Low carbon economic dispatch for virtual power plant considering energy storage DOI
Junxiang Li, Mingxing Huang,

Deqiang Qu

et al.

International Journal of Green Energy, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Dec. 28, 2024

Virtual power plant (VPP) amalgamates diverse distributed resources, thereby unlocking the full potential of energy's dispatch capabilities. Energy storage is an effective means to address uncertainty renewable energy and achieve complementarity. This study meticulously evaluates finite nature traditional within VPP, unpredictability associated with outputs, constraints faced by devices. It introduces strategic operational frameworks for VPP through cooperation between operator provider managing new type electric systems. With dual objectives amplifying economic gains maximizing benefits provider, this research formulates a low-carbon model, guided carbon tax framework. The improved particle swarm optimization algorithm used solve proposed model. numerical results confirmed that collaboration mitigates issues caused variability outputs on resulting in mutually beneficial scenario both provider. Additionally, emissions have been drastically decreased response low targets.

Language: Английский

Low carbon economic dispatch for virtual power plant considering energy storage DOI
Junxiang Li, Mingxing Huang,

Deqiang Qu

et al.

International Journal of Green Energy, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Dec. 28, 2024

Virtual power plant (VPP) amalgamates diverse distributed resources, thereby unlocking the full potential of energy's dispatch capabilities. Energy storage is an effective means to address uncertainty renewable energy and achieve complementarity. This study meticulously evaluates finite nature traditional within VPP, unpredictability associated with outputs, constraints faced by devices. It introduces strategic operational frameworks for VPP through cooperation between operator provider managing new type electric systems. With dual objectives amplifying economic gains maximizing benefits provider, this research formulates a low-carbon model, guided carbon tax framework. The improved particle swarm optimization algorithm used solve proposed model. numerical results confirmed that collaboration mitigates issues caused variability outputs on resulting in mutually beneficial scenario both provider. Additionally, emissions have been drastically decreased response low targets.

Language: Английский

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