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Research on security and privacy protection of electric power data sharing XING Huidi, GONG Gangjun, ZHAI Mingyue, LIU Xuesong, WANG Haomiao, YANG Shuang Integrated Intelligent Energy    2024, 46 (5): 30-40.   DOI: 10.3969/j.issn.2097-0706.2024.05.004 Abstract （346）   HTML （10）    PDF （1839KB）（857）       Knowledge map    Electric power data can reflect the development status of society and is promising in the opening and integrated applications. In order to create and release the value of power data， power companies need to build a data sharing service system for all industries. However， there are security issues such as privacy leakage， data tampering and shortage of data security aggregation method in the process of power data sharing. At present， there are three main technologies that can deal with the security problems above， blockchain， privacy computing and desensitization. Based on reviews on relevant literatures， a demand model for and privacy data protection in power data sharing is proposed. The three security and privacy protection technologies for electric power data sharing are summarized，and their integration and applications in different scenarios are comparatively analyzed. Different security and privacy protection schemes provide references for promoting electric power data opening and sharing. Table and Figures | Reference | Related Articles | Metrics

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Capacity optimization of wind-solar-nuclear-energy storage hybrid system considering wind and solar energy consumption NIE Xueying, CHENG Maosong, ZUO Xiandi, DAI Zhimin Integrated Intelligent Energy    2025, 47 (1): 51-61.   DOI: 10.3969/j.issn.2097-0706.2025.01.007 Abstract （339）   HTML （47）    PDF （4751KB）（206）       Knowledge map    The capacity configuration optimization of a wind-solar-nuclear-energy storage hybrid energy system was performed through a multi-objective evolutionary algorithm in this research. The hybrid energy system included photovoltaics（PV），wind turbines（WT），small modular thorium molten salt reactor（smTMSR），and thermal energy storage（TES）. The optimization objectives were to improve the stability of the electricity supply，reduce the electricity generation cost，reduce the electricity curtailment probability，and increase the fraction of renewable energy in the total power supply system（renewable energy fraction）. The PV capacity，WT capacity，and TES capacity were selected as the optimization parameters，while the local meteorological data of Wuwei city were used as input parameters. By comparing the performance of the nondominated sorting genetic algorithm（NSGA-Ⅱ，NSGA-Ⅲ）and the strength Pareto evolution algorithm（SPEA-SDE），the optimal algorithm was selected to solve the multi-objective optimization problem and obtain the Pareto solution set. The Criteria Importance Through Intercriteria Correlation（CRITIC）method was used to determine the objective weights，and the Technique for Order Preference by Similarity to Ideal Solution（TOPSIS）method was used to sort the obtained Pareto solutions，from which the best compromise solution was selected. The results demonstrated that NSGA-Ⅱ had the fastest convergence speed compared to other algorithms，but its solution set was less uniform. NSGA-Ⅲ，although slower to converge，had the most uniform solution set compared to other algorithms. The optimization results showed that the optimal capacity configuration resulted in a deficiency of power supply probability of 0.968 6%，a levelized cost of energy of 0.085 7 dollars/（kW·h）. an electricity curtailment probability of 4.898 6%，and a renewable energy share of 21.258 9%. The electricity curtailment mainly came from nuclear power，with minimal renewable energy curtailment. The sensitivity analysis results showed that the PV capacity had the most significant impact on the probability of power supply deficiency，electricity curtailment probability，and renewable energy fraction，while the WT capacity had the most significant impact on the levelized cost of energy. The wind-solar-nuclear-energy storage hybrid energy system can effectively promote renewable energy consumption and ensure the reliability of the power supply. Table and Figures | Reference | Related Articles | Metrics

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Anomalous data detection methods for new power systems WANG Liang, DENG Song Integrated Intelligent Energy    2024, 46 (5): 12-19.   DOI: 10.3969/j.issn.2097-0706.2024.05.002 Abstract （289）   HTML （10）    PDF （1719KB）（923）       Knowledge map    With the rapid development of new power systems， massive data with various types are generated from the power systems. The complicated data conditions bring new challenges to anomaly data detection for power systems. In a summary on commonly used methods for anomalous power data in detecting， traditional technology-based， machine learning-based and deep learning-based detection methods are introduces. The working principle， characteristics and shortcomings of the three types of detecting methods are analysed. In the end， the challenges and development trends of anomalous data detection in new power systems are looked forward. Table and Figures | Reference | Related Articles | Metrics

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Switching method for distribution network feeder automation system based on 5G communication delay ZHU Weiwei, ZHU Qing, GAO Wensen, LIU Caihua, WANG Luze, LIU Zengji Integrated Intelligent Energy    2024, 46 (5): 1-11.   DOI: 10.3969/j.issn.2097-0706.2024.05.001 Abstract （215）   HTML （6）    PDF （2545KB）（171）       Knowledge map    Since data transmission time is difficult to predict due to the uncertain delay of 5G communication， the fault response timeliness and decision-making accuracy of a feeder automation （FA） system are affected. Thus， a distribution network FA switching method based on 5G communication delay is proposed. Initially， the topological relationship between feeder terminals is established， and the real-time communication delay of the FA system is calculated based on the maximum communication delay in each branch of the FA system. Subsequently， a stacked Long Short-Term Memory （LSTM） neural network model is trained by the historical data of fault processing time under different FA strategies and various delays， to obtain the FA strategies with the fastest fault handling speed under different communication delays. Finally， based on the learning outcomes of the layer-stacked LSTM model， the FA strategy with the shortest fault handling time under a certain communication delay is selected. Experimental results demonstrate that the proposed method effectively mitigates the impact of uncertain delays in 5G communication on FA systems， ensuring their reliable operation. Moreover， compared to other machine learning methods， the layer-stacked LSTM model shows advantages in prediction accuracy and prediction delay， effectively enhancing the adaptive capacity and fault response speed of feeder terminals. Table and Figures | Reference | Related Articles | Metrics

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Modeling of photovoltaic-PEM hydrogen production system and comparative performance analysis of different coupling methods HU Kaiyong, ZHAO Peiyu, WANG Zhiming Integrated Intelligent Energy    2024, 46 (9): 37-44.   DOI: 10.3969/j.issn.2097-0706.2024.09.005 Abstract （213）   HTML （14）    PDF （2884KB）（85）       Knowledge map    Hydrogen production by photovoltaic-coupled electrolyzers is the main way to produce hydrogen， but outputs of photovoltaic cells vary with fluctuations of solar radiation，which will lead to intermittent power generation. In order to improve the utilization of solar energy as well as the stability of the photovoltaic hydrogen production system， an indirectly coupled hydrogen production system consisting of a photovoltaic cell and a proton exchange membrane （PEM）electrolyzer is established. The system consists of photovoltaic cells， a PEM electrolyzer， a maximum power point tracking （MPPT） controller， a DC-DC converter and a battery. The system regulates the electrical energy generated by PV cells by controlling the battery which stores excess power when the intensity of solar radiation is high and drives the electrolyzer when the PV cells cannot generate sufficient power. The effectiveness of the system is verified by a simulation test. The energy efficiencies and hydrogen production rates of PV hydrogen production systems using different coupling methods are compared. The results show that， among all the coupled systems proposed， the comprehensive efficiency of the indirect coupled system is the highest， and its hydrogen production rate does not change with the intensity of solar radiation. The optimized coupled system has the highest hydrogen production rate， but its electrolysis efficiency decreases with the increase of solar radiation intensity. The direct-coupled system has a quite low comprehensive efficiency and hydrogen production rate due to the mismatch between the PV cell and electrolyzer sizes. Table and Figures | Reference | Related Articles | Metrics

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Decentralized voltage control of distribution network based on multi-agent reinforcement learning MA Gang, MA Jian, YAN Yunsong, CHEN Yonghua, LAI Yening, LI Zhukun, TANG Jing Integrated Intelligent Energy    2024, 46 (10): 32-39.   DOI: 10.3969/j.issn.2097-0706.2024.10.005 Abstract （210）   HTML （2）    PDF （2033KB）（63）       Knowledge map    The integration of large-scale decentralized resources into the distribution network has changed the traditional power flow distribution， resulting in frequent voltage violations. Model-based voltage control methods require a detailed knowledge of power system network topology and have long computation time， making them unsuitable for real-time voltage control.To address this， this paper proposes a multi-agent online learning strategy for decentralized voltage control in distribution networks， considering asynchronous training. The method considered each photovoltaic （PV） inverter as an agent. First， the agents were partitioned and adjusted， then the voltage reactive power control problem of distribution network was modelled as a Markov decision process. Based on distributed system constraints， a multi-agent reinforcement learning decentralized control framework was used， and agents were trained with a multi-agent deep deterministic policy gradient（MADDPG） algorithm. Once trained， the agents could make decentralized decisions using local information without real-time communication， enabling real-time voltage control and reducing network losses by determining the output plan for the PV inverters. Finally， the effectiveness and robustness of the method were verified through simulation. Table and Figures | Reference | Related Articles | Metrics

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Application and prospect of federated learning in new power systems LYU Yongsheng, ZHANG Xiaoyu, WANG Xirong, GUO Peiqian Integrated Intelligent Energy    2024, 46 (11): 54-64.   DOI: 10.3969/j.issn.2097-0706.2024.11.007 Abstract （206）   HTML （6）    PDF （1033KB）（360）       Knowledge map    New power systems aiming to make clean， low-carbon， safe， flexible and efficient power supply is a key measure to achive the "dual carbon" target. However， with the widespread access of renewable energy， the fusion of artificial intelligence technologies and the rapid development of smart microgrids and distributed energy sources， such as electric vehicles， traditional centralized data processing methods fall short in protecting data privacy and enabling intelligent management. Federated learning （FL）， an innovative distributed machine learning technology， offers an effective efficiency optimization solution for new power systems due to its data privacy protection capability and intelligence. In reviews on the applications of FL in new power systems， basic principles and main algorithms of FL are expounded， practical cases of FL applied in load forecasting， anomaly detection， distributed power control and energy management under data privacy protection are analysed. Then the current technical challenges encounter by FL are also discussed. Finally， the prospects of FL in new power systems are made. Table and Figures | Reference | Related Articles | Metrics

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Capacity configuration optimization of wind‒solar hydrogen production based on life cycle assessment BAI Zhang, HAO Wenjie, LI Qi, HAO hongliang, WEN Caifeng, GUO Su, HUANG Xiankun Integrated Intelligent Energy    2024, 46 (10): 1-11.   DOI: 10.3969/j.issn.2097-0706.2024.10.001 Abstract （205）   HTML （10）    PDF （2861KB）（75）       Knowledge map    A wind-solar-hydrogen production complementary system is an important technical method to promote the local renewable energy utilization and reduce wind and solar power curtailment. However， the fluctuation of wind and solar outputs and the variety of system equipment challenge the capacity allocation optimization of wind‒solar‒hydrogen production complementary systems. A life cycle assessment（LCA）method was used to address this problem. Taking the levelized cost of hydrogen（LCOH），carbon emission intensity per unit of hydrogen， and energy loss rate as optimization objectives， an off-grid wind‒solar‒hydrogen production system with an annual production capacity of 20 000 t of hydrogen was constructed based on the improved NSGA-Ⅲ multi-objective optimization algorithm. The carbon emissions and economic benefits of the system were further analyzed. The results showed that after the optimization based on the wind and solar resource characteristics in Inner Mongolia， the LCOH of the system was 25.88 yuan/kg， with a carbon emission intensity of 0.59 kg/kg. The annual renewable energy utilization rate increased to 91.09%， demonstrating efficient resource utilization. The LCA showed that the system's total carbon emissions amounted to 250 300 t， and the carbon emission per unit of hydrogen was reduced by 97.05% compared to that of a typical coal-based hydrogen production system. The research results provide a reasonable reference for the utilization of wind-solar-hydrogen production complementary systems. Table and Figures | Reference | Related Articles | Metrics

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Security protection for integrated energy cyber physical systems based on energy hubs GONG Gangjun, WANG Luyao, CHANG Zhuoyue, LIU Xu, XING Huidi Integrated Intelligent Energy    2024, 46 (5): 65-72.   DOI: 10.3969/j.issn.2097-0706.2024.05.008 Abstract （199）   HTML （4）    PDF （2007KB）（155）       Knowledge map    To improve the energy and information exchange efficiency between devices and energy nodes in an integrated energy system （IES）， reduce energy production and transmission costs， and achieve efficient conversion and flexible allocation of multiple energy sources， a centralized-distributed integrated energy system based on energy hubs（EH） is constructed. According to the model of the IES，the cyber physical system based on the cluster of sub-cyber physical systems is defined. On the information end of the IES， the operational model for each sub-cyber physical system and information interaction model for sub-information system servers in an EH node are given. Being exposed to cyber security threats， the integrated energy cyber physical system comprehensively takes complementarity of different energy sources， network transmission and distribution of energy， energy storage， clean energy's dynamic access to the grid and other operational requirements into considerations， and adopts a three-element and three-layer secure trusted protection architecture based on trusted computing technology. Starting from protecting every energy node， this protection system constructs a protection mechanism based on node trust， network connection trust and application trust， to ensure the safe and reliable operation of the IES. Table and Figures | Reference | Related Articles | Metrics

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Review on impedance modeling of grid-connected inverters under weak grid conditions ZHUO Chaoran, XIN Jie, HONG Hanzhuo, AN Bang, LI Ning Integrated Intelligent Energy    2024, 46 (6): 88-101.   DOI: 10.3969/j.issn.2097-0706.2024.06.010 Abstract （195）   HTML （4）    PDF （1245KB）（474）       Knowledge map    The impedance analysis method has become an important means of studying the stability of the interaction system between grid-connected inverters and the power grid. To make further investigations， two control modes for grid-connected inverters are reviewed， and the impact of impedance modeling on the power system stability and broadband oscillation suppression are analyzed， providing a theoretical basis for solving the broadband stability problem in new power systems.Then，grid-connected inverters' impedance modeling methods including dq linearization，harmonic linearization， as well as the impedance model identification method based on neural networks are expounded. The comparison on the modeling methods facilitates their practical applications. The summaries on the advantages，challenges and opportunities of impedance modeling methods for grid-connected inverters in existing power electronic systems provide guidance for improving the stability of the interaction system. Table and Figures | Reference | Related Articles | Metrics

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Optimized scheduling on large-scale hydrogen production system for off-grid renewable energy based on DDPG algorithm ZHENG Qingming, JING Yanwei, LIANG Tao, CHAI Lulu, LYU Liangnian Integrated Intelligent Energy    2024, 46 (6): 35-43.   DOI: 10.3969/j.issn.2097-0706.2024.06.005 Abstract （193）   HTML （3）    PDF （3212KB）（750）       Knowledge map    To improve the renewable energy consumption， reduce the investment on rectifiers and grid connection equipment， cut down the cost of water electrolysis for hydrogen production through powering hydrogen production by renewable energy， an islanded renewable energy large-scale hydrogen production system is constructed. An intelligent energy management platform can improve the economy and safety of the system. Firstly， a simulation model of the renewable energy large-scale hydrogen production system is established and its control strategy is formulated. Secondly， an energy optimization scheduling strategy based on deep deterministic policy gradient （DDPG） algorithm is proposed. Through long-term trainings， the agent obtained from the DDPG algorithm can achieve intelligent dynamic optimized scheduling on energy. Comparing the performances of the proposed strategy with deep Q network （DQN）， Particle Swarm Optimization （PSO） and traditional control methods in terms of economy and safety， it is shown that applying the DDPG algorithm in energy optimization and management can get higher economic returns and utilization rates of renewable resources， and ensure the safe operation of the system. Table and Figures | Reference | Related Articles | Metrics

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Comprehensive benefit analysis on the cascade utilization of a power battery system HUANG Xiaofan, LI Jiarui, LIU Hui, TANG Xiaoping, WANG Ziyao, WANG Tong Integrated Intelligent Energy    2024, 46 (7): 63-73.   DOI: 10.3969/j.issn.2097-0706.2024.07.008 Abstract （185）   HTML （3）    PDF （1113KB）（236）       Knowledge map    With the development of clean energy， new energy vehicles gradually entered the market. As an energy storage device and an important component of a new energy vehicle， the power battery will see its performance degradation with the extension of time and changes in working conditions until its decommissioning. The retired power battery can be applied to other fields to improve its full-life cycle value. A life-cycle assessment（LCA） model and a life-cycle cost（LCC） model for the cascade utilization of a power battery system are developed. The environmental impacts of a pack of lithium iron phosphate batteries' five stages from production to recycling on global warming potential （GWP） are calculated by the LCA. The GWP， fine particulate matter formation （FPMF）， terrestrial acidification （TA）， marine eutrophication （MEP）and fossil resource scarcity （FRS） of the battery system under four scenarios are analyzed， and sensitivity analyses on parameters such as energy consumption and charging and discharging efficiency are conducted. LCC assessment analyses the net present value （NPV） and levelized cost of electricity （LCOE） of the battery system， and sensitivity analyses are performed on parameters that affected LCOE， such as energy storage efficiency and discharge depth. The results show that retired batteries processed by wet recycling applied to wind energy storage have favorable social benefits， leading to a smallest GWP of 194. The NPV and LCOE of the system with a 15-year service time are -42.066 million yuan， 2.44 yuan/（kW·h）， respectively. Making quantitative analyses on the social and economic benefits of the cascade utilization of power battery energy storage systems is of great significance for comprehensive utilization of resources and environmental protection in China. Table and Figures | Reference | Related Articles | Metrics

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Risk analysis on the source-grid-load-storage system affected by cyber attacks YU Sheng, ZHOU Xia, SHEN Xicheng, DAI Jianfeng, LIU Zengji Integrated Intelligent Energy    2024, 46 (5): 41-49.   DOI: 10.3969/j.issn.2097-0706.2024.05.005 Abstract （184）   HTML （2）    PDF （2407KB）（144）       Knowledge map    With the boost of Energy Internet， power grid dispatching is gradually taking "source-grid-load-storage" integrated optimization strategy. The optimization mode can realize effective use of clean energy，sharing of resources and demand response of an integrated system with optimal allocation of resources，multi-energy complementation，big data analysis and other advanced technologies. However， due to the deep coupling of physical devices and information systems， cyber attacks aiming at information systems might lead to physical faults. To evaluate the effect of cyber attacks on a source-grid-load-storage integrated system， the effect of cyber attacks is analyzed from the perspective of attackers. Then， the improved attack graph is built， and attack routes are determined by Frequent Pattern Growth（FP-Growth）association rule mining. Then， the probability of being aimed and attacked is obtained by vulnerability assessment and Bayesian theorem. The risk assessment index is the product of the probability of cyber attack on the source-grid-load-storage integrated system and the load loss. The risks of distribution network circuit breakers and distributed sources subjected to cyber attacks are quantitively assessed， and the effectiveness of the proposed method is verified. Table and Figures | Reference | Related Articles | Metrics

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Construction of the hierarchical autonomous power balance model for software-defined new power systems WANG Zening, LI Wenzhong, LI Donghui, XU Taishan, YU Jun Integrated Intelligent Energy    2024, 46 (7): 1-11.   DOI: 10.3969/j.issn.2097-0706.2024.07.001 Abstract （180）   HTML （10）    PDF （1001KB）（160）       Knowledge map    As a typical complex system， a new power system energy is of severe power and energy imbalances resulting from the strong uncertainty of sources and demands. The balances are challenged by the basic alteration of electric energy and power balance logic. To make a new balance between coordinated and interactive sources， networks， loads and storage devices， a hierarchical autonomous power balance model with energy autonomous units is constructed. The hierarchical structure can simplify complex systems， and energy autonomous units have self-dispatching and self-balancing capacities. The units whose forms vary with different electricity market models provide effective paths for multiple resources to participate in the power market. In software paradigm theory， an energy autonomous unit is of an architecture that can integrate multiple elements， an adaptive operation mechanism， and a life-cycle evolution mechanism. Additionally， the construction methodology of software-defined energy autonomous units based on software-hardware decoupling is proposed. Finally， the key technologies applied in the units are discussed and looked forward. Table and Figures | Reference | Related Articles | Metrics

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Research on network attack modeling， evolution and response cost of power cyber physical systems YE Fei, ZHONG Xiaojing, GUAN Qianfeng Integrated Intelligent Energy    2024, 46 (5): 58-64.   DOI: 10.3969/j.issn.2097-0706.2024.05.007 Abstract （179）   HTML （11）    PDF （2144KB）（146）       Knowledge map    With the frequent interactions between the cyber layer and the physical layer， power cyber physical systems （CPSs） are facing great security challenges. Network attacks propagating from the cyber layer to the physical layer may cause the collapse of the entire power system. A new type of network attack propagation model，SIAIBRARB，is established based on the double-layer coupling structure of power CPSs and the propagation evolution theory. The model describes the propagation behavior of network attacks in power network nodes. Using dynamic analysis method， we analyze the attack intensity and influence range of a network attack on a power CPS，and provide a specific algorithm to predict the attack intensity. Moreover， the PRCCs and 3D correlation partial differential method are used to analyze the sensitivity of system parameters. The importance of the power CPS network structure and propagation probability to network security have been verified by two simulation tests. Taking the prior case of China Southern Power Grid Company Limited as an example， its typical design and costs are summarized，and the variation of the actual construction cost of the power network security protection system is analyzed. Considering from three perspectives， the construction of a security protection system can be precisely graded， in which the construction costs and CPS security should be considered simultaneously. The theoretical results can provide a reference for power grid defenders to develop new defense schemes under the threat of network attacks. Table and Figures | Reference | Related Articles | Metrics

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Low-carbon operation control on park-level integrated energy systems considering shared energy storage devices for electric vehicles WANG Jun, TIAN Hao, ZHAO Ergang, SHU Zhan, WAN Zijing Integrated Intelligent Energy    2024, 46 (6): 16-26.   DOI: 10.3969/j.issn.2097-0706.2024.06.003 Abstract （179）   HTML （3）    PDF （1082KB）（84）       Knowledge map    In the context of achieving "dual carbon" goals， industrial parks， serving as the main force in energy conservation and carbon reduction，can advance energy efficiency and carbon reduction. A low-carbon operation control model for industrial parks that considers the characteristics of shared energy storage devices for electric vehicles is proposed. Firstly， a ladder-type carbon trading mechanism is introduced to the calculation on dynamic carbon emission factors of nodes in the model， and emission reductions made by electric vehicles are considered into carbon quotas. Then， ground source heat pumps are introduced to the supply side of the park， meeting the thermal load demands through electric-to-thermal conversions. And shared energy storage devices for electric vehicles are introduced to the demand side. Considering the characteristics of these devices， the model for shared energy storage is established. Finally， taking carbon trading costs， electricity purchase costs and response subsidy costs into account， an optimized low-carbon operation model for industrial parks is established with the objective of minimizing operational costs. The optimization is carried out by using the CPLEX software. Simulation results demonstrate that considering the shared energy storage devices of electric vehicles and upgrading the ladder-type carbon trading mechanism can effectively reduce the operational cost and carbon emissions of the industrial park， validating the economy and carbon reduction of the model proposed. Table and Figures | Reference | Related Articles | Metrics

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Construction of new power system in Shaanxi Province with the collaboration of source-network-load-storage HE Fangbo, PEI Ligeng, ZHENG Rui, FAN Kangjian, ZHANG Xiaoman, LI Gengfeng Integrated Intelligent Energy    2024, 46 (7): 40-46.   DOI: 10.3969/j.issn.2097-0706.2024.07.005 Abstract （177）   HTML （6）    PDF （1489KB）（117）       Knowledge map    In the context of achieving "dual carbon" target，the domestic power industry is actively conducting researches on energy transformation path ，aiming at building a new power system with new energy as the mainstay. Shaanxi Province is the main battlefield of the "dual carbon" action due to its rich resource endowments and its favorable location as a major sending end for clean energy. Based on the fact of the power industry in Shaanxi Province， the current situation and problems are analyzed from source，network，load and storage end，and a construction concept of the new power system in Shaanxi Province with the collaboration of source-network-load-storage is put forward. The source end should take new energy as the main body and the traditional units as the guarantee；the network should be able to accommodate high-proportion new energy， get multiple loads accessed and take in diversified market entities；the load side should make active responses to resource adjustments and endeavor to build a multi-energy complementary system for new energy consumption；the storage end should establish and improve relevant mechanisms as soon as possible to facilitate energy storage and new energy accommodation. Finally，suggestions which can extend the application scope of the proposed concept to other provinces and cities are given. Table and Figures | Reference | Related Articles | Metrics

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Development trend analysis on building energy systems under "dual carbon" target ZOU Fenghua, ZHU Xingyang, YIN Junping, MENG Shiyu, JIANG Haiyan, CHEN Aikang, LIU Lan Integrated Intelligent Energy    2024, 46 (8): 36-40.   DOI: 10.3969/j.issn.2097-0706.2024.08.005 Abstract （175）   HTML （3）    PDF （1000KB）（114）       Knowledge map    With the continuous access of flexible energy sources such as distributed new energy and electric vehicles，the potential of building energy systems in energy conservation and carbon reduction gets inspired.It is of great significance to clarify the development trend of building energy systems for achieving the goals of carbon peak and carbon neutrality in urban areas.Since the building energy system whole process includes system construction，operation and management，the new system structure，energy supply mode，system operation mode，digital management，demand response and control mechanism should be analyzed comprehensively.Based on the analysis results，the development trend of building energy systems towards production and marketing integration，low carbonization，flexibility，digitization and standardization are prospected，which provides reference for the high-quality development of urban building energy systems. Table and Figures | Reference | Related Articles | Metrics

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Photovoltaic power forecasting model based on probabilistic TCN-Transformer SHENG Ruixiang, ZHANG Xiaoyu Integrated Intelligent Energy    2024, 46 (11): 10-18.   DOI: 10.3969/j.issn.2097-0706.2024.11.002 Abstract （173）   HTML （5）    PDF （1450KB）（339）       Knowledge map    A short-term PV power prediction method based on a temporal convolutional network （TCN） and a Transformer structure is proposed. Firstly， the main factors affecting PV power generation，such as wind speed， rainfall， light intensity and cloudiness， are analysed. Then， TCN is used to extract the global spatial features of the sequence， and Transformer is used to extract the temporal features of long-term dependencies in the sequence， so that a TCN-Transformer composite model with a high prediction precision is applied to PV power deterministic and probabilistic prediction. Simulation analyses are performed on the dataset from DKASC（Australia）， and the results show that the improved TCN-Transformer model exhibits excellent prediction performance under different weather conditions， improving the short-term prediction accuracy on PV power. Table and Figures | Reference | Related Articles | Metrics

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Pricing mechanism and optimal scheduling of virtual power plants containing distributed renewable energy and demand response loads LI Mingyang, DONG Zhe Integrated Intelligent Energy    2024, 46 (10): 12-17.   DOI: 10.3969/j.issn.2097-0706.2024.10.002 Abstract （172）   HTML （7）    PDF （1775KB）（62）       Knowledge map    Faced with the widespread integration of distributed wind power， photovoltaic power generation， and flexible loads into the grid， aggregating these resources through virtual power plants （VPPs） and adopting a reasonable pricing mechanism to guide users to participate in demand response can effectively enhance the absorption capacity of renewable energy and reduce overall operating costs. Traditional time-of-use pricing mechanisms often struggle to achieve a good match between demand response loads and renewable energy output， which may result in irrational or excessive demand response. To address this， a VPP internal pricing mechanism based on renewable energy output was proposed for VPPs containing distributed wind power， distributed photovoltaic power generation， and flexible loads. Power trading priorities were set to guide the optimal operation of internal VPP resources， with the goal of minimizing the overall operating costs of the VPP. A mixed integer linear programming （MILP） model was constructed for optimal VPP scheduling. Simulation results based on real data from a region in Inner Mongolia show that， compared to optimization results based on traditional time-of-use pricing， this method significantly improves renewable energy utilization and reduces VPP operating costs. Table and Figures | Reference | Related Articles | Metrics