Real-time electricity pricing mechanism in China based on system dynamics

He, Yongxiu; Zhang, Jixiang

doi:10.1016/j.enconman.2015.02.007

Cited by 34 publications

(6 citation statements)

References 23 publications

(22 reference statements)

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“…A sensitivity analysis is next carried out to investigate whether the results of the SD model vary once the related parameters change and to assess which variable has the greatest impact on the model results (Blumberga et al, 2015;He and Zhang, 2015). Four variables are selected for the sensitivity analysis: a coefficient of environmental preferences, a coefficient of rate control, the initial number of the enterprises that implement the carbon reduction labeling scheme, and the total number of the consumers.…”

Section: Sensitivity Analysismentioning

confidence: 99%

For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation

Zhao

Zhou

Han

et al. 2016

Technological Forecasting and Social Change

133

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Section: Sensitivity Analysismentioning

confidence: 99%

For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation

Zhao

Zhou

Han

et al. 2016

Technological Forecasting and Social Change

133

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“…Wang et al [57] presented a simulation that indicated possible gains from real-time pricing in China. The examples of dynamic pricing for China's case were presented by, e.g., He and Zhang [58] and Ma et al [59]. The adjustments in pricing and implementation of smart grids (including support schemes) can be made by considering the demand response functions involving inefficiency term, as suggested by Broadstock et al [60].…”

Section: Smart Grids In Chinamentioning

confidence: 99%

Sustainability in the Electricity Sector through Advanced Technologies: Energy Mix Transition and Smart Grid Technology in China

Baležentis

Štreimikienė

2019

Energies

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In this paper, we integrate technological, institutional, and financial approaches towards expansion of the smart grid technology. We turn to China as the major producer and consumer of energy with an increasing focus on renewables. China’s electricity market has experienced a number of reforms while trying to address the economic and environmental challenges. In order to identify the basic requirements for the Chinese power sector, we look into the underlying trends of the energy mix, regulatory policies, and financial flows. Understanding these facets allows one to suggest directions for the further development of the Chinese power sector in the light of the smart grid concept. Indeed, the smart grid concept has no strict definition and, therefore, requires simultaneous consideration of multiple factors. The analysis shows that ensuring smooth transfer of electricity across the regions is a quintessential condition for smart grid development and the promotion of renewable energy in China. As the role of the state-owned enterprises still remains the most important one in the sector, private initiatives should be supported. Therefore, financial incentives are needed to guide the shifts in the energy mix and maintain efficient energy generation and consumption in China.

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“…Regarding the bidding strategy of the electricity market, scholars at home and abroad have conducted many studies. In real-time market bidding, He and Zhang [5] used system dynamics simulation to predict dynamic real-time electricity price levels. Jia et al [6] used deep reinforcement learning methods to dynamically learn incomplete information in the electricity market and predict the strategies of competitors.…”

Section: Introductionmentioning

confidence: 99%

Bidding strategy of thermal power compound differential evolution game under the market mechanism of peak regulation auxiliary service

Dong

et al. 2021

IET Generation Trans & Dist

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As the main provider of peak regulation auxiliary services, thermal power units are particularly important to ensure their revenue in an uncertain environment. To obtain the optimal bidding strategy for thermal power units, a thermal power peak regulation bidding model based on the Northeast Power Grid's auxiliary service market bidding mechanism is established. Secondly, the evolutionary game theory is introduced into the bidding strategy of thermal power units. Meanwhile, in order to solve the multi-party game problem, a compound differential evolution game algorithm is constructed to solve the two-tiers bidding. Finally, based on the actual operating data of a typical day, the efficiency of the compound differential evolution game algorithm bidding strategy is verified, and the bidding strategy of thermal power units in different situations is discussed. The results show that when all units participate in peak regulation, the first-tier quotation is an optimal strategy at 0.19 yuan kWh −1 and below, and the second-tier quotation is distributed between 0.6-0.8 yuan kWh −1. When only some units are involved in peak regulation, the first-tier quotation of thermal power units adopts a high price strategy, mostly at 0.3 yuan kWh −1 , and the second-tier quotation is still based on a high price strategy.

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Real-time electricity pricing mechanism in China based on system dynamics

Cited by 34 publications

References 23 publications

For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation

For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation

Sustainability in the Electricity Sector through Advanced Technologies: Energy Mix Transition and Smart Grid Technology in China

Bidding strategy of thermal power compound differential evolution game under the market mechanism of peak regulation auxiliary service

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