Design of Hydropower Dominated Provincial Electricity Spot Markets in China

Cai, Zhi; Zhang, Chuancheng; Hu, Xiaojing; Zhang, Guofang; Lu, Yi

doi:10.1109/icpee51316.2020.9311053

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…As the electrical market develops, three main policy objectives are being pursued: supply security, enhanced economic efficiency, and environmental regulation implementation [11,12]. In order to distribute market benefits as far as feasible and to enable all market players to gain from high-quality services, all policies are created and carried out with these three factors in mind.…”

Section: Introductionmentioning

confidence: 99%

Optimization Research on Provincial Users' Participation in Regional Electricity Spot Market Bidding Based on Hierarchically Gated Recurrent Neural Network

Jinqing Luo

2024

jes

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The creation of strategic pricing models is crucial in the highly competitive centralized energy markets in order to maximize revenues. In order to achieve maximum profit, market participants must act intelligently while bidding on electrical energy purchases or sales. Notwithstanding the many restructuring changes of the Chinese electricity sector, market participants are nonetheless exposed to risks associated with volatility in market prices and uncertainty over demand behavior. The data are collected from New South Wales electricity market. Data-adaptive Gaussian average filtering (DAGAF) is used to pre-process the data during the pre-processing step. Hierarchically Gated Recurrent Neural Networks (HGRNNs) are successfully used to classify both long-term and spot transactions. The neural network's weight parameter is optimized by the Lotus Effect Optimization Algorithm (LEA), which enhances the HGRNN. The RESMB-HGRNN-LEA proposed is implemented on the Python working platform. To calculate the suggested approach, performance measures including accuracy, precision, sensitivity, computation time, and recall were looked at.In comparison to the existing technique, the proposed RESMB-HGRNN-LEA method yields better results in terms of accuracy (16.65% and 18.85%), sensitivity (16.34% and 12.23%), precision (14.89% and 16.89%), and computing time (82.37% and 94.47%).

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Section: Introductionmentioning

confidence: 99%

Optimization Research on Provincial Users' Participation in Regional Electricity Spot Market Bidding Based on Hierarchically Gated Recurrent Neural Network

Jinqing Luo

2024

jes

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“…In 2017, the construction of the spot market was started under the new round reform of China's electricity market. Eight provinces (i.e., Shanxi, Zhejiang, Guangdong, Sichuan, West Inner Mongolia, Shandong, Fujian, and Gansu) were selected by the National Development and Reform Commission (NDRC) as the first batch of spot market trial operation areas (Cai et al, 2020). After that, each province conducted multiple rounds of continuous settlement trial operations.…”

Section: Introductionmentioning

confidence: 99%

Opinions on unbalanced funds in China’s electricity market

Zhu

Yin

et al. 2023

Front. Energy Res.

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“…In short-term generation scheduling, the electricity price in the dayahead (Golmohamadi et al, 2021;Lago et al, 2021;Tschora et al, 2022) market is another important factor that is influenced by the load and nodal blockage in each receiving province. Currently, hydropower simultaneously faces long-term trading and shortterm spot markets (Cai et al, 2020;Jia et al, 2022). The former involves both priority electricity and market trading, and the latter has to meet complex hydraulic connections and constraints, as well as market limitations (Guo et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Market bidding method for the inter-provincial delivery of cascaded hydroelectric plants in day-ahead markets considering settlement rules

Han,

Shen,

Cheng

2023

Front. Energy Res.

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Chinese electricity market reform poses huge challenges to hydropower operations and electricity trading. This study proposes a scheduling method coupling priority electricity and day-ahead trading for large hydropower plants. The study focuses on complex factors such as tariff uncertainty, different types of electricity settlement rules, and inter-provincial electricity transmission links. Spot market tariff scenarios are determined through the Latin hypercube and the K-means methods. A performance formulation of priority electricity deviation considering settlement assessment rules is established. A transmission description for different sub-plants and a triangular linear interpolation method based on binary independent branching mode are proposed to solve inter-regional transmission connections and hydraulic coupling in cascaded hydropower plants, respectively. Finally, the Big M method is employed to equivalently transform the complex non-linear problem into a mixed-integer linear programming (MILP) model. The method is verified with the day-ahead operation of four large hydropower plants downstream of the Jinsha River in China as a case study. Settlement assessment rules, inter-regional power transmission, and price uncertainty are analyzed in three different cases. Three conclusions are obtained: 1) the priority electricity performance rate and the price are positively correlated, which is useful to guide hydropower plants to actively participate in the market. 2) Introducing the prediction error of electricity price in the model can help avoid market decision risk and improve the expected return by approximately 1.2%. 3) Considering the settlement penalty rule is helpful for power generation enterprises to improve power allocation and thus seek higher revenue compared to traditional methods without considering it.

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Design of Hydropower Dominated Provincial Electricity Spot Markets in China

Cited by 8 publications

References 4 publications

Optimization Research on Provincial Users' Participation in Regional Electricity Spot Market Bidding Based on Hierarchically Gated Recurrent Neural Network

Optimization Research on Provincial Users' Participation in Regional Electricity Spot Market Bidding Based on Hierarchically Gated Recurrent Neural Network

Opinions on unbalanced funds in China’s electricity market

Market bidding method for the inter-provincial delivery of cascaded hydroelectric plants in day-ahead markets considering settlement rules

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