Subsequently, the socially-accepted flexibility potential of the home energy management system is estimated. Using methods of online household survey, cluster analysis, and energy-economic optimization, the socially-accepted techno-economic potential of households in a three-community cluster sample area is computed. Results show about a third of the participants accept the developed system. This yields a shiftable load of nearly 1.8 MW within the small sample area. Furthermore, the system yields the considerably larger monetary surplus on the supplier-side due to its focus on system support optimization. New electricity market opportunities are necessary to adequately reward a systemically useful load behavior of households.

scholarly journals Blockchain-Enabled Transactive Home Energy Management Systems in Distribution Networks

2020 ◽  
Author(s):  
Lawryn Edmonds ◽  
Bo Liu ◽  
Hongyu Wu ◽  
Hang Zhang ◽  
Don Gruenbacher ◽  
...  
Keyword(s):  
Energy Management ◽  
Distribution System ◽  
Distribution Networks ◽  
Electric Utility ◽  
Management Systems ◽  
Energy Management Systems ◽  
Customer Information ◽  
Viable Solution ◽  
Home Energy Management ◽  
System Operator

As home energy management systems (HEMSs) are implemented in homes as ways of reducing customer costs and providing demand response (DR) to the electric utility, homeowner’s privacy can be compromised. As part of the HEMS framework, homeowners are required to send load forecasts to the distribution system operator (DSO) for power balancing purposes. Submitting forecasts allows a platform for attackers to gain knowledge on user patterns based on the load information provided. The attacker could, for example, enter the home to steal valuable possessions when the homeowner is away. In this paper, we propose a framework using a smart contract within a private blockchain to keep customer information private when communicating with the DSO. The results show the HEMS users’ privacy is maintained, while the benefits of data sharing are obtained. Blockchain and its associated smart contracts may be a viable solution to security concerns in DR applications where load forecasts are sent to a DSO.

scholarly journals A Study of Home Energy Management Systems for Northern Houses

2017 ◽  
Vol 96 (4) ◽  
pp. 112-120
Author(s):  
Atsuhiro KAWAMURA ◽  
Hiroki HAYASHI ◽  
Taro MORI ◽  
Hidekazu KAJIWARA ◽  
Kazunori CHIDA ◽  
...  
Keyword(s):  
Energy Management ◽  
Management Systems ◽  
Energy Management Systems ◽  
Home Energy Management

Naïve Bayes classifier enabled home energy management scheme for cost-effective end-user comfort

2021 ◽  
Vol 40 (1) ◽  
pp. 403-413
Author(s):  
M. Firdouse Ali Khan ◽  
Ganesh Kumar Chellamani ◽  
Premanand Venkatesh Chandramani
Keyword(s):  
Energy Management ◽  
Time Window ◽  
Cost Effective ◽  
Pattern Generation ◽  
Home Appliances ◽  
Management Scheme ◽  
Home Energy Management ◽  
Maximum Comfort ◽  
The Cost ◽  
User Comfort

Under demand response enabled demand-side management, the home energy management (HEM) schemes schedule appliances for balancing both energy and demand within a residence. This scheme enables the user to achieve either a minimum electricity bill (EB) or maximum comfort. There is always the added burden on a HEM scheme to obtain the least possible EB with comfort. However, if a time window that contains comfortable time slots of the day for an appliance operation, is identified, and if the cost-effective schedule-pattern gets generated from these windows autonomously, then the burden can be reduced. Therefore, this paper proposes a two-level method that can assist the HEM scheme by generating a cost-effective schedule-pattern for scheduling home appliances. The first level uses a classifier to identify the comfortable time window from past ON and OFF events. The second level uses pattern generation algorithms to generate a cost-effective schedule-pattern from the identified window. The generated cost-effective schedule-pattern is applied to a HEM scheme as input to demonstrate the proposed two-level approach. The simulation results exhibit that the proposed approach helps the HEM scheme to schedule home appliances cost-effectively with a satisfactory user-comfort between 90% and 100%.

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