2019
DOI: 10.1016/j.solener.2019.08.040
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An agent-based approach to modeling zero energy communities

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Cited by 41 publications
(47 citation statements)
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“…With the transition from vertically integrated utilities to deregulated electricity markets, power systems' complexity is increasing, namely because new rules and players are emerging and being implemented. Distributed generation (smart grid and microgrids) (Farhangi 2010), EVs (Tan, Ramachandaramurthy, and Yong 2016), consumption flexibility and DR processes (Faria, Spínola, and Vale 2016), large penetration of renewable-based generation (Calabria, Saraiva, and Rocha 2016), energy efficiency measures (Zhou et al 2016), and building energy management (Mittal et al 2019), among many others, contribute to the increasing management and operation complexity, the transmission and distribution networks and the interactions between traditional and new players. The uncertainties associated with the renewable-based generation, electricity market prices, energy consumption, or EVs are just a few examples of the increased sources of uncertainty and thus of complexity brought to the power and the energy sector.…”
Section: Abm In Power Systems -Literature Reviewmentioning
confidence: 99%
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“…With the transition from vertically integrated utilities to deregulated electricity markets, power systems' complexity is increasing, namely because new rules and players are emerging and being implemented. Distributed generation (smart grid and microgrids) (Farhangi 2010), EVs (Tan, Ramachandaramurthy, and Yong 2016), consumption flexibility and DR processes (Faria, Spínola, and Vale 2016), large penetration of renewable-based generation (Calabria, Saraiva, and Rocha 2016), energy efficiency measures (Zhou et al 2016), and building energy management (Mittal et al 2019), among many others, contribute to the increasing management and operation complexity, the transmission and distribution networks and the interactions between traditional and new players. The uncertainties associated with the renewable-based generation, electricity market prices, energy consumption, or EVs are just a few examples of the increased sources of uncertainty and thus of complexity brought to the power and the energy sector.…”
Section: Abm In Power Systems -Literature Reviewmentioning
confidence: 99%
“…An agent-based approach to model zero energy communities is described in Mittal et al (2019). This paper details a conceptual ABM for an urban neighborhood to predict the household level of adopting renewable energy behaviors in the presence of multiple options.…”
Section: Energy Communitiesmentioning
confidence: 99%
“…The profiles of User2, User3 and User4 in Figure 9 are both positive and negative. Profiles are positive during the daytime from 09:00 a.m. to 15:00 p.m. (9)(10)(11)(12)(13)(14)(15) as the local generation exceeds the local demand; they export power to the electricity grid for the entire interval 9-15 with the exception of short time intervals (i.e., lunch-time) during which the use of domestic appliances determines the inversion of the power flow at the meter.…”
Section: Energetic Analysis: Case0 None Electric Vehicle Bussiness mentioning
confidence: 99%
“…To this end, the economic benefits of the new business models for generating [8] and peer-to-peer exchanging energy [9] within the community are good levers. Energy communities, if local, better identify energy 2 of 18 needs and better manage energy exchanges in urban neighborhoods [10] and municipalities [11,12] as well, especially when the energy community operates the electrical distribution grids [13].…”
Section: Introductionmentioning
confidence: 99%
“…Energy communities could lead to the achievement of net-zero energy neighborhoods rather than buildings by increasing the self-consumption. Marique et al [11] and Mittal et al [12] have highlighted the opportunities of achieving zero-energy consumption by developing a framework for net-zero energy neighborhoods. In an energy consumption scenario analysis involving typical central European neighborhood typologies, Nematchoua et al (2021) have reported a 90% reduction of actual energy consumption at the neighborhood scale.…”
Section: Introductionmentioning
confidence: 99%