Expert Assessment of Prioritized Determinants For a Smarter Grid Through The Lens of Residential Demand Response: The Case Study of Ontario, Canada

In recent years, smart grids have attracted considerable attention. However, despite the promising potential of the technologies encompassed within such systems, their adoption has been slow, geographically varied, and in the context of residential demand response, often subject to public scrutiny. The heterogeneous evolution of the smart grid is not only the product of technological limitations but is additionally sensitive to socio-political considerations prevalent at the national or provincial level. Through expert interviews that were conducted in Ontario, Canada, this study provides insights into which smart grid factors are considered as most important for its development, and also what are the drivers, inhibitors, benefits, and drawbacks that a smart grid provides and / or entails, placing particular emphasis on residential demand response programs. The constructs scrutinized were adapted from previous studies, and the information collected was analyzed following the procedure of the Grounded Delphi Method. The findings indicate that a consensus was reached, in that smart grids pave the way for increased demand flexibility and loss reductions, though these are contingent on measures being implemented regarding the creation of investment opportunities, engagement of consumers, and ensuring the security of private data. Relevant policy implications and research recommendations are also explored.

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Strategies for Datacenters Participating in Demand Response by Two-Stage Decisions

Mathematical Problems in Engineering ◽

10.1155/2020/5206082 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Yuling Li ◽

Xiaoying Wang ◽

Peicong Luo

Keyword(s):

Smart Grid ◽

Demand Response ◽

Smart Grids ◽

Peak Load ◽

Two Stage ◽

The Sustainable Development ◽

Second Stage ◽

Potential Demand ◽

Electricity Costs ◽

Demand Response Programs

Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.

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

Energies ◽

10.3390/en13133299 ◽

2020 ◽

Vol 13 (13) ◽

pp. 3299 ◽

Cited By ~ 1

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.

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Energy Consumption Management in Buildings in the Context of Voluntary and Mandatory Demand Response Programs in Smart Grids

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe) ◽

10.1109/isgt-europe47291.2020.9248750 ◽

2020 ◽

Author(s):

Mahsa Khorram ◽

Modar Zheiry ◽

Pedro Faria ◽

Zita Vale

Keyword(s):

Energy Consumption ◽

Demand Response ◽

Smart Grids ◽

Demand Response Programs

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Shedding Light on the Factors That Influence Residential Demand Response in Japan

Energies ◽

10.3390/en14102795 ◽

2021 ◽

Vol 14 (10) ◽

pp. 2795

Author(s):

Nikolaos Iliopoulos ◽

Motoharu Onuki ◽

Miguel Esteban

Keyword(s):

Demand Response ◽

Primary Data ◽

Willingness To Participate ◽

The Public ◽

Related Information ◽

Direct Load Control ◽

Integration Of Renewables ◽

Residential Demand ◽

Demand Response Programs ◽

Energy Grid

Residential demand response empowers the role of electricity consumers by allowing them to change their patterns of consumption, which can help balance the energy grid. Although such type of management is envisaged to play an increasingly important role in the integration of renewables into the grid, the factors that influence household engagement in these initiatives have not been fully explored in Japan. This study examines the influence of interpersonal, intrapersonal, and socio-demographic characteristics of households in Yokohama on their willingness to participate in demand response programs. Time of use, real time pricing, critical peak pricing, and direct load control were considered as potential candidates for adoption. In addition, the authors explored the willingness of households to receive non-electricity related information in their in-home displays and participate in a philanthropy-based peer-to-peer energy platform. Primary data were collected though a questionnaire survey and supplemented by key informant interviews. The findings indicate that household income, ownership of electric vehicles, socio-environmental awareness, perceived sense of comfort, control, and complexity, as well as philanthropic inclinations, all constitute drivers that influence demand flexibility. Finally, policy recommendations that could potentially help introduce residential demand response programs to a wider section of the public are also proposed.

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An Effectiveness Modelling Approach for IoT-Based Smart Grids

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Design, Applications, and Maintenance of Cyber-Physical Systems ◽

10.4018/978-1-7998-6721-0.ch005 ◽

2021 ◽

pp. 92-111

Author(s):

Dongming Fan ◽

Yi Ren ◽

Qiang Feng

Keyword(s):

Smart Grid ◽

Smart Grids ◽

Information Technologies ◽

Self Healing ◽

New Paradigm ◽

Agent Based ◽

Efficient Energy ◽

Real Time Analysis ◽

Multi Agent

The smart grid is a new paradigm that enables highly efficient energy production, transport, and consumption along the whole chain from the source to the user. The smart grid is the combination of classical power grid with emerging communication and information technologies. IoT-based smart grid will be one of the largest instantiations of the IoT in the future. The effectiveness of IoT-based smart grid is mainly reflected in observability, real-time analysis, decision-making, and self-healing. A proper effectiveness modeling approach should maintain the reliability and maintainability of IoT-based smart grids. In this chapter, a multi-agent-based approach is proposed to model the architecture of IoT-based smart grids. Based on the agent framework, certain common types of agents are provided to describe the operation and restoration process of smart grids. A case study is demonstrated to model an IoT-based smart grid with restoration, and the interactive process with agents is proposed simultaneously.

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Optimal Control of Multiple Microgrids and Buildings by an Aggregator

Energies ◽

10.3390/en13051058 ◽

2020 ◽

Vol 13 (5) ◽

pp. 1058 ◽

Cited By ~ 3

Author(s):

Giulio Ferro ◽

Riccardo Minciardi ◽

Luca Parodi ◽

Michela Robba ◽

Mansueto Rossi

Keyword(s):

Distributed Generation ◽

Electric Vehicles ◽

Demand Response ◽

Electrical Grid ◽

Energy Management Systems ◽

New Energy ◽

Systems Models ◽

Fair Assignment ◽

Demand Response Programs

The electrical grid has been changing in the last decade due to the presence of renewables, distributed generation, storage systems, microgrids, and electric vehicles. The introduction of new legislation and actors in the smart grid’s system opens new challenges for the activities of companies, and for the development of new energy management systems, models, and methods. A new optimization-based bi-level architecture is proposed for an aggregator of consumers in the balancing market, in which incentives for local users (i.e., microgrids, buildings) are considered, as well as flexibility and a fair assignment in reducing the overall load. At the lower level, consumers try to follow the aggregator’s reference values and perform demand response programs to contain their costs and satisfy demands. The approach is applied to a real case study.

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