scholarly journals Willingness to Pay for Home Energy Management Systems: A Survey in New York and Tokyo

2019 ◽  
Vol 11 (17) ◽  
pp. 4790 ◽  
Author(s):  
Ayu Washizu ◽  
Satoshi Nakano ◽  
Hideo Ishii ◽  
Yasuhiro Hayashi
Keyword(s):  
New York ◽  
Willingness To Pay ◽  
Automatic Control ◽  
Energy Management ◽  
Control Function ◽  
Management Systems ◽  
Energy Management System ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Home Energy Management System

This study evaluates the acceptability of home energy management systems (HEMS) in New York and Tokyo using a questionnaire survey. We investigated three basic functions of HEMS: money saving, automatic control, and environmental impact, and then quantified people’s propensity to accept each of these three functions by measuring their willingness to pay. Using the willingness to pay results, we estimated the demand probability under a given usage price for each of the three functions of home energy management systems and analyzed how socio-economic and demographic factors influence the demand probability. The demand probability related to a home energy management system function decreases as the usage price of the function increases. However, depending on people’s socio-economic characteristics, the rate of decrease in demand probability relative to the rate of increase in usage price varies. Among the three functions of home energy management systems, we found that the automatic control function showed the highest demand probability in New York and Tokyo, emphasizing the significance of an automatic control function. In New York, when the home energy management system has an automatic control function, its demand probability increases, which is further enhanced if people trust their utility company. In Tokyo, when a home energy management system has an environmental impact function, its demand probability increases at a given price. People in Tokyo have anxieties related to new technologies such as home energy management systems. Therefore, it is necessary to enhance their comprehension of a home energy management systems to address this anxiety.

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 Design of Ensemble Forecasting Models for Home Energy Management Systems

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7664
Author(s):  
Karol Bot ◽  
Samira Santos ◽  
Inoussa Laouali ◽  
Antonio Ruano ◽  
Maria da Graça Ruano
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Simple Procedure ◽  
Ensemble Forecasting ◽  
Management Systems ◽  
Energy Forecasting ◽  
Energy Management Systems ◽  
Ensemble Techniques ◽  
Home Energy Management ◽  
Home Energy Management System

The increasing levels of energy consumption worldwide is raising issues with respect to surpassing supply limits, causing severe effects on the environment, and the exhaustion of energy resources. Buildings are one of the most relevant sectors in terms of energy consumption; as such, efficient Home or Building Management Systems are an important topic of research. This study discusses the use of ensemble techniques in order to improve the performance of artificial neural networks models used for energy forecasting in residential houses. The case study is a residential house, located in Portugal, that is equipped with PV generation and battery storage and controlled by a Home Energy Management System (HEMS). It has been shown that the ensemble forecasting results are superior to single selected models, which were already excellent. A simple procedure was proposed for selecting the models to be used in the ensemble, together with a heuristic to determine the number of models.

scholarly journals An Overview of the Building Energy Management System Considering the Demand Response Programs, Smart Strategies and Smart Grid

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3299 ◽  
Author(s):  
Mohammad Shakeri ◽  
Jagadeesh Pasupuleti ◽  
Nowshad Amin ◽  
Md. Rokonuzzaman ◽  
Foo Wah Low ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Demand Response ◽  
Smart Grids ◽  
Management System ◽  
Management Systems ◽  
Energy Management System ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Demand Response Programs

Electricity demand is increasing, as a result of increasing consumers in the electricity market. By growing smart technologies such as smart grid and smart energy management systems, customers were given a chance to actively participate in demand response programs (DRPs), and reduce their electricity bills as a result. This study overviews the DRPs and their practices, along with home energy management systems (HEMS) and load management techniques. The paper provides brief literature on HEMS technologies and challenges. The paper is organized in a way to provide some technical information about DRPs and HEMS to help the reader understand different concepts about the smart grid, and be able to compare the essential concerns about the smart grid. The article includes a brief discussion about DRPs and their importance for the future of energy management systems. It is followed by brief literature about smart grids and HEMS, and a home energy management system strategy is also discussed in detail. The literature shows that storage devices have a huge impact on the efficiency and performance of energy management system strategies.

scholarly journals Industrial Energy Management System: Design of a Conceptual Framework using IoT and Big Data

2021 ◽  
Author(s):  
Mehar Ullah ◽  
Arun Narayanan ◽  
Annika Wolff ◽  
Pedro Nardelli
Keyword(s):  
Big Data ◽  
System Design ◽  
Energy Management ◽  
Management Systems ◽  
Energy Management System ◽  
High Level Architecture ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Industrial Energy ◽  
High Level

<div>This contribution aims to propose a high-level architecture for IEnMS that incorporates IoT and Big Data. This is necessary because although IoT and Big Data have been considered in home energy management systems (HEMS), their implementation and applications in IEnMS are not well studied.</div>

scholarly journals Industrial Energy Management System: Design of a Conceptual Framework using IoT and Big Data

2021 ◽  
Author(s):  
Mehar Ullah ◽  
Arun Narayanan ◽  
Annika Wolff ◽  
Pedro Nardelli
Keyword(s):  
Big Data ◽  
System Design ◽  
Energy Management ◽  
Management Systems ◽  
Energy Management System ◽  
High Level Architecture ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Industrial Energy ◽  
High Level

<div>This contribution aims to propose a high-level architecture for IEnMS that incorporates IoT and Big Data. This is necessary because although IoT and Big Data have been considered in home energy management systems (HEMS), their implementation and applications in IEnMS are not well studied.</div>

scholarly journals Home Energy Management System for Dynamic Loads using Mamdani Fuzzy Logic Approach

2022 ◽  
Vol 10 (3) ◽  
pp. 1-13
Author(s):  
Nishi Singh ◽  
◽  
M.P.S. Chawla ◽  
Sandeep Bhongade ◽  
◽  
...  
Keyword(s):  
Energy Management ◽  
Demand Management ◽  
Energy Management System ◽  
Distributed Energy ◽  
Energy Management Systems ◽  
Home Energy Management ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Home Energy Management System

HEMS (home energy management systems) are controllers that manage and coordinate a home's generation, storage, and loads. These controllers are becoming increasingly important. To ensure that distributed energy penetration continues to grow resources are appropriately utilized and the process is not disrupted within the grid[1]. An approach to hems design based on behavioural control approaches is discussed in this paper which do not require accurate models or forecasts and are particularly responsive to changing situations, in this study. In this study, the role of the customer as well as the micro grid in intelligent demand management is demonstrated using MATLAB 2018 Fuzzy tool.[3]

Home Energy Management System

2012 ◽  
Vol 132 (10) ◽  
pp. 695-697 ◽  
Author(s):  
Hideki HAYASHI ◽  
Yukitoki TSUKAMOTO ◽  
Shouji MOCHIZUKI
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Management System ◽  
Home Energy Management ◽  
Home Energy Management System
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