A Framework for Qualifying and Evaluating Smart Grids Approaches: Focus on Multi-Agent Technologies

Basso, Gillian; Gaud, Nicolas; Gechter, Franck; Hilaire, Vincent; Lauri, Fabrice

doi:10.4236/sgre.2013.44040

Cited by 30 publications

(16 citation statements)

References 18 publications

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“…Like Netlogo it is free and open source which enables users to extend the domain specific language. Some ABM frameworks are specialized even further (e.g., for smart grids [333]) but we would warn against their use because it inhibits the development of integral models [176].…”

Section: Learn From Professional Programmersmentioning

confidence: 99%

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

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Section: Learn From Professional Programmersmentioning

confidence: 99%

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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“…More information on Direct Energie via www.directenergie.com3 See press release http://www.ecoco2.com/blog/10450-direct-energiepremier-fournisseur-agree-pour-leffacement-diffus4 More information on Flextricity via www.flextricity.com…”

mentioning

confidence: 99%

Aggregation of demand side flexibility in a smart grid: A review for European market design

Eid

Codani

Chen

et al. 2015

2015 12th International Conference on the European Energy Market (EEM)

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International audienceThe increased share of renewable generation and the integration of Distributed Generation (DG) require more electricity system flexibility. One way to increase this flexibility is to use the potentials of demand response (DR). In order to activate the full range of customers in DR, a new market intermediary actor is needed to aggregate the resources in an adequate technical and economical format. These actors, so called " aggregators " , can act as flexibility providers to support security of supply considering network, generation and consumers constraints. However, despite their technical and economical utility, aggregators are not self-emerging in many European countries. Consequently, this paper aims at identifying the main barriers accounting for this lack of aggregators in Europe. Eventually this paper provides a policy review for European market designs that support aggregation

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“…The problem of energy management in a microgrid includes many subissues such as demand management, production management, systems management, storage and network stability (Vasiljevska et al, 2013;Basso et al, 2013).…”

Section: Case Studymentioning

confidence: 99%

Engineering multi-agent systems using feedback loops and holarchies

Basso

Cossentino

Hilaire

et al. 2016

Engineering Applications of Artificial Intelligence

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A Framework for Qualifying and Evaluating Smart Grids Approaches: Focus on Multi-Agent Technologies

Cited by 30 publications

References 18 publications

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Aggregation of demand side flexibility in a smart grid: A review for European market design

Engineering multi-agent systems using feedback loops and holarchies

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