A multi-region optimization planning model for China’s power sector

Rui, Cheng; Xu, Z.; Liu, Pei; Wang, Zhe; Li, Zheng; Jones, Ian S.

doi:10.1016/j.apenergy.2014.10.023

Cited by 113 publications

(45 citation statements)

References 18 publications

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“…In the proposed model, China's power sector is divided into 10 regions, reflecting the current physical structure of regional high voltage transmission networks [24]. As shown in Fig.…”

Section: Model Structurementioning

confidence: 99%

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Substitution effect of renewable portfolio standards and renewable energy certificate trading for feed-in tariff

et al. 2018

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• The substitution effect of RPS and REC trade for the FIT was calculated and analyzed.• A multi-region power market model was proposed and developed.• REC trade can reduce the government's expenditure on subsidies for renewable energy.• FIT subsidy provides guarantees of the local power sectors' profit.• RPS, REC trade and FIT subsidy need to be considered together. A R T I C L E I N F O Keywords:Renewable portfolio standard Renewable energy certificate Feed-in tariff Subsidies A B S T R A C TThe Feed-in Tariff (FIT) has been successfully used to promote the development of renewable energy; nevertheless, it may cause financial burden on the governments at the same time. Compared with FIT, Renewable Portfolio Standards (RPS) and the Renewable Energy Certificate (REC) trading have been considered to reduce the government's expenditure caused by the subsidization. To examine the effectiveness of RPS and REC trading, the development of renewable energy and the environmental and economic benefits under different policies have been quantitatively investigated by using a multi-region power market model and China has been chosen as a case study. The obtained results show that: (i) REC trading can efficiently reduce the government's expenditure on subsidies for the development of renewable energy; (ii) Compared to FIT, RPS and REC trading will reduce the power sectors' profit; and (iii) RPS and REC trading may not be enough to achieve the target on renewable energy especially when the capital cost is high, therefore, RPS, REC trade and FIT subsidy should be implemented as complementary policies, not independent.

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“…In the proposed model, China's power sector is divided into 10 regions, reflecting the current physical structure of regional high voltage transmission networks [24]. As shown in Fig.…”

Section: Model Structurementioning

confidence: 99%

“…A detailed prediction of regional power demand is conducted based on the future possible macroeconomic slowdown given in [24]. The forecast regional electricity demand to 2020 [32] is shown in Fig.…”

Section: Electricity Demandmentioning

confidence: 99%

Substitution effect of renewable portfolio standards and renewable energy certificate trading for feed-in tariff

et al. 2018

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“…The popularization rate of each type of technology should be set as a non-negative variable, as is shown in Equation (12). The retrofits of coal-fired and gas-fired power plants can be implemented at once, so the popularization rates of these technologies are 0 or 100% (Equation (13)…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…It can be noted that, in the literature mentioned above [3,[11][12][13][14], all parameters in the models are fixed. However, this is not real under tremendously complex environments which are full of uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…Ye et al [11] built a multi-period optimization model for China's power sector with considerations of SO 2 , NO X , and CO 2 emission control. Cheng et al [12] proposed a multi-region optimization model and considered how investment decisions to expand and alter the existing generation mix could be optimized across a timeframe from 2011 to 2050. Chen et al [13] developed a deterministic linear programming model with consideration of the non-carbon externalities and applied it to China's power sector for the period from 2015 to 2030.…”

Section: Introductionmentioning

confidence: 99%

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A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China

2017

Sustainability

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Abstract:In order to solve problems caused by climate change, countries around the world should work together to reduce GHG (greenhouse gas) emissions, especially CO 2 emissions. Power demand takes up the largest proportion of final energy demand in China, so the key to achieve its goal of energy-saving and emission reduction is to reduce the carbon emissions in the power sector. Taking Shenzhen as an example, this paper proposed a stochastic optimization model incorporating power demand uncertainty to plan the carbon mitigation path of power sector between 2015 and 2030. The results show that, in order to achieve the optimal path in Shenzhen's power sector, the carbon mitigation technologies of existing coal and gas-fired power plants will be 100% implemented. Two-thirds and remaining one-third of coal-fired power plant capacities are going to be decommissioned in 2023 and 2028, respectively. Gas-fired power, distributed photovoltaic power, waste-to-energy power and CCHP (Combined Cooling, Heating, and Power) are going to expand their capacities gradually.

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Optimal Planning of Electric Power Systems

Abdin¹,

Zio²

2019

Optimization in Large Scale Problems

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A multi-region optimization planning model for China’s power sector

Cited by 113 publications

References 18 publications

Substitution effect of renewable portfolio standards and renewable energy certificate trading for feed-in tariff

Substitution effect of renewable portfolio standards and renewable energy certificate trading for feed-in tariff

A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China

Optimal Planning of Electric Power Systems

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