Energy Management in the Smart Grids via Intelligent Storage Systems

Klaimi, Joelle; Rahim-Amoud, Rana; Merghem-Boulahia, Leïla

doi:10.1007/978-3-319-46331-5_11

Cited by 8 publications

(10 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ABMs have previously been employed in studying the adoption of various sustainable behaviors and attitudes, 19 including models of norm transmission and evolution, 20,21 recycling, 22 traffic and transport, [23][24][25] farming, 26 energy and risk management, 27,28 and psychology. 29,30 Our contribution to this rapidly developing field is in developing a holistic systemic approach to the emergence of behavior as a subtle function of social, individual, and environmental factors by focusing explicitly on the emergent leverage points and tipping points.…”

Section: Introductionmentioning

confidence: 99%

Cultural Evolution of Sustainable Behaviors: Pro-environmental Tipping Points in an Agent-Based Model

Kaaronen

Strelkovskii

2020

One Earth

View full text Add to dashboard Cite

Graphical AbstractHighlights d An ABM is used to study the cultural evolution of sustainable behaviors d Behaviors emerge as a function of affordances, social learning, and habits d The affordances in an environment have a major effect on behavior adoption d The ABM is validated against cycling behaviors in Copenhagen Authors Roope Oskari Kaaronen, Nikita Strelkovskii Correspondence roope.kaaronen@helsinki.fi In Brief Kaaronen and Strelkovskii have designed an agent-based model to study the cultural evolution of sustainable behaviors. Behaviors emerge as a product of personal, environmental, and social factors. Particularly the structure of the environment has an effect on the adoption of pro-environmental behaviors. Even linear changes in pro-environmental affordances (action opportunities) can trigger non-linear collective behavior change. The model is validated against cycling behaviors in Copenhagen. This model gives further justification for policies and urban design that make proenvironmental behavior psychologically salient, accessible, and easy.

show abstract

Section: Introductionmentioning

confidence: 99%

Cultural Evolution of Sustainable Behaviors: Pro-environmental Tipping Points in an Agent-Based Model

Kaaronen

Strelkovskii

2020

One Earth

View full text Add to dashboard Cite

show abstract

“…This changing paradigm empowering end-users will allow new business models and energy infrastructure ownership configurations to emerge [1,2]. In this setting, local energy communities (LEC) in which end-users become prosumers and prosumagers are gaining momentum, both in the literature [3,4] and in the EU's regulatory framework, being at the heart of the European energy policy for 2030 and 2050 [5].…”

Section: The Role Of Energy Communities In the Eu Agendamentioning

confidence: 99%

Assessing the Influence of Different Goals in Energy Communities’ Self-Sufficiency—An Optimized Multiagent Approach

et al. 2021

View full text Add to dashboard Cite

Understanding to what extent the emergence of prosumers and prosumagers organized in energy communities can impact the organization and operation of power grids has been one of the major recent research avenues at the European level. In renewable-based communities aiming to reach some level of energy self-sufficiency, a key issue to be addressed is assessing how the presence of end-users playing different roles in the system (self-consuming, producing and trading, performing demand management, etc.) can influence the overall system performance. In this setting, this paper combines Distributed Artificial Intelligence and optimization approaches to assess how prosumagers and consumers pursuing different goals can influence the energy self-sufficiency of a local energy community. The residential demand is accurately modeled, and the agents’ preferences are considered in the modeling to represent a smart community. The results show that although energy community members may have conflicting individual goals, the overall system self-sufficiency can be maximized with economic benefits for all stakeholders, thus illustrating the advantages of energy communities.

show abstract

“…(iii) Low, medium, and high priority loads: priorities are set according to customer preferences defining the order of which loads are fed with energy. e highest priority demands are satisfied at the beginning, then the medium priority demands, and finally the lowest priority ones [44].…”

Section: Load Scheduling Load Scheduling Is a Part Of The Demand Sidmentioning

confidence: 99%

“…More advanced techniques can be incorporated with rule-based approaches for higher efficiency. We cite as examples artificial neural networks (ANN) [33], fuzzy logic [34], and the adoption of multiagent systems (MAS) [35][36][37]44]. e use of the latter technique has garnered much interest lately.…”

Section: Algorithmsmentioning

confidence: 99%

Energy Management Strategies for Smart Green MicroGrid Systems: A Systematic Literature Review

Essayeh

Fenni

Dahmouni

et al. 2021

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

Having neither precise definition nor a commonly accepted scope, the term “MicroGrid” tends to be used differently across researchers and practitioners alike. The management of energy usage within a microgrid is one of the topics that was handled from numerous perspectives. This study presents systematic literature review (SLR) of research on architectures and energy management techniques for microgrids, providing an aggregated up-to-date catalogue of solutions suggested by the scientific community. The SLR incorporated 45 papers selected according to inclusion/exclusion criteria and defined a priori. The selection process was based on an automated search and covered three known digital libraries. The extraction process covers three main questions. (i) The architectures of microgrids including their components, their bus configuration, and the adopted utility grid policy. (ii) The employed methods to ensure an optimal usage of energy under uncertainty. (iii) The confronted challenges and constraints of the suggested strategies. The findings of this SLR indicate a great diversity of methods and a rich background. Finally, the SLR suggests that future research should take into account the uncertainty aspect relating to energy management rather than the direct use of historical data as it is commonly done in most research papers. A sensitivity analysis should be provided in the latter case.

show abstract

Energy Management in the Smart Grids via Intelligent Storage Systems

Cited by 8 publications

References 27 publications

Cultural Evolution of Sustainable Behaviors: Pro-environmental Tipping Points in an Agent-Based Model

Cultural Evolution of Sustainable Behaviors: Pro-environmental Tipping Points in an Agent-Based Model

Assessing the Influence of Different Goals in Energy Communities’ Self-Sufficiency—An Optimized Multiagent Approach

Energy Management Strategies for Smart Green MicroGrid Systems: A Systematic Literature Review

Contact Info

Product

Resources

About