Yun Teng’s research while affiliated with Shenyang University of Technology and other places

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Publications (44)


Fig. 7 Solving process based on BiLSTM-PSO
Fig. 13 Carbon emission curves
Dynamic carbon emissions optimization method for HIES based on cloud-edge collaborative CBAM-BiLSTM-PSO network
  • Preprint
  • File available

April 2025

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4 Reads

Songqing CHENG

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Tong NIE

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Qian HUI

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[...]

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To achieve the low carbon optimization in hydrogen-based integrated energy system(HIES), this paper proposes a dynamic carbon emissions optimization method for HIES based on cloud-edge collaborative CBAM-BiLSTM-PSO network. Firstly, based on the theory of carbon emission flow, the carbon emissions in HIES are converted from the source to multiple energy load nodes, and a dynamic carbon reduction model for HIES is established. The HIES source load coordinated carbon reduction is achieved by setting the edge objective function at the load and the cloud objective function. And by setting noise sources to correlate the relationship between input variables and decision variables, uncertainty embedding of the objective function is achieved. Then, a cloud-edge collaborative computing network is established to achieve the prediction of new energy power output and multi-energy load consuming as well as scheduling plan solving. Convolutional block attention module (CBAM) is used to strengthen key feature data and fuse heterogeneous data. The particle swarm algorithm (PSO) is combined with the bidirectional long short-term memory network (BiLSTM) to form the CBAM-BiLSTM-PSO solving algorithm, which realizes the solution of HIES source load coordinated carbon emission reduction plan. Finally, the method proposed in this paper was validated using actual running HIES as an example. The results showed that the proposed method can effectively extract the operating characteristics of equipment within HIES, achieve coordinated optimization of carbon reduction, and reduce the carbon emissions of HIES. Compared with other models, the training time of this model is shortened and the accuracy is improved, providing a feasible solution for the data-based low-carbon operation of HIES.

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Research on frequency stability control method of multi-energy system considering grid-connected parameters of electric hydrogen energy coupling equipment

January 2025

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32 Reads

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1 Citation

Science and Technology for Energy Transition

Renewable energy coupling hydrogen production technology can overcome the weakness of randomness and intermittence for renewable energy to a certain extent. However, due to the long-distance and reverse distribution of renewable energy generating units and the main network, there will be a risk of oscillation instability when a high proportion of power electronic hydrogen production system is interconnected with the power grid. Firstly, the impedance model of the electric hydrogen production system is established. The oscillation characteristics of hydrogen production system interconnected with power grid are analyzed. Secondly, the influence of electrolytic hydrogen system on the stability of multi-energy system is analyzed. The instability problems caused by input power fluctuation and hydrogen production rate change are studied. Then, an oscillation suppression strategy for renewable energy hydrogen production system based on power allocation is proposed. It is used to enhance the stability of the multi-energy system of the electrolytic water hydrogen production system. Finally, through the establishment of renewable energy electrolysis hydrogen experimental simulation system. The system frequency stability under different renewable energy output fluctuations and different impedance conditions of the system is verified. The simulation results show that the proposed multi-energy hydrogen production control method based on power allocation can ensure the stability of the system under the fluctuation of renewable energy output.


A bi-level optimization strategy of electricity-hydrogen-carbon integrated energy system considering photovoltaic and wind power uncertainty and demand response

January 2025

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29 Reads

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1 Citation

To address the power supply-demand imbalance caused by the uncertainty in wind turbine and photovoltaic power generation in the regional integrated energy system, this study proposes a bi-level optimization strategy that considers the uncertainties in photovoltaic and wind turbine power generation as well as demand response. The upper-level model analyzes these uncertainties by modeling short-term and long-term output errors using robust optimization theory, applies an improved stepwise carbon trading model to control carbon emissions, and finally constructs an electricity-hydrogen-carbon cooperative scheduling optimization model to reduce wind and carbon emissions. The lower-level model incentivizes users to participate in integrated demand response through dynamic energy pricing, thereby reducing the annual consumption cost of load aggregator. The Karush-Kuhn-Tucker conditions and the Big-M method are used to solve the bi-level optimization model. Simulation results indicate that the improved carbon trading model reduces carbon emissions by approximately 40.12 tons per year, a decrease of 1.1%; the prediction accuracy of the short-term error model improves by 6.77%, and the prediction accuracy of the long-term error model improves by 15.16%; the electricity-hydrogen-carbon synergistic dispatch optimization model enhances the total profit of integrated energy system operator by 14.07% and reduces the total cost of load aggregator by 10.06%.



Hybrid Decision Support Framework for Energy Scheduling Using Stochastic Optimization and Cooperative Game Theory

December 2024

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9 Reads

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2 Citations

This study introduces a multi-criteria decision-making (MCDM) framework for optimizing multi-energy network scheduling (MENS). As energy systems become more complex, the need for adaptable solutions that balance consumer demand with environmental sustainability grows. The proposed approach integrates conventional and alternative energy sources, addressing uncertainties through fermatean fuzzy sets (FFS), which enhances decision-making flexibility and resilience. A key component of the framework is the use of stochastic optimization and cooperative game theory (CGT) to ensure efficiency and reliability in energy systems. To evaluate the importance of various scheduling criteria, the study applies the logarithmic percentage change-driven objective weighing (LOPCOW) method, offering a systematic way to assign weights. The weighted aggregated sum product assessment (WASPAS) method is then used to rank potential solutions. The hybrid scheduling alternative, combining distributed and centralized solutions, stands out as the best alternative, significantly improving resource optimization and system resilience. While implementation costs may increase, the hybrid approach balances flexibility and rigidity, optimizing resource use and ensuring system adaptability. This work provides a comprehensive framework that enhances the efficiency and sustainability of energy systems, helping decision-makers address fluctuating demands and renewable energy integration challenges.






Coordinated optimization model of urban multi-energy supply and ecological environment restoration based on “novel energy cell”

A coordinated optimization model of urban multi-energy supply and ecological environment restoration based on “novel energy cell” cluster is proposed in the paper for dealing the rapid growth of the proportion of renewable energy and the increasing requirements of compatibility and coordination between urban ecological environment governance facilities and multi-energy systems, which contain electricity, heat, cold, and gas. First, the concept of novel energy cell and its mechanism model, which has ecological restoration functions such as sewage and waste treatment, is proposed in the paper. Second, the interaction mechanism between multi-energy supply benefits and ecological restoration benefits in the novel energy cell cluster is studied, and the quantification model of the comprehensive benefits of the novel energy cell cluster is established. Then, with the objectives of the maximum energy saving rate, the maximum emission reduction of system pollutants, and the minimum total operating costs of the system, a comprehensive benefit optimization model of urban multi-energy system and its solving algorithm are established. Finally, a simulation model is established. The simulation results show that the proposed method is conducive to the coordinated development of the integration of energy, environment, and economy of the city.


Citations (25)


... The pricing factors were used to guide stakeholders to reduce carbon emissions while avoiding unnecessary increases in operational costs due to indiscriminate carbon reduction. Lu et al. [10] proposed a two-stage optimisation strategy to address supply-demand imbalance, considering the demand response and the uncertainties of photovoltaic (PV) and wind power generation. Jiao et al. [11] developed a regional energy system (RES) management model and a coordinated optimisation strategy for shared energy storage systems to minimise investment and operational costs. ...

Reference:

Optimisation of Dynamic Operation Strategy for a Regional Multi-Energy System to Reduce Energy Congestion
A bi-level optimization strategy of electricity-hydrogen-carbon integrated energy system considering photovoltaic and wind power uncertainty and demand response

... Their ability to quickly respond to fluctuations in energy demand makes them a valuable component of the overall energy strategy. In summary, the energy system is a multifaceted network that combines various technologies and strategies to enhance energy efficiency, reliability, and sustainability [34,35]. ...

Research on frequency stability control method of multi-energy system considering grid-connected parameters of electric hydrogen energy coupling equipment

Science and Technology for Energy Transition

... Consequently, Fe 3 O 4 , a magnetic metal oxide, was selected to be integrated with the pre-prepared PDMS@SiO 2 substrate solution to yield a PDMS@SiO 2 /Fe 3 O 4 composite friction material with enhanced performance attributes. Subsequent empirical investigations revealed that the incorporation of nanoscale SiO 2 and Fe 3 O 4 oxide particulates into the PDMS friction layer is pivotal in optimizing the TENG friction layer material [12]. The modified friction layer material was found to elevate the TENG's output performance, attributed to alterations in surface micro-nanostructures, electrical conductivity, and the efficiency of charge transfer and separation [13]. ...

Voltage control method for multi-energy system based on the coupling of renewable energy hydrogen production and storage

Science and Technology for Energy Transition

... Various MCDM methods have shown distinct strengths and weaknesses, each outperforming other in specific case studies 62 . AROMAN enhances data accuracy and decision-making efficiency through a two-step normalization process 63 . Given its robustness and high-confidence results, AROMAN is a suitable choice for complex MCDM problems, with previous studies highlighting its effectiveness across applications 60,64 . ...

Optimized Grid Partitioning and Scheduling in Multi-Energy Systems Using a Hybrid Decision-Making Approach

... Literature [81] proposed a regional multi-energy system optimal scheduling model based on the cloud edge synergy theory, which can effectively improve the scheduling data processing capacity and the economics of regional multi-energy system scheduling. Literature [82] reported a two-tier optimal scheduling model for regional multi-energy systems with the cloud service application layer and the edge computing layer as the upper and lower optimal scheduling layers. The model was solved using a multi-objective whale optimization algorithm with the objectives in the optimal scheduling cost and minimum scheduling data transmission. ...

A cloud-edge cooperative scheduling model and its optimization method for regional multi-energy systems

... The modified model predictive control based improved Firefly1to3 (MMPC-IFA1to3) algorithm effectively regulates power flow, minimizing voltage deviations and ensuring stable operations across various conditions, demonstrated through MATLAB/Simulink and real-time testing. Zuo et al. [34] addresses reactive power optimization in multi-energy systems amidst supply and demand uncertainties. It develops a simulation model for reactive power balance, enhancing voltage stability by considering the dynamics of heat and gas network constraints, thus improving overall system performance and safety. ...

Reactive power optimization control for multi-energy system considering source-load uncertainty
  • Citing Article
  • March 2024

Electric Power Systems Research

... Marco et al. [9] extensively investigated water jacket designs using CFD analysis and analytical thermal modeling, presenting correlations for optimizing cooling piping parameters. Zhao et al. [10] proposed a cooling structure where a water-cooled plate is positioned between the axial laminations of the motor stator. Their study examined the effects of water flow rate, plate thickness, and motor loss density, demonstrating that the design meets the cooling requirements for high-loss-density motors. ...

Design and analysis of a high loss density motor cooling system with water cold plates
  • Citing Article
  • June 2023

Global Energy Interconnection

... With the vigorous construction of "hub, platform, and sharing, strong smart grid, and ubiquitous power internet of things" in recent years, a steady stream of distributed power sources such as wind power and photovoltaic, electric vehicles, and energy storage have been connected to the distribution network. The protection system of traditional distribution network is facing a severe test [1]. The ability of the distributed power supply device to withstand overvoltage and overcurrent is weak, and the fault current is weak, so the original three-stage protection cannot be used in the distribution network. ...

Consider the Source Charge Uncertainty and Energy Storage System Optimization Allocation Model of Carbon Emissions Limits
  • Citing Conference Paper
  • March 2023

... Current analysis is a popular approach for fault diagnosis but alternative features are emerging. For example, researchers have used electromagnetic properties to identify faults in wind generators with permanent magnets [15]. Finite element analysis, a versatile tool for analysing rotating machinery, has also been applied to diagnose stator faults in PMSMs [16]. ...

Analysis of electromagnetic characteristics of typical faults in permanent magnet wind generators
  • Citing Article
  • February 2023

Global Energy Interconnection

... The impact of the charging and discharging behavior of the ESS on the grid voltage is mainly reflected in its dynamic regulation of the current distribution [10,11]. By absorbing or releasing active and reactive power, the ESS changes the power balance at local nodes, which, in turn, affects the node voltage. ...

Distributed multi-energy storage cooperative optimization control method for power grid voltage stability enhancement
  • Citing Article
  • March 2023

Electric Power Systems Research