国网河北省电力有限公司

[Objective]High-penetration distributed photovoltaic(PV)grid integration leads to insufficient power absorption capacity in distribution networks.Meanwhile,the development of new distribution systems imposes higher reliability requirements.Grid-forming energy storage,with its flexible power synchronization control capabilities,possesses the ability to both promote distributed PV consumption and enhance reliability in new distribution networks.This paper proposes an optimal configuration model for grid-forming energy storage that considers both distributed PV consumption and reliability improvement in distribution networks.[Methods]First,a bi-level optimization model for the siting and sizing of grid-forming energy storage is established.The upper-level model considers fault conditions and load importance to establish an energy storage siting model for improving distribution network reliability.The lower-level model considers the uncertainty of distributed PV systems to establish an energy storage sizing model for enhancing PV consumption.Specifically,the confidence set for the probability distribution of PV uncertainty is constrained by 1-norm and ∞-norm constraints,and is solved using the column and constraint ceneration(CCG)algorithm based on the distributionally robust optimization.Second,a comprehensive evaluation index system incorporating reliability,distributed PV consumption,and economic performance is established.The optimal configuration scheme is obtained using an improved Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method.[Results]The proposed algorithm is validated through a modified 33-node test system.The results show that compared with traditional energy storage schemes,the proposed model improves the reliability index by more than 10%,and reduces the distributed PV curtailment rate by 7.44%.The optimal effect is achieved by configuring grid-forming energy storage at four key nodes.[Conclusions]The proposed grid-forming energy storage optimization configuration method significantly improves the distributed photovoltaic capacity and reliability of distribution network,providing reference for planning and investment in distribution networks with high-penetration distributed PV integration.

With the increasing penetration of renewable energy sources in the active power distribution network,their inherent randomness and intermittency pose significant challenges to existing scheduling strategies.This paper proposes an economic dispatching strategy for active distribution network based on multi-agent deep reinforcement learning.Firstly,it constructs a multi-area framework for renewable energy autonomy,with each autonomous region corresponding to an intelligent agent.The multi-agent deep reinforcement learning(MADRL)algorithm is applied to address the collaborative economic dispatching issues across regions.Secondly,it models the active distribution network containing wind turbines and energy storage devices at the regional level,with economic optimization objec-tives and operational constraints set.Finally,building upon the multi-agent deep deterministic policy gradient(MADDPG)algorithm,the bidirectional gated recurrent unit(BiGRU)is employed instead of fully connected lay-ers for renewable energy output prediction,effectively mitigating the impact of renewable energy fluctuations.The effectiveness of the proposed strategy and the superiority of similar algorithms are validated through using an im-proved IEEE 33-node test system.

In the process of promoting the low-carbon transformation of power systems， integrating cyber， physical， and social factors is crucial for effectively managing carbon assets on the user side and implementing low-carbon scheduling in virtual power plants （VPPs）. To this end， this paper proposes a low-carbon scheduling model for VPPs based on a cyber-physical-social system （CPSS）. First， a low-carbon scheduling framework for VPPs is established under the CPSS. Then， considering the coupling characteristics of dynamic carbon emission factors and users’ response behavior over time， a user-side carbon asset development evaluation system based on carbon asset price coefficients is built to obtain an optimized user sequence for low-carbon demand response. Finally， an optimization model is proposed with the objective of minimizing carbon emissions from VPPs， and orderly scheduling is performed based on the optimized sequence. Case analysis on the IEEE 33-node system demonstrates that the proposed low-carbon scheduling method maximizes adherence to users’ electricity consumption patterns while fully exploiting user-side carbon assets， thereby achieving low-carbon scheduling for VPPs.

In order to remove highly toxic Cr(Ⅵ)from desulfurization wastewater of thermal power plants,activated carbon(AC)coupled with nitrogen-rich carbon nitride(C3N5)composite(C3N5/AC)was prepared by in-situ growth method.X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),X-ray photoelectron spectroscopy(XPS),N2 adsorption-desorption isotherms(BET),UV-vis diffuse reflectance spectroscopy(UV-vis DRS),steady-state fluorescence spectroscopy(PL),and electrochemical impedance spectroscopy(EIS)were used to characterize the crystalline phase,characteristic groups,elemental composition,specific surface area and pore size,spectral ab-sorption range and response intensity,photogenerated carrier recombination ability,and charge transfer resistance of C3N5/AC in detail.The photocatalytic activity and stability of C3N5/AC for the treatment of simulated wastewater con-taining Cr(Ⅵ)were investigated.The results showed that the specific surface area of the composite reached 51.24 m2/g at the AC coupling amount of 3％(mass fraction),which was 8 times that of pure C3N5.AC coupling improved the visible-light response intensity of the material,realized the efficient separation of photogenerated carriers,and ef-fectively reduced the charge transfer resistance.C3N5/AC exhibited excellent Cr(Ⅵ)removal activity.The removal rate of Cr(Ⅵ)by C3N5/AC with 3％AC coupling amount reached 92.46％under visible light irradiation,and showed good stability after 5 cycles.The proposed mechanism for photocatalytic removal of Cr(Ⅵ)from wastewater by C3N5/AC involved the reduction of Cr(Ⅵ)to Cr(Ⅲ)by e-and O2·-under acidic conditions.

The research on uninterrupted loop-closing load transfer in distribution network is of great significance to ensure the high requirements for power quality and supply reliability in industrial production and residential elec-tricity.At present,the loop-closing of the distribution network usually requires the use of additional devices,which has problems such as poor economic efficiency.In recent years,the research on power electronic transformers based on multiple-AC-ports has gradually attracted attention and has been put into practical application.For this application scenario and the demand for uninterrupted loop-closing load transfer,flexible loop-closing can be a-chieved based on the control of different ports of power electronic transformers to expand its application functions.This paper proposes an AC flexible loop-closing scheme based on the multiple-AC-ports cascaded H-bridge type power electronic transformer(MAC-CHB-PET).The structure of MAC-CHB-PET is analyzed.The internal mecha-nism of the impulse current and steady-state current generated during loop-closing are analyzed,and a power com-mand value calculation method based on MAC-CHB-PET loop-closing regulation is proposed based on the selected characteristic factors.Furthermore,the AC flexible loop-closing scheme for uninterrupted load transfer is proposed,based on MAC-CHB-PET,which adopts coordinated control of active and reactive power at two AC ports to regulate the AC bus voltage and achieve AC flexible loop-closing.A simulation model is established to verify the feasibility of the proposed AC flexible loop-closing scheme.