Optimal Configuration of Converter Capacity in AC/DC Hybrid Distribution Network Considering Overload Risk

Liu, Yundong; Zhang, Guoxing; Weng, Zhiying; Xu, Xianglian

doi:10.1109/icpes51309.2020.9349746

Cited by 2 publications

(2 citation statements)

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“…To optimize the performance of the MDP, the power interval of a certain confidence level was obtained by confidence interval estimation. The confidence interval could be solved according to Equation ( 14) [34,35]:…”

Section: Renewable-energy Uncertaintymentioning

confidence: 99%

“…In addition, in order to handle the uncertainty of photovoltaics according to Section 3.2.2, in this paper, the photovoltaic output is divided into three segments, (0, 0.3], (0.3, 0.6] and (0.6, 1], and applies a Gaussian mixture to fit the output prediction errors in different segments. The available photovoltaic output was obtained by solving the confidence interval of 95% [34], as shown in Figure 7.…”

Section: Basic Scenario and Datamentioning

confidence: 99%

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Assessing the Effects of Tradable Green Certificates and Renewable Portfolio Standards through Demand-Side Decision-Making Simulation: A Case of a System Containing Photovoltaic Power

Wang

et al. 2023

Energies

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Understanding the effect of a tradable green certificate (TGC) and renewable portfolio standard (RPS) policy mix is of great importance for sustainable renewable-energy development and carbon neutrality, given that the demand side subjects are the responsible subjects under China’s RPSs and studies from the demand-side perspective are relatively limited. To fill this gap, this paper analyzes the coupled relationship between the TGC market and the electricity market as well as the reflexivity of the TGC market. Meanwhile, on the basis of modeling TGC prices and renewable-energy uncertainty, this paper constructs a Markov decision process (MDP) model to simulate the sequential decision-making process of the demand side and further proposes a solution model based on dynamic programming and evolutionary algorithms. The results show that: (1) In addition to policy parameters such as RPS weight, TGC price caps and penalties, a preference for short-term benefits and renewable-energy uncertainty also affect transaction behaviors on the demand side. (2) Increasing RPS weight within an appropriate range can stimulate demand for renewable power and TGC, while excessively low RPS weight will result in accumulation of unsold TGC. In addition, the preference for short-term benefits can stimulate demand for renewable power and curb demand for TGC. (3) An increase in the TGC price cap can stimulate demand for renewable power and restrain demand for TGC, but this phenomenon may not exist when RPS weight is too low or responsible subjects prefer short-term benefits. (4) Setting a penalty of no less than the TGC price cap is of great significance to ensure the operation of the TGC market and RPSs.

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Section: Renewable-energy Uncertaintymentioning

confidence: 99%

Section: Basic Scenario and Datamentioning

confidence: 99%