Low-carbon economic optimal dispatch strategy of integrated energy system considering electric-heat flexible load and carbon trading

Jiang, Xin; Ai, Qian; Chen, Yun; Wang, Jiayu

doi:10.1109/ispec54162.2022.10033052

Cited by 11 publications

(12 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equipment parameters and electricity/ heat prices refer to [8]. The parameters related to carbon trading are referred to [9]. The iterative convergence of the distributed optimal scheduling of microgrids is shown in figure 2.…”

Section: Multi-microgrid Distributed Optimal Scheduling Modelmentioning

confidence: 99%

A distributed low-carbon dispatch model for regional multi-integrated energy microgrids considering carbon trading

Zhao,

Xiang,

Liu

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

View full text Add to dashboard Cite

Integrated energy microgrids, as an important means of realizing coupled and complementary energy sources, are of great significance in promoting the transformation of the energy structure and accelerating the realization of the dual-carbon goal. In the same region, the energy interaction of multi-microgrids can realize energy mutualization, improve the level of new energy consumption and reduce carbon emissions. Based on this, this paper proposes a regional multi-microgrid distributed dispatch model. A single microgrid scheduling model based on carbon trading mechanism is established. On this basis, a multi-microgrid cooperative operation model is proposed considering the energy sharing of multi-microgrids. Finally, a consensus-based ADMM algorithm is used for distributed scheduling of multiple microgrids. The arithmetic example verifies the effectiveness of the proposed model.

show abstract

Section: Multi-microgrid Distributed Optimal Scheduling Modelmentioning

confidence: 99%

A distributed low-carbon dispatch model for regional multi-integrated energy microgrids considering carbon trading

Zhao,

Xiang,

Liu

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

View full text Add to dashboard Cite

show abstract

“…The relationship between load rate and efficiency of HPS is shown in figure 2 [7]. Where L is the load rate, η is the actual efficiency, and η* is the rated efficiency.…”

Section: Optimize Control Strategymentioning

confidence: 99%

Intelligent Optimal Control Strategy of Heat Pump System Based on Digital Twins

Zhang

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

In the context of the digital transformation of the power grid, digital twins, as one of the key technologies to promote the digital and intelligent development of the power industry, are still in the theoretical research stage. Focusing on the application of digital twin technology in the power industry, an intelligent optimal control strategy for heat pump system (HPS) based on digital twin technology is proposed. Firstly, the DOE-2 model of HPS and the prediction model of building heat load are established. Secondly, based on the real-time monitoring data, the improved quantum particle swarm optimization algorithm is used for the rolling optimization of model parameters. Finally, the optimal control strategy of the HPS is formulated based on the comprehensive consideration of energy consumption, the number of startups and shutdowns, and the temperature control requirements of the HPS. The example results show that the digital twin model has high accuracy. Compared with the manual control method, the proposed optimal control strategy can effectively improve energy efficiency utilization and has a better control effect, providing technical support for the operation and management of HPS.

show abstract

“…After setting the constraints for the second level planning model, the third level planning model can be constructed [8]. The third level model takes the cost of frequency control as the objective function, and mainly analyzes the work problem of power generation equipment and energy storage equipment.…”

Section: The First Layer Model Of Operation Cost the Second Layer Mod...mentioning

confidence: 99%

Source-network storage and load coordination method of multi-energy system based on regional planning

Chen

Lin

et al. 2023

Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022)

View full text Add to dashboard Cite

At present, due to the serious environmental pollution in China, the planning of multi-energy system is becoming more and more urgent. To meet people's demand for energy planning of a multi-energy system, this paper proposes a method of source-network storage-load coordination of the multi-energy system based on regional planning. By taking the planning cost as the objective function, a three-level multi-energy systems collaborative planning model is constructed to achieve the optimal planning and allocation of energy. Taking the conventional multi-energy system source-network load storage coordination method as the contrast object, the feasibility of the proposed method is proved by the comparative experiment. The experimental results show that the proposed method can effectively reduce the frequency fluctuation caused by the uncertainty of the source load, and effectively control the frequency fluctuation, which has a positive significance for improving energy efficiency.

show abstract

Low-carbon economic optimal dispatch strategy of integrated energy system considering electric-heat flexible load and carbon trading

Cited by 11 publications

References 7 publications

A distributed low-carbon dispatch model for regional multi-integrated energy microgrids considering carbon trading

A distributed low-carbon dispatch model for regional multi-integrated energy microgrids considering carbon trading

Intelligent Optimal Control Strategy of Heat Pump System Based on Digital Twins

Source-network storage and load coordination method of multi-energy system based on regional planning

Contact Info

Product

Resources

About