Integrated Intelligent Energy

Numerical simulation on the wind blocking and speed increasing effect of trough solar arrays

ZHANG Lidong, LI Pei, JIANG Tieliu, LI Qinwei, ZHANG Lei, XU Feng, MENG Xin

2024, 46(6): 1-7. doi:10.3969/j.issn.2097-0706.2024.06.001

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Taking the Simple solver of the open source computational fluid dynamics （CFD） software， OpenFOAM， to numerically simulate a flow field， the wind blocking effect of a windbreak under a wind speed of 5.00 m/s is studied. The windbreak is composed of trough solar arrays. The effects of the barrier at six different heights and with three different distances （30， 60， and 90 m） from its leeward side to the flow field on the overall velocity of the flow field are analyzed. It is found that there is obvious partitioning in the blocking effect. When the airflow passes through the windbreak wall， the flow velocity attenuates significantly at a position lower than the height of the wall， and it accelerates at a position higher than the wall. There is a velocity attenuation area behind the wall， whose size is highly positively correlated with the height and distance of the wall. When the distance of the leeward side gets farther， the flow velocity at a position higher than the wall gets slower and that at a position lower than the wall gets faster. The wind velocity gets stable with the extension of the distance from the leeward side to the flow field.

Research on fault diagnosis of active distribution network based on parallel fusion deep residual shrinkage network

FENG Ji, YANG Guohua, SHI Lei, PAN Huan, LU Yuxiang, ZHANG Yuanxi, LI Zhen

2024, 46(6): 8-15. doi:10.3969/j.issn.2097-0706.2024.06.002

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Since the faults of the distribution networks with distributed generators present diversity，and the fault diagnoses are vulnerable to nonlinear factors such as the type of distributed generators and their outputs， a fault diagnosis model based on a parallel fusion deep residual shrinkage network（P-FDRSN） is proposed. The P-FDRSN is constructed by two parallel networks， a fault identification branch and a fault location branch. The parallel structure introduces shrinkage mechanism into its residual module to reduce the influence of noise or redundant information on the network and to improve the robustness of the network against noise. After transforming fault recording signal waveforms into grayscale images and time-frequency images，the signals are fed into the DRSN for deep feature extraction， and then， the acquired features are fused in the convergence layer， so as to enhance the feature learning capability on the fault recording signals. Finally， the simulation results show that the fault location and identification accuracies of the proposed model for various types of distributed generators of different outputs can be maintained above 98.75% and 97.25%， respectively. Even under the interference of noise，the diagnosis accuracy of the model will be kept above 96.75%，showing a high accuracy and decent robustness.

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

2024, 46(6): 16-26. doi:10.3969/j.issn.2097-0706.2024.06.003

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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.

Optimal scheduling of virtual power plants integrating electric vehicles based on reinforcement learning

LI Mingyang, DOU Mengyuan

2024, 46(6): 27-34. doi:10.3969/j.issn.2097-0706.2024.06.004

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Disorderly charging behaviors of massive electric vehicles （EVs） may cause violent fluctuations in power loads， affecting the security and stability of the power grid. With the application of vehicle to grid（V2G） technology， the scheduling method can be optimized by aggregating EV charging stations and surrounded distributed renewable energy generators into a virtual power plant（VPP）. The aggregation can improve the economy of charging behaviors and satisfaction of EV users， raise the utilization rate of distributed renewable energy， and mitigate load fluctuations in the grid. However， the overall charging or discharging load is the aggregation result of random charging or discharging behaviors of massive individual EVs， which is difficult to be accurately described by mathematical models. Thus，an interactive optimal scheduling framework based on deep reinforcement learning is presented for a VPP including EVs， with the objective of maximizing the benefit of all EV users in the VPP. The VPP control center，serving as an intelligent agent， can decide the charging and discharging of individual EVs without their detailed models. The agent continuously learns and updates its strategies through interactions with regional grids， overcoming the limitations of centralized optimal scheduling. The framework is solved by Deep Deterministic Policy Gradient（DDPG） algorithm. Simulation results show that， compared with the centralized scheduling， the proposed method improves the benefits of individual EV users， and the coordinative scheduling of EV charging/discharging loads and renewable energy outputs shaves the peak loads in the grid， and boosts the overall performance of the VPP.

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

2024, 46(6): 35-43. doi:10.3969/j.issn.2097-0706.2024.06.005

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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.

Distributed photovoltaic-energy storage reactive power optimization method for distribution networks under cloud energy storage mode

WANG Lin, KONG Xiaomin, ZHOU Zhongyu, LIU Jianping, WANG Xiaodong, ZHANG Ning

2024, 46(6): 44-53. doi:10.3969/j.issn.2097-0706.2024.06.006

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Aiming at the problems caused by the access of high-proportion distributed photovoltaic to distribution networks， such as power fluctuations， over-limit voltages， line overloads and excessive line losses， a distributed photovoltaic-energy storage reactive power optimization method for distribution networks taking cloud energy storage mode is proposed. The method takes reactive power compensation price mechanism to encourage cloud energy storage devices to participate in distribution network voltage regulation auxiliary services， and fully employs the voltage regulation capacities of distributed photovoltaic panels， static var compensators（SVCs）， shunt capacitors（SCs） and on-load tap changers（OLTCs）. Finally， taking the minimum operation cost and minimum voltage deviation of a distribution network as optimization objectives， an economic optimization model of the distribution network system based on the flexible multi- resources regulation of cloud energy storage devices is established. Simulation analysis shows that the participation of cloud energy storage in the joint optimization of active and reactive power is helpful to stabilize the voltage fluctuation of the distribution network， alleviate the voltage regulation pressure of the reactive power compensation device and reduce the line power loss， guaranteeing the safe and economic operation of the distribution network system.

Capacity allocation optimization of hybrid energy storage systems considering fluctuation control on offshore wind power

ZHANG Xunxiang, WU Jiekang, SUN Yehua, PENG Qijian

2024, 46(6): 54-65. doi:10.3969/j.issn.2097-0706.2024.06.007

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The strong fluctuation of offshore wind power makes it difficult to keep the variation within limitations when wind power is connected to the grid. In order to stabilize offshore wind outputs， a capacity allocation method for a hybrid energy storage system（HESS）considering offshore wind power fluctuation is proposed. Firstly， the weighted moving average filtering method is used to obtain the output information instructions for the HESS. Then， energy valley optimizer（EVO） is used to optimize the modal decomposition number N and penalty factor $ϑ$ of the variational mode decomposition（VMD）， and the VMD with optimized parameters is used to decompose the HESS power instructions. Finally， an optimized cost model for the HESS is constructed with the goal of minimizing the average daily cost of the HESS in its whole life cycle. The optimal energy storage allocation scheme is established by allocating the HESS power based on optimal frequency division points. The simulation results show that the method proposed can effectively improve the economy of the HESS installed to stabilize wind power outputs， providing a reference for the grid connection of an offshore wind power station integrated with an energy storage system.

Economic dispatch and profit distribution strategy for multi-agent virtual power plants considering risk preferences

YU Haibin, LU Wenzhou, TANG Liang, ZHANG Yuchen, ZOU Xiangyu, JIANG Yuliang, LIU Jiabao

2024, 46(6): 66-77. doi:10.3969/j.issn.2097-0706.2024.06.008

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Virtual power plants （VPPs） are playing an increasingly prominent role in new power systems， while the operational strategies and revenues of a VPP with distributed energy resources（DERs）are affected by the fluctuated outputs of wind turbines and PV generators in the plant. A fair， reasonable and transparent benefit distribution mechanism is the key to maintaining the cooperation between different DERs in a VPP. To motive various entities in a VPP to participate in trades， the profit is allocated among different entities based on their own characteristics and contributions though consultations. An optimal scheduling and profit distribution strategy is proposed for the VPP integrating wind turbines， PV generators， controllable distributed power suppliers and flexible loads considering their risk preferences. The multi-agent VPP participates in the electricity market （EM），and its profit distribution model is built based on Nash-Hassanyi bargaining solution. A numerical analysis is carried out，aiming to maximize the operational efficiency， guide the operation and reduce the operation risk of the VPP. The results verify that the proposed benefit distribution method can effectively balance the interests of all parties， quantify the actual economic contribution of each DER to the VPP， and improve the willingness of each entity to participate in market competition. The benefit allocation mechanism using Nash-Hassanyi solution is superior to that using Shapley value method in terms of allocation rationality and applicability.

Key technologies of the evaluation on distributed wind-storage systems' frequency and voltage regulation capacities

ZHAO Changwei, WANG Hui, GU Zhicheng, LIU Xubin, ZHU Guangming, GE Leijiao

2024, 46(6): 78-87. doi:10.3969/j.issn.2097-0706.2024.06.009

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The wide and scattered connection of wind power to medium/high voltage distribution networks is getting popular，resulting in insufficient frequency and voltage support of weak power grids. The evaluation on the frequency and voltage regulation capacities of distributed wind-storage systems is helpful for the scheduling and management of grids，detecting and avoiding potential problems that could destroy the stability of grids timely，but the construction of an evaluation system is thorny due to its complex and variable structure. To fulfill the construction， the influence factors， comprehensive evaluation indicators and comprehensive evaluation method for the systems' frequency and voltage regulation capacities have to be considered comprehensively in analyzing existing technical methods and pointing out the key techniques and challenges. The study focuses on the following contents：multi-time scale high-precision wind power output forecasting technology，adjustment capacities of different wind-storage system configuration schemes under different conditions;calculation and improvement methods of the frequency-voltage regulation capacity and contribution index of a distributed wind-storage system under multi-modal coupling condition; improvement on the robustness of evaluation method under uncertain conditions. Finally， new ideas on frequency and voltage regulation capability evaluation for distributed wind-storage systems are presented， to provide references for the development of wind power in China.

Review on impedance modeling of grid-connected inverters under weak grid conditions

ZHUO Chaoran, XIN Jie, HONG Hanzhuo, AN Bang, LI Ning

2024, 46(6): 88-101. doi:10.3969/j.issn.2097-0706.2024.06.010

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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.

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