Decentralization of renewable energy sources based optimum scheduling and management through a virtual power plant

Abstract In this paper, renewable resources and co-generation units are grouped together to perform optimized operational scheduling in a virtual power plant (VPP) system. Renewable sources consist of solar photovoltaic, wind, and fuel cell units that are equipped together with a cogenerating unit to intensify the system's dependency in case of power shortage from renewable sources. The uncertainty aspect is investigated for the developed system as renewables are associated, and its impact on network operation is discussed. Storage provision is facilitated in the form of flexible and spinning reserves in which electric vehicle (EV) and energy storage systems (ESS) increase the system reliability by ensuring continuity of power supply. Optimal scheduling is carried out from both economic and environmental perspectives in which the net profit of the system is improved and the generated emissions are reduced by considering dual scheduling i.e., day-ahead (DA) and proposed 15 min interval. Moreover, a nature-inspired metaheuristic red fox optimization (RFO) is employed to handle the VPP problem and the results with the context to net profit and emission are also compared with work available in the literature. Finally, the proposed approach is promising in terms of higher computational efficacy and reveals the suitability of the VPP system.

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Publication Details

Journal
Environmental Research Communications
Published
2024-11-01
DOI
https://doi.org/10.1088/2515-7620/ad9087
Citations
12
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
2.50

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article

Decentralization of renewable energy sources based optimum scheduling and management through a virtual power plant

N. S. Jayalakshmi, Manohar Singh, Vinay Kumar Jadoun, Anubhav Kumar Pandey
12 citations
Environmental Research Communications
Smart Grid Energy Management
2.50
article

Decentralization of renewable energy sources based optimum scheduling and management through a virtual power plant

N. S. Jayalakshmi, Manohar Singh, Vinay Kumar Jadoun, Anubhav Kumar Pandey
article en
12 citations

Abstract

Abstract In this paper, renewable resources and co-generation units are grouped together to perform optimized operational scheduling in a virtual power plant (VPP) system. Renewable sources consist of solar photovoltaic, wind, and fuel cell units that are equipped together with a cogenerating unit to intensify the system's dependency in case of power shortage from renewable sources. The uncertainty aspect is investigated for the developed system as renewables are associated, and its impact on network operation is discussed. Storage provision is facilitated in the form of flexible and spinning reserves in which electric vehicle (EV) and energy storage systems (ESS) increase the system reliability by ensuring continuity of power supply. Optimal scheduling is carried out from both economic and environmental perspectives in which the net profit of the system is improved and the generated emissions are reduced by considering dual scheduling i.e., day-ahead (DA) and proposed 15 min interval. Moreover, a nature-inspired metaheuristic red fox optimization (RFO) is employed to handle the VPP problem and the results with the context to net profit and emission are also compared with work available in the literature. Finally, the proposed approach is promising in terms of higher computational efficacy and reveals the suitability of the VPP system.

Environmental Research CommunicationsVol. 6(11)
Manipal Academy of Higher Education (IN), Punjab Engineering College (IN), Dr. Hari Singh Gour University (IN)
Department of Science and Technology, Ministry of Science and Technology, India
Affordable and clean energy
Openalex Percentile: Top 10%
Smart Grid Energy Management
2.50
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Decentralization of renewable energy sources based optimum scheduling and management through a virtual power plant — N. S. Jayalakshmi, Manohar Singh, et al. · Environmental Research Communications (2024) | TGRS Research Map | TGRS