×
模态框(Modal)标题
在这里添加一些文本
Close
Close
Submit
Cancel
Confirm
×
模态框(Modal)标题
×
TSINGHUA JOURNALS HOME
Source Journal for Chinese Scientific and Technical Papers and Citations
RCCSE Chinese Core Academic Journals
Classification Catalogue of High Quality Scientific Journals in the field of Energy and Power
Classification Catalogue of High Quality Scientific Journals in Coal Field
Home
About Journal
Editorial Board
Submission Guideline
Instructions for Authors
Template for Copyright Agreement
Copyright and OA Policy
Editorial Review Policy
Paper Format Template
Reference Citation Format
Journals Online
Online First
Current Issue
Archive
Most Read
Most Download
E-mail Alert
Publication Ethics
Editorial Office
Chinese
Home
About Journal
Editorial Board
Journals Online
Just Accepted
Current Issue
Archive
Most Read
Most Download
Most Cited
E-mail Alert
Ethical Statement
Chinese
Home
Browse
Online first
Online first
The manuscripts published below will continue to be available from this page until they are assigned to an issue.
Please wait a minute...
Please choose a citation manager
RIS (ProCite, Reference Manager)
BibTeX
Content to export
Citation
Citation and abstract
Export
Select all
|
Select
A 3-layer Collaborative Optimization Strategy for Virtual Power Plant Based on Multi-agent Hybrid Game
HAN Xu1, SONG Xiaotong2, YU Kunyu1, LAI Yiming1, XU Wenyue3
Distributed Energy.
https://doi.org/10.16513/J.2096-2185.DE.26110085
Online available: 2026-04-14
Abstract
(18)
PDF
(8)
Knowledge map
Save
To address the challenges of diversified participants in the electricity market and resolve conflicts of interest among multiple virtual power plants (VPPs), this paper proposes a three-layer hybrid game strategy involving the distribution system operator (DSO), virtual power plant operator (VPPO), and user aggregator (UA) to support collaborative optimization of multi-VPP systems. First, a UA coalition is formed by aggregating various flexible resources, including photovoltaic prosumers, electric vehicle charging stations, and integrated energy loads. Next, a 3-layer hybrid game model is constructed, encompassing hierarchical energy transactions among DSO, VPPO, and UA, as well as peer-to-peer energy trading among UA entities, structured as a "Stackelberg game - Stackelberg game - cooperative game" framework. Finally, the proposed model is solved using the bisection method, Karush-Kuhn-Tucker conditions, and the alternating direction multiplier method. Case studies demonstrate that the proposed multi-layer hybrid game strategy reduces the operating costs of the photovoltaic prosumer UA and the electric vehicle charging station UA by 4.5% and 15.3%, respectively. Meanwhile, guided by the dynamic pricing mechanism of the DSO, the total profit of the system operators increases by 2.7%. This strategy can effectively balance the interests of multiple stakeholders, optimizing the energy trading and benefit allocation mechanisms among different operators.
Select
Experimental Study on Slagging Characteristics and Composition Evolution of Anthracite Coal at Low to Medium Loads
GE Wentao , CHEN Meng , WANG Chenyu , MU Lin , DONG Ming , WANG Chu
Distributed Energy.
https://doi.org/10.16513/J.2096-2185.DE.26110061
Online available: 2026-04-14
Abstract
(8)
PDF
(4)
Knowledge map
Save
This study investigates the ash deposition behavior of anthracite during combustion, which significantly affects boiler safety and efficiency due to slagging tendencies. A pilot-scale one-dimensional settling furnace system was employed to conduct combustion experiments under varied operating conditions, including different loads, primary/secondary air ratios, and excess air coefficients. Ash samples were analyzed by fusion tests, SEM, XRD, XRF, and laser sizing. Results show ash composition (C, O, Si, Al) and crystalline phases (quartz, mullite, hematite) remain stable. Increasing the load from 0.2 MW to 0.3 MW raises the ash deformation temperature from 1259 °C to 1312 °C, while the slagging index increases from 1268 to 1319, indicating a significantly enhanced slagging tendency. When the mass ratio of primary air to secondary air is increased from 2/8 to 4/6, the unburned carbon content in ash increases from approximately 37.5% to 40%, and the median particle size enlarges from 22 μm to about 28 μm, resulting in a pronounced promotion of ash deposition. Excess air coefficient had limited impact on fusibility and slagging. Ash exhibited a bimodal size distribution: fine particles form an adhesive layer, while coarse particles deposit by impaction, jointly accelerating slagging. The results demonstrate that boiler load dominates slagging behavior, with air distribution affecting burnout and particle characteristics. This study provides pilot-scale experimental data and mechanistic insights for slagging prediction and combustion optimization of anthracite-fired boilers under wide-load operation.
Select
Energy Storage Optimal Planning Method Considering Generation-Storage Coordination for Local Consumption and Power Supply Reliability#br#
MA Huimeng1 , LI Xiangjun1 , XIU Xiaoqing1 , GAN Zhiyong2 , ZHANG Li2 , HE Chun2
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.26110042
Online available: 2026-04-08
Abstract
(17)
PDF
(7)
Knowledge map
Save
To address the interconnected challenges of bus voltage limit violations, reverse power flow overloading,and deteriorated power supply reliability caused by high-penetration distributed renewable energy integration, this paper
proposes an energy storage optimal planning method considering generation-storage coordination for local consumption and power supply reliability. An energy storage optimal planning model is established, aiming to minimize the annualized
comprehensive cost (including energy storage investment and renewable curtailment penalties) while optimizing voltage fluctuation and net load fluctuation. The non-convex nonlinear model is solved using an improved multi-objective particle
swarm optimization algorithm. By incorporating an adaptive inertia weight mechanism and a dynamic crowding distancebased non-dominated solution set update strategy, the algorithm effectively avoids premature convergence and local
optima traps. Simulation results based on the IEEE 33-bus distribution network demonstrate that the “storage configuration + reasonable curtailment of renewable energy” scheme increases renewable energy local utilization by 12% and reduces
annualized comprehensive cost by 5.6% compared to the “reasonable curtailment of renewable energy” scheme, while achieving a 7.5% cost reduction compared to the “storage configuration” scheme alone.
Select
Optimization Model of Virtual Power Plant Participating in Power Peak Shaving Decision Based on Resource Response Capability and IGDT
YU Meng1, 2, LI Yan1, 2, ZHU Liangliang1, 2 , GUO Xiangyu3 , ZHANG Min3 , XU Chenguan1, 2
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100203
Online available: 2026-04-08
Abstract
(16)
PDF
(2)
Knowledge map
Save
To address the optimization problem of resource aggregation and bidding decision-making for virtual power plants (VPPs) participating in power peak shaving, a decision optimization model based on resource response capability and information gap decision theory (IGDT) is proposed. Considering four dimensions—response potential,fluctuation degree, duration, and response speed—an aggregation indicator system for distributed resources is constructed. A multi-objective aggregation optimization model is established, balancing the maximization of expected response revenue and the minimization of deviation penalty risk, to screen the optimal resource portfolio. The market transaction framework and bidding decision mechanism for VPPs participating in power peak shaving are designed. The IGDT theory is introduced to characterize the uncertainty of peak shaving compensation prices, and a risk-averse (RA) model is constructed to optimize bidding strategies.The simulation results show that the multi-objective optimization model of virtual power plant aggregation can take into account both economic and risk considerations. It can provide a theoretical method for virtual power plant aggregators to screen resources and reduce the risk of deviation punishment of virtual power plants. The IGDT-based bidding decision optimization model can help avoid the transaction risk caused by the uncertainty of peak compensation price, so that the virtual power plant can obtain reasonable response benefits.
Select
Secondary Frequency Modulation Strategy for Hybrid Energy Storage Systems Considering the Response Characteristics of Thermal Power and Compressed Air Energy Storage#br#
#br#
CHEN Zhuo1, CHEN Laijun2, CUI Sen2, LIU Hanchen2, WANG Xinyu2
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.26110051
Online available: 2026-04-08
Abstract
(21)
PDF
(6)
Knowledge map
Save
With the large-scale integration of high-penetration renewable energy into the power grid, there are increasing demands for frequency regulation. To address the issues of high regulation losses and poor economic performance resulting from the frequent ramping of conventional thermal power units, this paper proposes a secondary frequency regulation strategy for a hybrid energy storage system (HESS) that incorporates the response characteristics of both thermal power and compressed air energy storage (CAES). First, the automatic generation control signal is decomposed into high-frequency and low-frequency components using the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and multiscale permutation entropy (MPE) methods. Subsequently, leveraging the similarity between thermal power units and CAES in terms of dynamic response time and regulation inertia, a coordinated control method for a thermal-HESS is developed. This method enables the rational allocation of high- and low-frequency components among different units, thereby enhancing the system’s frequency regulation performance while reducing the output variability of the thermal unit. Finally, a dynamic simulation model is built in Matlab/Simulink to validate the regulation performance and economic benefits of the proposed strategy. Simulation results demonstrate that the proposed strategy can fully leverage the analogous response characteristics between thermal power and CAES during secondary frequency regulation, as well as the complementary advantages of the HESS in terms of fast response and large capacity. This coordinated approach effectively reduces and smoothens the output of the thermal power unit, thereby enhancing the overall frequency regulation performance and economic benefits of the thermal-HESS.
Select
Configuration Optimization Method for Underwater Compressed Air Energy Storage Based on Distributionally Robust Chance Constraints
HUANG Zheng1 , YANG Yi1 , WU Wei1 , CHEN Laijun2, 3 , LIU Hanchen2 , CUI Sen2, 3 , LI Shijie4
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100136
Online available: 2026-04-08
Abstract
(13)
PDF
(3)
Knowledge map
Save
Underwater compressed air energy storage (UW-CAES), which utilizes flexible underwater air bags to enable constant-pressure charge and discharge, has emerged as a compelling solution for renewable energy accommodation. However, there remains a distinct lack of research focused on parameter optimization to simultaneously reduce the capital costs of UW-CAES and enhance the operational economics of the plant. To address this critical gap, this paper proposes an optimal configuration method for UW-CAES based on distributionally robust chance constraints (DRCC). First, a comprehensive UW-CAES system model is established, explicitly accounting for the impact of pipeline pressure losses on system dynamics. Subsequently, an optimal configuration framework incorporating these pressure losses is formulated to optimize key system parameters, with the dual objectives of minimizing investment costs and maximizing operational revenues. Furthermore, the DRCC approach is employed to reformulate the stochastic chance constraints into tractable linear constraints. This mathematical transformation not only ensures computational efficiency but also facilitates a flexible trade-off between economic optimality and robustness. Case studies demonstrate the efficacy of the proposed methodology: the optimized system maintains a rated discharge power of 60 MW while reducing the required rated charge power to 53.2 MW−an 8.75% decrease compared to the original baseline−thereby significantly improving overall system efficiency. Finally, sensitivity analyses reveal that systematically calibrating the confidence level and Wasserstein radius within the DRCC framework effectively navigates the equilibrium between economic performance and system conservatism
Select
Research on Coordinated Planning for Enhancing Flexibility in Regional Coal-Fired Power Generation
LÜ Fengze1, 2, GUO Tingting2, CAO Fan3, LIU Pei1, 4
Distributed Energy.
https://doi.org/10.16513/J.2096-2185.DE.26110006
Online available: 2026-03-27
Abstract
(10)
PDF
(6)
Knowledge map
Save
To enhance the operational flexibility of coal-fired power plants in supporting high penetration of renewable energy, this paper focuses on the coordinated planning of regional coal-fired power flexibility upgrades. Existing research typically optimizes deep peak-shaving modifications on the boiler side of condensing units and thermal-electric decoupling technologies separately, with most studies neglecting the impact of grid structural constraints. this paper first systematically analyses the operational characteristics of four technical approaches: deep peak shaving modifications on the boiler side, zero-output modifications for low-pressure cylinders, electric boilers, and thermal storage devices. Subsequently, a mixed-integer linear programming model incorporating grid topology is constructed. This model aims to minimize total system costs, enabling the coordinated configuration and operational optimization of multiple technical pathways. A case study based on an enhanced IEEE 14-node
system demonstrates that integrated optimization of these technologies reduces total system costs by 5.98% and curtailment rates for wind and solar power by 15.68%. The results validate that the proposed collaborative planning approach effectively integrates complementary advantages across different technologies, significantly lowering system costs and alleviating pressure on renewable energy integration. It also reveals that the flexibility regulation capacity of coal-fired power plants is influenced by their node position within the grid.
Select
Frequency Regulation and Economic Optimization of Thermal-Energy Storage Coordination Under Time-Varying Inertia Conditions
LI Yurui, HAO Sipeng
Distributed Energy.
https://doi.org/10.16513/J.2096-2185.DE.25100495
Online available: 2026-03-03
Abstract
(45)
PDF
(12)
Knowledge map
Save
With the large-scale integration of distributed generation (DG) and power electronic devices, the power system exhibits significant low-inertia and time-varying characteristics. Traditional thermal-energy storage joint frequency regulation strategies, typically relying on fixed parameters, struggle to adapt to dynamic fluctuations in system inertia and lack refined consideration of the full life-cycle economics of energy storage. To address these issues, a cooperative frequency control strategy for thermal-storage systems is proposed, based on online inertia assessment and adaptive deadband optimization. A hierarchical oordination mechanism is established: under small disturbance conditions, the energy storage system (ESS) acts as a fastresponse istributed flexible resource with priority, utilizing a low deadband to prevent frequent wear on thermal units. Under large disturbance onditions, the strategy identifies the real-time equivalent inertia based on the inverse solution of the system frequency response and adaptively adjusts the ESS's virtual inertia and droop coefficients to provide dynamic damping compensation. Furthermore, an improved life-cycle cost model accounting for cycle life degradation is developed. Simulation results demonstrate that the proposed strategy effectively suppresses system oscillations and significantly reduces comprehensive regulation costs, offering a techno-economically optimal solution for distributed energy storage participating in ancillary services and frequency governance in low-inertia grids.
Select
Optimal Control of a Wind-PV Coupled Dual-Channel Electrolytic Cell Hydrogen Production System
GENG Xin, LOU Qinghui, SHI Xiangjian, FENG Kangkang, YANG Yu
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100099
Online available: 2026-02-06
Abstract
(61)
PDF
(22)
Knowledge map
Save
[Objectives] To address the poor operational stability and high unit hydrogen production cost caused by strong power fluctuations of wind and photovoltaic (PV) renewable energy, this study investigates an optimized control strategy for a dual-channel hybrid hydrogen production system under wind-PV coupled application scenarios. [Methods] An optimized control strategy for a dual-channel electrolytic cell system based on ensemble empirical mode decomposition (EEMD) and Petri net-based start-stop correction is proposed. Wind and PV power signals are decomposed using EEMD, and power components at different frequency bands are allocated to alkaline and proton exchange membrane (PEM) electrolytic cells according to their dynamic response characteristics. Meanwhile, a Petri net model is employed to construct start-stop logic for electrolytic cells, effectively suppressing frequent switching under low-load conditions. Furthermore, a multi-objective optimization model is established with the objectives of maximizing system energy conversion efficiency and minimizing the unit hydrogen production cost, which is solved using a multi-objective particle swarm optimization algorithm. [Results] Simulation results based on measured wind-PV power output data from the Zhangbei region indicate that the optimized hybrid hydrogen production system achieves an energy conversion efficiency of 58.64% and a unit hydrogen production cost of 2.3958 USD/kg. Compared with conventional single-type hydrogen production schemes, the proposed method improves efficiency by 15.25% and reduces cost by 1.7384 USD/kg, while significantly decreasing the number of start-stop events of electrolytic cells. [Conclutions] The results demonstrate that the proposed control strategy effectively enhances system stability and reduces economic cost, providing a practical and feasible optimization approach for the efficient operation of wind-PV hydrogen production systems.
Select
A Joint Trustworthy Forecasting Method for Power and Energy of
Regional Distributed Photovoltaic Systems
GAO Liyuan, CUI Mingtao, GUOGuanglai, ZHANG Peiyao
Distributed Energy.
https://doi.org/10.16513/J.2096-2185.DE.25100384
Online available: 2026-01-27
Abstract
(31)
PDF
(6)
Knowledge map
Save
To address the issues of existing regional distributed photovoltaic (PV) power forecasting, such as heavy reliance on meteorological data, high operation and maintenance costs, poor data quality and insufficient result credibility,a joint credible forecasting method for PV power and energy is proposed. First, power measurements from smart meters and daily frozen energy data are jointly filtered, fused, and normalized to enhance data set quality. Second, a multi-time-scale, high-accuracy sequence-to-sequence (Seq2Seq) forecasting framework is developed, integrating historical and forecast data from centralized regional PV plants; a multi-time-scale loss function that jointly accounts for both power and energy is employed to optimize prediction accuracy. Finally, a model integrity verification scheme based on commit-and-prove succinct non-interactive argument of knowledge (cp-SNARKs) is designed to ensure result credibility while preserving model confidentiality. Experimental validation using real-world data from a city in North China demonstrates that the proposed method significantly reduces forecasting errors for both power and energy, thereby improving PV power prediction accuracy. Requiring no meteorological inputs or system modifications, the approach features high data quality, superior prediction accuracy, low operational cost, and strong verifiability, making it readily extensible to other time-series forecasting tasks such as load forecasting and wind power prediction.
Select
A Multi-Timescale Adaptive Dispatch Method for Virtual Power Plants Based on Multi-Source Uncertainty and Online Parameter Correction
HUO Feifan, LÜ You, TIAN Helu, LIAO Conglin
Distributed Energy.
https://doi.org/10.16513/J.2096-2185.DE.25100518
Online available: 2026-01-22
Abstract
(61)
PDF
(36)
Knowledge map
Save
To address the scheduling failures, power imbalances, and economic losses in virtual power plants (VPPs) caused by multisource uncertainties—including stochastic renewable generation, load fluctuations, and parameter deviations—this paper develops a multi-timescale adaptive dispatch framework incorporating multi-source uncertainty modeling and online parameter correction. The framework employs two-stage robust optimization for day-ahead scheduling to generate a robust pre-dispatch plan, and introduces a state-feedback mechanism in the intra-day stage, where an improved quantum-inspired genetic algorithm is used to recursively correct critical parameters, thereby forming a closed-loop dispatch structure. Simulation experiments validate the effectiveness of the proposed approach. Results show that, under significant forecasting errors in renewable generation and electro-thermal loads, the method improves actual operational revenue by approximately 3.2% compared to conventional deterministic dispatch. Moreover, the online parameter correction strategy reduces system balancing costs by nearly 90% during most time periods. The framework effectively balances robustness, economic efficiency, and adaptability, offering a viable technical pathway for the secure and economical operation of VPPs under high uncertainty
Select
Vibration Analysis and State Assessment of 5 MW Test Wind Turbine in Frozen Environment
LI Wei1, 2, CHEN Hai3, JIANG Bo3, AN Chaolin3
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100388
Online available: 2025-12-12
Abstract
(46)
PDF
(22)
Knowledge map
Save
Vibration monitoring and condition assessment are crucial technical means and management measures for ensuring the safe operation of large wind turbines, especially in the winter freezing environment of Yunnan-Guizhou Plateau, the vibration monitoring and state assessment of the antifreezing test wind turbine is particularly important. The icing random distribution of the wind turbine blade may lead to mass imbalance and aerodynamic shape change among three blades, combined with installation differences of new equipment or auxiliary materials in three blades of wind turbine for antiicing/deicing requirement, so these factors may collectively induce severe vibration of the wind turbine to result with equipment safety hazards. This study employs the active aerothermal method to construct three 5MW test wind turbines, and the primary influencing factors of turbine vibration is analyzed deeply. The vibration monitoring data during four months from three 5MW antifreezing test turbines were employed to calculate 9 key turbine vibration condition variables and comprehensively evaluate the vibration condition in combination with characteristic limit values, and the vibration development trend of each turbine was judged by longitudinally and horizontally comparing. The assessment results indicate that the vibration intensity and its difference among three test wind turbines are smaller, which can operate safely for a long period, and the impact of blade icing and antiicing modifications on vibration is not significant.
Select
Wide-Range Operational Approach for Advanced Adiabatic Compressed Air Energy Storage Systems Incorporating Array-Type Heat Exchangers
WANG Wei1, CHEN Laijun2, 3, LEI Yinsheng4, ZUO Yiming4, GAO Ruiyan4, LIU Hanchen2
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100427
Online available: 2025-12-12
Abstract
(51)
PDF
(25)
Knowledge map
Save
As an extension of the heat exchanger network (HEN), the array-type heat exchangers can effectively enhance the operational capability of Advanced Adiabatic Compressed Air Energy Storage (AA-CAES). However,the complexity of the variable-configuration array-type heat exchanger network exerts a significant influence on the operational capability of the AA-CAES system. To address this gap, this paper proposes a wide-range operational strategy for AA-CAES systems that incorporates array-type heat exchangers. First, a model of the array-type heat exchangers array for AA-CAES is established based on the thermal-electrical analogy theory. Subsequently, a widerange operation method for AA-CAES is proposed, leveraging the operational characteristics of the array-type heat exchangers. This method determines the number of heat exchanger units participating in power regulation according to the required power output, followed by a multi-objective optimization of the array-type heat exchangers using power deviation and residual thermal energy of the thermal oil as objective functions. Finally, a case study based on the parameters of a commercially operational AA-CAES station is conducted to validate the effectiveness of the proposed method. The results demonstrate that, compared to traditional heat exchangers, the modular heat exchanger array can effectively expand the feasible operating region of the AA-CAES discharging system, reduce power tracking deviation,and increase the utilization rate of thermal energy in the thermal oil. The research will provide the theoretical foundation and technical support for flexible regulation of AA-CAES.
Select
Multi-Timescale Scheduling of Regional Integrated Energy Systems Incorporating Compressed Air Energy Storage Ramp Capabilities
LI Jianhua1 , CUI Sen2, 3 , ZHANG Xiaolong1 , GUO Junbo1 , SU Fawan1 , WANG Jupeng1
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100364
Online available: 2025-12-03
Abstract
(59)
PDF
(4)
Knowledge map
Save
To address the challenges of power fluctuations and ramping demands faced by regional integrated energy
systems under high penetration of renewable energy, this paper focuse
s on the ramping support capability of Advanced
Adiabatic Compressed Air Energy Storage (AA-CAES). A multi-timescale optimization dispatch model for regional integrated energy systems incorporating AA-CAES ramping capability is established. First, an operational model of AA-CAES is established to analyze its support capability for thermal power ramping. Second, a multi-timescale optimization dispatch strategy for regional integrated energy systems incorporating AA-CAES ramping capability is proposed. Long-timescale optimization minimizes operational costs while ensuring system power balance, and short timescale dynamic power correction is achieved using Model Predictive Control (MPC). Simulation results demonstrate that multi-timescale scheduling, incorporating AA-CAES ramping capability, effectively enhances the system's resilience to renewable energy fluctuations, reduces thermal power dispatch requirements, lowers operational costs, and improves the integration of renewable energy. This approach provides theoretical guidance for the economic and stable operation of regional integrated energy systems.
Select
Virtual Power Plant Optimal Scheduling Based on the Synergy of Carbon Capture,Electric-to-Gas Conversion and Electric Vehicles
TIAN Yongyaun, LIU Min
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100298
Online available: 2025-12-02
Abstract
(65)
PDF
(8)
Knowledge map
Save
Under the background of the "dual carbon" goals, the contradiction between the high proportion of renewable energy grid connection and the reliance on fossil energy has become increasingly prominent. To coordinate low-carbon constraints with energy security, this paper proposes an optimized scheduling model for virtual power plants (VPP) based on the collaboration of carbon capture (CCS), electric-to-gas (P2G), and electric vehicles (EV). This model builds an integrated framework of "emission reduction - conversion - benefit" by aggregating distributed resources such as gas turbine units, combined heat and power (CHP), wind power, photovoltaic power and EVs: Firstly, CCS is used to capture CO ₂ ; Secondly, through CCS-P2G, carbon dioxide is converted into methane by utilizing the abandoned wind and photovoltaic energy, and the captured CO₂ is consumed to form a carbon cycle. Finally, aggregated EVs participate in carbon market transactions and increase their profits by using the China Certified Emission Reductions (CCER) they generate. The case analysis based on MATLAB/CPLEX shows that
compared with the traditional gas-CHP system model, the model proposed in this paper can reduce carbon emissions
by 91. 3% (from 2,466. 9 tons to 214. 34 tons), lower the cost of wind and solar power curtailage by 50,249. 30 yuan, and increase the consumption rate of renewable energy. And by selling CCER, the net cost of VPP was reduced by 8,208. 42 yuan. Ultimately, the overall net cost of VPP was reduced by 77,562. 28 yuan. The research verified the effectiveness of multi-technology collaboration in enhancing the economic and environmental benefits of VPP,providing theoretical support and practical paths for the low-carbon transformation of the new power system.
Select
Practices and Explorations in Hydrogen Energy Discipline Development
LI Jianlin1, YU Yuxin1, LIANG Zhonghao2, 3, LIU Yun1
Distributed Energy.
https://doi.org/10.16513/j.2096-2185.DE.25100423
Online available: 2025-11-17
Abstract
(34)
PDF
(42)
Knowledge map
Save
As a core domain in global energy transition and low-carbon development, hydrogen energy holds significant importance for supporting industrial innovation and talent cultivation through disciplinary development. Currently, universities and research institutions worldwide are actively exploring pathways to establish hydrogen energy disciplinary systems. Based on systematic research into hydrogen energy discipline development, this paper examines the current state of such development in China and explores practical approaches centered on talent cultivation and curriculum system construction. Analyzing aspects such as disciplinary layout, curriculum systems, research platforms, and faculty development, it elucidates achievements in cultivating specialized talent, driving technological innovation, and serving industrial growth through examining disciplinary development objectives, innovative teaching methods, and resource integration. Simultaneously, it dissects existing challenges and proposes targeted optimization strategies, aiming to provide theoretical references and practical insights for China's high-quality hydrogen energy discipline development. It identifies existing issues in current discipline development, including insufficient interdisciplinary integration, scarcity of practical resources, and room for improvement in internationalization. Recommendations are provided for the next phase of hydrogen energy discipline development and exploration in China,offering guidance for the sustainable advancement of this field and driving the high-quality development of China'shydrogen energy industry.
page
Page 1
of 1
Total 16 records
First page
Prev page
Next page
Last page