A stochastic multi-interval scheduling framework to quantify operational flexibility in low carbon power systems

Yamujala, Sumanth; Kushwaha, Priyanka; Jain, Anjali; Bhakar, Rohit; Wu, Jianzhong; Mathur, Jyotirmay

doi:10.1016/j.apenergy.2021.117763

Cited by 18 publications

(1 citation statement)

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“…Nevertheless, this work suffers great limitations in the case where a large variety of renewable energy occurs in the power system, due to the failure of the linearization model. In low-carbon power systems, an index based on operating range and ramping was utilized to quantify operational flexibility (Yamujala et al, 2021). Considering the transmission capacity and energy conversion constraints, the flexibility margin index was proposed to evaluate the flexibility from the aspect of the acceptable wind power fluctuations range (Zhao et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Low-Carbon and economic flexibility scheduling of power system with multiple generation resources penetration

Zhang

Wang

et al. 2023

Front. Energy Res.

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The operation flexibility of the power system suffers great challenges due to the vigorously developing of renewable energy resources under the promotion of the carbon neutralization goal. To this end, this paper proposes an economical and flexible energy scheduling method for power system integrated with multiple generation resources while considering the operation of low-carbon. Specifically, flexibility evaluation indexes are constructed to describe the characteristics of the flexible generation units. Then they are connected with the flexibility of the power system in an economic and low-carbon flexible energy scheduling model. To coordinate the operation economy, flexibility, and carbon emission reduction, the model incorporates demand response, operational characteristics, and flexibility requirements. Further, the model is fully validated through the simulation on the modified IEEE 30-bus system. Results demonstrate that: the proposed method can reduce the system’s carbon emission and total operating costs and promote photovoltaic consumption.

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Section: Introductionmentioning

confidence: 99%