Overhead transmission lines dynamic rating estimation for renewable energy integration using machine learning

Sobhy, Abdelrahman; Megahed, Tamer F.; Abo‐Zahhad, Mohammed

doi:10.1016/j.egyr.2021.07.060

Cited by 10 publications

(2 citation statements)

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“…While taking the maximum renewable energy accommodation capacity as the optimization goal, this paper also considers the constraints of power balance, system reserve capacity, thermal power unit output, thermal power unit ramping, and other constraints to simulate the actual operation of the power grid point by point. The system's spinning reserve capacity constraint is expressed as follows: (11) where P j max (t, n) is the percentage of the maximum output of the jth type unit in the sub-grid n at time t to the installed capacity. S j (t, n) is the number of the jth type unit operating in the sub-grid n at the time t. P l (t, n) is the total load in the district grid n at the time t. P re and N re are the positive and negative spare capacity of the system, respectively.…”

Section: Optimization Modelmentioning

confidence: 99%

“…In the second type of research, [9,10] realized the improvement of renewable energy accommodation capacity by considering the demand response mechanism in the power grid. In [11], this paper proposes a new machine-learning-based method to determine the capacity of the grid to accommodate renewable energy by estimating the transmission capacity of the power line. Ref.…”

Section: Introductionmentioning

confidence: 99%

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Research on Renewable-Energy Accommodation-Capability Evaluation Based on Time-Series Production Simulations

Zhou

Zhang

Dan³

et al. 2022

Energies

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In recent years, renewable energy has received extensive attention due to its advantages of sustainability, economy, and environmental protection. However, with the rapid development of renewable energy, the problem of curtailment is becoming increasingly serious. Studying the calculation method and establishing a quantitative evaluation system of renewable energy accommodation capacity are important means to solve this problem. This paper comprehensively considers the factors affecting the accommodation of renewable energy, establishes a accommodation calculation model with the maximum accommodation of renewable energy as the optimization target based on the time series production simulation method, and uses the hybrid particle swarm optimization (PSO) algorithm to solve it. The model is verified with historical data such as load, photovoltaic (PV), and wind power in a certain region throughout the year. The experimental results verify the rationality of the renewable-energy accommodation-capacity model proposed in this paper and the correctness of the theoretical analysis. The calculation results have important reference and guiding significance for the operation and control of power-grid planning and dispatching.

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Section: Optimization Modelmentioning

confidence: 99%