Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading

Tan, Qinliang; Ding, Yong; Ye, Qi; Mei, Shufan; Zhang, Yimei; Wei, Yongmei

doi:10.1016/j.apenergy.2019.113598

Cited by 54 publications

(16 citation statements)

References 31 publications

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“…After weighting by entropy method, we get that the weights of indicators in the index system are w pg , w hc , w ic , w l . Then the weighted sum can be used to get the compound score I i of each province: I i = w pg I pg + w hc I hc + w ic I ic + w l I l (4) where I pg , I hc , I ic , I l are the quota allocation values of per capita GDP, historical cumulative carbon emissions, carbon emissions per unit of industrial added value, and employment indicators, respectively. Finally, the distribution of provincial carbon quotas in 2030 is equal to:…”

Section: Residents' Welfare Employmentmentioning

confidence: 99%

Provincial Carbon Emission Quota Allocation Study in China from the Perspective of Abatement Cost and Regional Cooperation

et al. 2020

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To achieve the carbon reduction target, the Chinese government not only requires a quota allocation scheme in line with the current development situation, but also needs to minimize the economic expenditure in the emission reduction work. Therefore, this study integrates the multi-index method and zero-sum gains–data envelopment analysis model to obtain a fair and efficient multi-criteria quota allocation scheme. To ensure the effectiveness of the scheme, the fairness and cost effect of the scheme are quantitatively tested. In addition, regional cooperation factors are introduced into the research framework to providing feasible practical measures. The results show that: (1) After optimization, the eastern region has the largest quota increment, accounting for 45% of the country’s quota. (2) The multi-criteria quota allocation scheme after secondary allocation is a more ideal scheme. The quota scheme not only meets the requirements of fairness and efficiency, but also has lower abatement costs. (3) Regional cooperation should be encouraged by China, especially the eastern region, which can alleviate the reducing emission pressure through cooperation. Although the western region needs to undertake additional emission reduction tasks, it can improve the utilization rate of local renewable resources and be conducive to long-term economic development. These results will provide a reference for China to achieve its carbon reduction targets.

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Section: Residents' Welfare Employmentmentioning

confidence: 99%

Provincial Carbon Emission Quota Allocation Study in China from the Perspective of Abatement Cost and Regional Cooperation

et al. 2020

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“…However, the addition of the renewable energy systems requires the upgradation of the optimization problem to include the effect of the distributed generation systems to the conventional grid. The work in [19] suggests the dispatch of a hybrid energy system consisting of wind, thermal and PV energy source. The authors consider the different modes for the dispatch problem such as the low emission mode, the energy saving mode and the high efficiency mode of operation for the suggested hybrid energy system.…”

Section: A Relevant Literaturementioning

confidence: 99%

“…The references [19]- [26] discuss the economic dispatch of the hybrid energy systems without providing any mathematical details for obtaining the used forecast results in their findings for distributed generation sources. The authors in [27] have suggested an efficient methodology to compute the solar forecast results, but their findings are limited to a single PV plant and total scheduling duration of nine hours.…”

Section: B Research Gapmentioning

confidence: 99%

Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

et al. 2021

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“…In [30], a decentralized economic dispatch was proposed by considering the carbon capture power plants with carbon emission trading. Moreover, the power uncertainty of wind and photovoltaic energy was fully taken into account in [31,32] based on carbon emission trading. For the purpose of clarifying the internal relation between energy consumption and carbon emissions from power grids, the concept of carbon emission flow is put forward for the first time in reference [33].…”

Section: Low-carbon Powermentioning

confidence: 99%

Multi-Agent Cooperation Based Reduced-Dimension Q(λ) Learning for Optimal Carbon-Energy Combined-Flow

Gao

et al. 2020

Energies

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This paper builds an optimal carbon-energy combined-flow (OCECF) model to optimize the carbon emission and energy losses of power grids simultaneously. A novel multi-agent cooperative reduced-dimension Q(λ) (MCR-Q(λ)) is proposed for solving the model. Firstly, on the basis of the traditional single-objective Q(λ) algorithm, the solution space is reduced effectively to shrink the size of Q-value matrices. Then, based on the concept of ant cooperative cooperation, multi-agents are used to update the Q-value matrices iteratively, which can significantly improve the updating rate. The simulation in the IEEE 118-bus system indicates that the proposed technique can decrease the convergence speed by hundreds of times as compared with conventional Q(λ), keeping high global stability, which is very suitable for dynamic OCECF in a large and complex power grid compared with other algorithms.

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Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading

Cited by 54 publications

References 31 publications

Provincial Carbon Emission Quota Allocation Study in China from the Perspective of Abatement Cost and Regional Cooperation

Provincial Carbon Emission Quota Allocation Study in China from the Perspective of Abatement Cost and Regional Cooperation

Application of Dynamically Search Space Squeezed Modified Firefly Algorithm to a Novel Short Term Economic Dispatch of Multi-Generation Systems

Multi-Agent Cooperation Based Reduced-Dimension Q(λ) Learning for Optimal Carbon-Energy Combined-Flow

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