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An Aggregated Model for Energy Management Considering Crowdsourcing Behaviors of Distributed Energy Resources

Increasing deployment of distributed energy resources (DERs) is re-sculpturing the modern power systems in recent years. Future smart power distribution systems should be competent at accommodating extensive integration of DERs and managing the associated uncertainties at the distribution level. The electricity market has been proved to be an efficient way to employ market signals to direct behaviors of users and DERs with large capacity and homogeneous pattern. However, existing market frameworks cannot effectively handle a large number of small-scale DERs due to their diverse characteristics and arbitrary behavior patterns. In this context, an aggregated model which can represent and manage a diverse collection of DER, load, and storage is proposed. An additional trading platform, namely the energy sharing market, is established to reinforce the coordination and collaboration among various aggregators as well as operators. Energy sharing scheme is applied and a corresponding dynamic dispatch platform is designed to solve the crowdsource problem. The efficiency of the proposed model is validated by the numerical studies, and the market performance and impacts of energy sharing on the power systems are illustrated.
- National Renewable Energy Laboratory United States
- Zhejiang University of Science and Technology China (People's Republic of)
- National Renewable Energy Laboratory United States
- Hefei University of Technology China (People's Republic of)
- Hefei University of Technology China (People's Republic of)
energy management, crowdsourcing behavior, energy sharing, electricity supply industry deregulation, TK1-9971, Distributed power generation, Electrical engineering. Electronics. Nuclear engineering
energy management, crowdsourcing behavior, energy sharing, electricity supply industry deregulation, TK1-9971, Distributed power generation, Electrical engineering. Electronics. Nuclear engineering
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
