Low-carbon economic dispatch considering integrated demand response and multistep carbon trading for multi-energy microgrid

Long, Yilin; Li, Yong; Wang, Yahui; Cao, Yijia; Jiang, Lin; Zhou, Yicheng; Deng, Youyue; Nakanishi, Yosuke

doi:10.1038/s41598-022-10123-0

Cited by 26 publications

(9 citation statements)

References 11 publications

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“…The index reflects the low-carbon level of power operation, product, and the value chain, including 2 secondary indicators: ‘Carbon source flow (SC1)’ and ‘Integrated operation capability (SC2)’. ‘Carbon source flow (SC1)’ includes 2 tertiary indicators: Byproduct recovery rate (SC11) and ‘Carbon emission recovery rate (SC12)’, [ 50 ]. ‘Integrated operation capability (SC2)’ includes 4 tertiary indicators: ‘Power grid material inspection (SC21)’, ‘Storage cluster throughput (SC22)’, ‘Green procurement (SC23)’ and ‘Quality control ability (SC24)’.…”

Section: Methodsmentioning

confidence: 99%

Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019

Ren

Zhang

Fan

2022

IJERPH

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2011–2019 was the critical period of the low-carbon transformation of the power industry, reflecting the deepening influence of market mechanisms. Decarbonization of the new power system is a systematic project that needs to strengthen the top-level design and overall planning. Therefore, the paper first evaluates the decarbonization of the existing power system and controls the grid architecture, power structure, energy utilization, supply chain, and trading market to further optimize the system by strengthening the basic theoretical research of the new power system, exploring the key elements of the low-carbon development of the power system, promoting the breakthrough of the key subjects, and formulating the new power system decarbonization path. In the international push for carbon neutrality goals, identifying key factors in the decarbonization of the power system is critical to achieving low-carbon development in the power sector. Combined with the characteristics and development trends of the power industry, the five dimensions of “Power generation decarbonization (SP)”, “Energy utilization efficiency (EU)”, “Supply chain decarbonization (SC)”, and “Power grid decarbonization (PG)”, and “the Trading system (TS)” are selected to construct an evaluation index system for the power decarbonization and identify the key factors. The Analytic Network Process (ANP) Method is used to calculate the index weight and measure the decarbonization level of the power industry in 30 provinces in China from 2011 to 2019. The evaluation results reveal that the overall decarbonization level of the power industry is on the rise and has stabilized after peaking in 2016. The regression results of the systematic GMM estimation show that “the intensity of cross-regional transmission”, “the degree of carbon market participation”, “technology innovation”, and “policy support” can significantly promote power decarbonization, and different regions have heterogeneity. Therefore, we propose to achieve technological innovation and upgrading in the eastern region, strengthen the construction of smart grids in the central region, optimize the power structure in the western region, and improve the market mechanism as a whole, to form a low-carbon development path for the power industry.

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Section: Methodsmentioning

confidence: 99%

Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019

Ren

Zhang

Fan

2022

IJERPH

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“…The integration of load-side demand response resources with varying response times has been identified as a means to address the capacity constraints of carbon capture facilities [31] and enhance the low-carbon performance of the system. As depicted in Fig.…”

Section: Multi-timescale and Low-carbon Scheduling Framework Based On...mentioning

confidence: 99%

Analysis of low-carbon comprehensive energy system scheduling considering multiple uncertainties

Wang,

Chen,

Luo

et al. 2024

Clean Techn Environ Policy

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Carbon capture systems and the utilization of renewable energy are key ways to reduce carbon emissions, but their uncertainty seriously affects the stable operation and economic efficiency of power systems. To tackle this challenge, a low-carbon economic scheduling model for microgrid electric-thermal integrated energy systems(IES) considering uncertainty is proposed in this paper. The model suggests an ideal dispatch of the IES system that accounts for the disruption of the carbon capture system's integration into the grid belt and plans for the carbon capture plant's low carbon features. Coupling of wind energy with carbon capture power plants employing incentives for system operation and dispatch to incorporate load-side demand response resources. The system's low carbon performance is increased through cooperative source-load resource optimization. A well-established industrial automation optimal dispatch model is developed using YALMIP and CPLEX. The results reveal that the method contributes to the resolution of the system adaptability problem and encourages a balance between low carbon and economics for large loads, taking into account that uncertainty raises the cost by around 3%, thereby boosting system robustness to an acceptable degree.

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“…However, the implementation of an appropriate multi-objective economic emission dispatch system is still an intensively studied topic that requires additional effort to balance the power grid network energy flow in order to support the rapid development of PEVs [62]- [64], commercial flying drones, and other dynamic loads of energy storage devices [65]- [67]. The authors in [68] presented a combined grid stability and cross emissions reduction model for the energy dispatch by considering PEVs to attain the lowest grid operational cost. The presented model can reduce the operational cost and emissions of energy hubs by relocating the transferable electrical loads, such as PEVs, to time intervals when generation costs are low.…”

Section: B Related Workmentioning

confidence: 99%

A Dynamic Optimal Scheduling Strategy for Multi-Charging Scenarios of Plug-in-Electric Vehicles Over a Smart Grid

et al. 2023

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Green transportation has become our top priority due to the depletion of the earth's natural resources and rising pollutant emission levels. Plug-in electric vehicles (PEVs) are seen as a solution to the problem because they are more cost and environment friendly. Due to rapid industrialization and government incentives for zero-emission transportation, a significant challenge is also constituted in power grids by the self-interested nature of PEVs, with the asymmetry of information between the charging power demand and supply sides. In this paper, we propose an optimal strategy in industrial energy management system, based on evolutionary computing, to characterize different charging situations. The proposed approach considers stochastic, off-peak, peak, and electric power research institute charging scenarios for attaining the vehicleto-grid capacity in terms of optimal cost and demand. An extensive scheduling of charging cases is studied in order to avoid power outages or scenarios in which there is a significant supply-demand mismatch. Furthermore, the proposed scheme model also reduces the greenhouse gases emission from generation side to build a sustainable generation infrastructure, which maximizes the utility of fuel-based energy production in the presence of certain nonlinear constraints. The simulation analysis demonstrates that PEVs can be charged and discharged in a systematic manner. The participation of transferable load through the proposed methodology can significantly reduce the economic costs, pollutant impacts, efficiency, and security of power grid operation.INDEX TERMS Energy emission dispatch (EED), industrial energy management system (IEMS), plugin electric vehicle (PEV), plug-in electric vehicle charging coordination (PEVCC), vehicle-to-grid (V2G), valve-point loading effect (VLE)

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Low-carbon economic dispatch considering integrated demand response and multistep carbon trading for multi-energy microgrid

Cited by 26 publications

References 11 publications

Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019

Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019

Analysis of low-carbon comprehensive energy system scheduling considering multiple uncertainties

A Dynamic Optimal Scheduling Strategy for Multi-Charging Scenarios of Plug-in-Electric Vehicles Over a Smart Grid

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