Metallic foreign objects in various types of power equipment may cause discharge problems. To achieve accurate multi-spectral monitoring of the discharge phenomenon caused by metallic foreign object, it is necessary to deeply understand its influence on the mechanism of optical radiation during discharge. Currently, research on the impact of metallic foreign objects on high-voltage discharge is mostly focused on the macro level, without delving into the micro-particle level to analyze its effect on the discharge mechanism, and the influence of metallic foreign object on optical radiation during discharge has not been thoroughly explored. To address these issues, this paper analyzes the characteristics of metallic foreign object's impact on the full-band optical radiation of discharge and its influence mechanism on the day-blind ultraviolet band through experiments and simulations.
A high-voltage discharge experimental platform was first constructed. Discharge images were captured using ultraviolet and high-speed cameras, and the emission spectra were measured with a spectrometer to investigate the influence of metallic foreign object on full-band optical radiation during discharge. The effect of metallic foreign objects on the generation of day-blind ultraviolet radiation was further studied. It was verified that the particle transitions responsible for producing day-blind ultraviolet radiation are mainly $\mathrm{N}_{2}\left(\mathrm{~A}^{3} \Sigma_{\mathrm{u}}^{+} \rightarrow \mathrm{X}^{1} \Sigma_{\mathrm{g}}^{+}\right)$ and NO-γ(A²Σ⁺(v′)→X²Π(v″)). Based on this, a two-dimensional plasma simulation model was constructed to investigate the effect of different quantities of large metallic particles and varying masses of metal shavings on the discharge process. The model was used to calculate the number densities of NO(A²Σ⁺) and $\mathrm{N}_{2}\left(\mathrm{~A}^{3} \Sigma_{\mathrm{u}}^{+}\right)$ particles under different conditions, and the simulation results were validated by comparing them with the measured spectra. The experimental and simulation results were then comprehensively analyzed to explore the influence of metallic foreign object on day-blind ultraviolet radiation during discharge.
High-speed camera reveals that metallic foreign object increases the chance of arc formation between the tip of the needle electrode and the metallic foreign object. From the spectrum of the 200-1000 nm band measured in the experiment, it is evident that the increase in metallic foreign object enhances the optical radiation across the entire spectrum generated by the discharge. However, this enhancement is selective to certain bands, with the ultraviolet and visible light bands responding more sensitively. Therefore, ultraviolet and visible light detection is more effective for monitoring discharges caused by metallic foreign objects.
Analysis of UV images, 240~280 nm spectra, and simulations shows that an increase in the metal foreign object causes an increase in the amplitude of the spectral curve of the sun-blind UV band, an increase in the number densities of NO(A²Σ⁺) and $\mathrm{N}_{2}\left(\mathrm{~A}^{3} \Sigma_{\mathrm{u}}^{+}\right)$ particles, and an increase in the rate of the chemical reactions in the discharge region; however, the spectral shape remains basically unchanged, which means that it does not affect the types of chemical reactions and the relative ratios among them. By combining the electric field simulation results, the reason can be analyzed as follows: the metal foreign object increases the strength and inhomogeneity of the electric field, promoting the excitation and ionization of particles. This leads to the production of more NO(A²Σ⁺) and $\mathrm{N}_{2}\left(\mathrm{~A}^{3} \Sigma_{\mathrm{u}}^{+}\right)$ particles, thus promoting the enhancement of the sun-blind ultraviolet radiation.
The results of this paper apply to discharge phenomena in air influenced by metallic foreign objects, and the influence of metal particles on discharge in SF₆ and its alternative gases will be further investigated in the future.

Electric aircraft has become a major development trend in the future aviation industry due to its advantages of low carbon and environmental protection. The air insulation of electric aircraft needs to withstand high-frequency voltage in high altitude. Therefore, this paper qualitatively studies the air discharge characteristics and microscopic mechanisms between needle-plate electrodes under different pulse voltage parameters and different humidity in the low temperature sub-atmospheric pressure environment of high altitude through simulation and experimentation.
Firstly, the pulse power supply was built by a 4-stage half-bridge Marx circuit. Then, the two-dimensional axisymmetric streamer discharge model of low-temperature sub atmospheric air was built, and three sets of Helmholtz equations were coupled to calculate the photoionization. Finally, the images of air streamer discharge under different conditions were captured by intensified charge coupled device (ICCD).
The following conclusions are drawn through simulation and experiment under the condition of low temperature and sub-atmospheric pressure: (1) The simulation outcomes reveal that when the reduced electric field strength remains the same, as the altitude increases, the breakdown voltage drops, the electron density gradually reduces, the electric field strength of the streamer head decreases, and the development speed of the streamer slows down. As the rising edge of the pulse grows, the electron density decreases simultaneously. When the discharge can be accomplished within one pulse, an increase in the pulse width has minimal effect on the discharge. Under the circumstances of low temperature and sub-atmospheric pressure, with the rise in humidity, the electron density increases concurrently, the peak value of the electric field intensity also rises, and the development speed of the streamer becomes faster. (2) The experimental results indicate that when the reduced electric field strength is consistent, with the increase of altitude, the penetration time of the streamer becomes longer, the channel brightness decreases, and the channel radius increases. When the pulse width of the pulse voltage is greater than the discharge time, the increase in the pulse width has no influence on the discharge process; when the frequency of the pulse voltage rises, the brightness of the streamer channel gradually intensifies; under the condition of low temperature and sub-atmospheric pressure, with the increase in humidity, the penetration time of the streamer becomes shorter and the brightness of the streamer channel increases. (3) Under the same conditions, the simulation and experimental results have a consistent conclusion regarding the development speed of the streamer. The influence of the pulse width on the discharge depends on whether the discharge can be completed within one pulse. The brightness of the streamer channel is positively correlated with the electric field intensity of the streamer head.

Sulfur hexafluoride (SF₆), which has strong electronegativity and self-recovery, exhibits excellent insulation and arc-extinguishing capabilities and is widely used in the field of power insulation. However, SF₆ is a strong greenhouse effect gas, and its global warming potential is 23 500 times that of CO₂, and its degradation can significantly reduce the pollution and harm of SF₆ to the atmosphere. Then, there are many kinds of toxic and harmful substances in SF₆ degradation products, among which sulfuryl fluoride (SO₂F₂), as the main decomposition product of SF₆, still has the greenhouse effect and huge toxicity and stable nature. The degradation of SO₂F₂ can improve the harmless degradation process of SF₆ and realize the harmless emission of SF₆. At present, many scholars at home and abroad for the treatment of SO₂F₂ waste gas treatment methods mainly include the alkali treatment method, adsorption method, Non-temperature plasma method, etc., in which the Non-temperature plasma method has the advantages of simple structure, ease of control, high efficiency, etc. Still, there is a problem of poor regulation of the product. By filling the catalyst, the degradation rate can be increased and the product selectivity can be improved. In this paper, the degradation of SO₂F₂ by dielectric barrier discharge (DBD) plasma synergistic filling materials was investigated, and the effects of γ-Al₂O₃, ZSM-5, and glass beads on the degradation of SO₂F₂ with different input powers were investigated.
The experimental platform for SO₂F₂ degradation by DBD plasma synergistic filler materials was first constructed. GC-MS was used to quantify SO₂F₂ and its degradation products, and the SO₂F₂ degradation rate and product content were calculated and detected. The experiments found that the addition of filling materials can improve the discharge conditions of the system, enhancing discharge voltage and current. Furthermore, the filling materials can effectively improve the SO₂F₂ degradation rate and energy efficiency (degradation rate: glass beads>γ-Al₂O₃>ZSM-5>no filler), and also change the decomposition path and product selectivity of SO₂F₂ to produce SO₂ that is easy to handle. 2% SO₂F₂ at a flow rate of 150 mL/min and a power of 100 W. As the input power increases, the degradation rate of SO₂F₂ gradually rises, while the energy efficiency shows an overall decreasing trend. With the filling of glass beads, the degradation rate and energy efficiency of SO₂F₂ were 99.5% and 7.69 g/(kW·h), respectively, and the concentration of SO₂ product was 9 278.56×10^-4%, under the same experimental conditions, the degradation rate of SO₂F₂ was lower than that of γ-Al₂O₃ and glass bead filling when ZSM-5 was filled, but the ZSM-5 filling could make SO₂F₂ decompose completely and directionally to SO₂, at which time the content of SO₂ The SO₂F₂ decomposition products are mainly SO₂, SOF₂, SOF₄ and SiF₄, etc. The results of the study show that the SO₂F₂ degradation rate is lower than that of γ-Al₂O₃ and γ-Al₂O₃ filling, but ZSM-5 filling can almost completely directional decomposition of SO₂F₂ to SO₂, at which time the content of SO₂ is 16 908×10^-4%. The results of the study provide reference solutions for the efficient degradation of SO₂F₂ and the harmless treatment of SF₆. The main decomposition products of SO₂F₂ include SOF₂, SO₂, SOF₄, and OF₂. The addition of a catalyst can alter the decomposition pathway of SO₂F₂, facilitating the generation of the more manageable SO₂. The degradation products also contain a significant amount of SiF₄, indicating that etching reactions have occurred.

With the development of wind power research, the factors considered in the simulation model are gradually increasing. The demand for wind turbine models that take into account both electrical and mechanical characteristics is increasing, thus promoting the development and application of co-simulation technology. However, the detailed electrical model has strict requirements on the simulation time step, which reduces the efficiency of co-simulation. Some scholars have properly simplified the electrical model to improve the simulation speed when carrying out co-simulation. But, improper selection of simulation time step has a negative impact on simulation accuracy. Therefore, this paper studies the model optimization and step size selection to solve the problem of the contradiction between simulation accuracy and speed.
First, the complex electrical model is optimized by ignoring the power electronic switching model and reducing the order of the higher-order model, so that the computational complexity is reduced and the application range of the simulation step size is increased. GH Bladed and Matlab/Simulink are selected to build the co-simulation platform. Then, a comprehensive evaluation method based on residual similarity and feature selection verification is proposed, which takes into account simulation accuracy and speed. The evaluation of simulation accuracy is divided into two aspects: global and transient difference. The comprehensive evaluation index is formed by combining the evaluation index of simulation accuracy and simulation speed in a weighted way to guide the selection of simulation time step. Finally, the co-simulation is carried out to verify the effect of the optimization model on the simulation efficiency under the conditions of wind speed disturbance, frequency disturbance and fault crossing disturbance. According to the simulation results and the comprehensive evaluation method, the reference suggestions for the selection of simulation step size are put forward.
Through simulation results and analysis, the following conclusions are drawn: (1) Through the optimized model, the co-simulation model can be run at a larger simulation time step, and the co-simulation efficiency is improved. (2) According to the proposed comprehensive evaluation method, the simulation results are evaluated from two dimensions of simulation accuracy and speed, which solves the problem of quantitative evaluation of the accuracy and speed of the model simulation results. (3) Through the co-simulation of various working conditions and the quantitative evaluation of simulation accuracy and speed, the following conclusions are drawn: Under the background of the simulation in this paper, under the condition of wind speed fluctuation, the simulation time step of co-simulation is chosen to be around 0.05 s; under the condition of frequency disturbance, the simulation time step of co-simulation is chosen to be around 0.01 s; under the condition of fault ride-through disturbance, the simulation time step of co-simulation is chosen to be around 0.005 s. (4) Based on the evaluation results of multi-condition simulation, the factors such as time scale of simulation condition and mutation characteristics of observed parameters should be fully considered in the selection of simulation time step. When the time scale is large and the observed parameters do not have mutation characteristics, the larger simulation time step can be selected. When the time scale is small and the observed parameters have mutation characteristics, the selection of simulation time step should be reduced appropriately.

Ice disasters can cause serious damage to power transmission network, it is crucial to enhance the resilience of power transmission network during ice disasters. Unlike extreme natural disasters such as hurricanes or earthquakes, ice disasters develop slowly and last long time. It is difficult to predict the development trend of ice disaster accurately due to the influence of microclimate and terrain on their geographic coverage. Currently, the spatiotemporal evolution patterns of ice disasters are not clear. The existing research on improving the resilience of power transmission networks considering the impact of ice disasters have not involved the temporal modeling of ice disaster scenarios. Therefore, the paper proposes a method for temporal modeling of ice storm scenarios based on multispectral satellite remote sensing. By combining multispectral remote sensing image fusion methods based on Laplacian pyramid decomposition, efficient extraction and analysis of the spatial distribution and temporal changes of ice-covered areas in Sentinel-2 satellite remote sensing images are achieved. Using partial differential convolution, ice-covered areas are predicted dynamically based on the fused images, and an ice disaster temporal model is constructed. Additionally, a conditional variational autoencoder is used to generate a set of ice disaster scenarios, which accurately reflect the spatiotemporal characteristics of "source-network-load" during ice disasters.
Considering the interaction between the disaster development process and resilience enhancement measures, the power transmission system resilience can be simultaneously enhanced through both pre-disaster prevention and in-disaster repair measures. This paper proposes a comprehensive resilience evaluation index and constructs a two-stage robust resilience enhancement planning model for power transmission networks based on the set of ice disaster scenarios. The first stage focuses on pre-disaster fixed energy storage configuration and pre-planning of maintenance resources to find the optimal investment decision. The second stage focuses on in-disaster power supply through fixed energy storage and emergency maintenance considering limited maintenance resources, ensuring rapid response from fixed energy storage and maintenance teams after the occurrence time of the ice disaster, which aims to ensure rapid load recovery, maximize system resilience, and minimize system economic losses. The model is iteratively solved using a parallelizable column-and-constraint generation algorithm.
Finally, case studies are conducted using ice-covered remote sensing data from a region in Yunnan and a modified IEEE RTS-79 power transmission system as the test system. The results show that the coordination of fixed energy storage power supply and emergency maintenance can effectively ensure power supply and transmission during ice disasters, as the system resilience improved by 90.97% and total system losses decreased by 43.19% during the ice disasters. Compared with other resilience enhancement strategies, the proposed strategy in this paper balances both economic efficiency and resilience. What’s more, different ice disaster center locations are set in the case study considering the inherent uncertainty of ice disasters. The results demonstrate that for ice disasters with multiple origins, the proposed method effectively ensures power restoration in the transmission system, enhances system resilience, reduces load shedding losses and total costs.

Under the two-stage voltage control architecture of provincial regulation, the superior dispatching control center directly sends the voltage command value to the automatic voltage control (AVC) sub-stations of each wind farm, and the AVC sub-stations of each wind farm in the wind power cluster independently perform voltage control without communication with each other. In this case, the AVC sub-stations of each wind farm can only obtain the operation data of the local station. The high efficiency and accuracy of reactive power allocation cannot be achieved through AVC master station, which makes the voltage regulation efficiency of wind power cluster low. In addition, due to the different response time of the energy management platform and the wind turbine, the voltage regulation response speed of the wind farm is also different. Wind farms with fast regulation speed bear more reactive power, and wind farms with slow regulation speed bear less reactive power, resulting in unbalanced reactive power and waste of reactive power regulation capacity.
Firstly, this paper analyzes the influence of reactive power regulation period and regulation step of AVC sub-station on the voltage control of wind farm grid-connected point. Considering that the operating parameters of each wind farm equipment in the actual system are relatively fixed, the reactive power regulation period is not easy to change, and the fixed adjustment step cannot take into account the adjustment speed and adjustment accuracy. Therefore, this paper focuses on improving the voltage regulation speed of wind farm by changing the reactive power regulation step length.
Secondly, because the voltage of the wind farm grid-connected point is not only related to the reactive power output of its own station, but also affected by the reactive power output of other stations, this paper proposes a voltage control strategy of the AVC sub-station of wind power plant based on "variable step perturbation observation". This strategy changes the output reactive power of the wind power plant, and then measures the voltage change of the grid-connected point, and evaluate the influence of voltage control of other wind farms on the wind farm grid-connected point, dynamically adjust the reactive power regulation step of AVC sub-station, improve the voltage regulation speed of the wind farm, so that the voltage of the wind farm grid-connected point can enter the voltage dead zone faster.
Thirdly, in order to improve the reactive power imbalance in the wind power cluster, the reactive power constraint relationship of the wind farm stations in the cluster is established by analyzing the voltage reactive power coupling relationship between each wind farm, and considering the difference of the reactive power margin of each wind farm station, the variable step size control strategy is improved, and an improved wind farm voltage control strategy considering reactive power constraint is proposed. The voltage regulation speed and reactive power balance of wind power cluster are considered.
Finally, based on the operating data of a wind power cluster in East China, a simulation model of wind farm convergence system is built to verify the effectiveness of the proposed strategy.

In the existing energy storage system, pumped storage units have the advantages of large capacity, flexible operation, rapid start and stop, etc., and play an important role in the peak frequency regulation of the power system, and pumped storage units and wind power, photovoltaic power generation, etc. with the use of the power system can promote the new energy consumption level. However, the complex frequency domain characteristics presented by the multi-timescale control of the power electronic devices are prone to interacting with the power grid and triggering the oscillation phenomenon. Currently, there are relatively few studies on impedance modeling of the variable-speed pumped storage unit with full-size converter and their stability analysis based on impedance criterion. The impedance modeling of the variable-speed pumped storage unit with full-size converter and its analysis are of great significance for the future stability analysis of large-scale pumped storage units connected to the power grid. Therefore, this paper establishes an impedance model of the variable-speed pumped storage unit with full-size converter taking into account the frequency coupling effect, and analyzes the stability of the grid-connected system of the pumped storage unit based on the impedance model.
In the process of establishing the equivalent impedance model of the variable-speed pumped storage unit with full-size converter, the state-space model of the hydraulic turbine and the synchronous motor are firstly established, and the impedance model in the dq coordinate system is obtained on the basis of the model. After that, the impedance models of the machine-side converter and the grid-side converter are established respectively, and finally the equivalent impedance model of the variable-speed pumped storage unit with full-size converter considering the frequency coupling effect is established taking into account the effect of the grid impedance.
Further, the correctness of the impedance model of the variable-speed pumped storage unit with full-size converter was verified using the frequency scanning method. Based on the established impedance model, the grid-connected stability of the pumped storage unit under different grid impedance conditions is investigated by using Nyquist stability criterion. And the effects of key turbine and governor parameters as well as common control loop parameters such as phase-locked loop, DC voltage outer loop and current loop parameters of the full-power converter on the impedance characteristics of the unit as well as on the grid-connected stability are also investigated.
This study draws the following conclusions: (1) A more accurate equivalent impedance model of the variable-speed pumped storage unit with full-size converter that takes into account the frequency coupling effect is established. (2) As the grid impedance increases, i.e., the grid strength becomes weaker, the stability of the unit deteriorates. (3) Under the same grid strength, the bandwidths of the phase-locked loop and the current loop have a greater impact on the system stability, while the bandwidth of the DC voltage loop has a smaller impact on its stability. In addition, the values of the key parameters of the turbine as well as the governor have no significant effect on the impedance characteristics of the unit and very little effect on the stability of the system.

Addressing the issues of inadequate exploitation of hydrogen energy collaboration potential and the challenge in balancing accuracy and efficiency of probabilistic solution algorithms, this paper proposes a calculation method for the probabilistic optimal energy flow of electricity-hydrogen systems based on compressed sparse arbitrarily polynomial chaos expansions (CS-aPCE).
Firstly, to harness the spatial-temporal collaboration potential of hydrogen energy, a modeling approach for electricity-hydrogen optimal energy flow is introduced incorporating peer-to-peer (P2P) hydrogen collaboration between on-site and off-site hydrogen refueling stations (HRSs). Considering the P2P coupling of inter-station hydrogen flows and bidirectional electricity flows, a P2P collaboration mechanism is proposed for between on-site and off-site HRSs and the power distribution network. Based on Nash bargaining theory, a probabilistic optimal electricity-hydrogen energy flow model is constructed, which incorporates time-delay and discreteness constraints for inter-station hydrogen P2P transactions. This model coordinates multi-stakeholder benefit allocation and electricity-hydrogen price decisions, enhancing feasibility and fairness.
Secondly, a probabilistic optimal energy flow solution algorithm for on-site and off-site HRSs and power distribution networks is proposed based on CS-aPCE, aiming to improve the efficiency and accuracy of high-dimensional probability calculations. The core of this algorithm lies in leveraging historical data to drive the collocation points, subsequently calculating key statistical metrics such as expectations and standard deviations through analytical methods, without reliance on prior probabilistic information. To further optimize computational performance, the CS-aPCE algorithm integrates Gaussian quadrature rules to construct high-frequency collocation points and incorporates compressed sparse grid techniques. Effective compression criteria are proposed, and the dimensionality reduction effect and computational accuracy of the algorithm are theoretically proven, ensuring its efficiency and robustness under high-dimensional randomness.
The effectiveness of the proposed method is validated through numerical examples, leading to the following conclusions: firstly, the CS-aPCE algorithm presented in this paper can solve high-dimensional and probabilistic electricity-hydrogen energy flow problems rapidly and with high precision. The computation time is merely 10% of that required by the Monte Carlo simulation method, while the errors in expected values and standard deviations are below 4.21%. Furthermore, the computational accuracy for higher-order moments is improved by 60.28% to 156.98% compared to the traditional aPCE method. Secondly, the stationarity threshold exerts a certain influence on the accuracy and efficiency of the CS-aPCE algorithm. A reasonable threshold should be selected by comprehensively considering the stationarity distribution characteristics of random variables. Finally, the electricity-hydrogen optimal energy flow model considering P2P hydrogen collaboration between stations can mobilize the coordination potential of flexible resources within the distributed hydrogen supply network, coordinate the distribution of inter-station hydrogen flows, and achieve fair allocation of benefits among multiple stakeholders.

As electric vehicles (EV) grow more popular and vehicle-to-grid (V2G) technology advances, large-scale EV aggregations (EVA) have become integral to the power system. However, effectively capturing the distinct idle energy storage characteristics of EVAs across regions and integrating them seamlessly into power system operations remains a challenge. The shortcomings of existing research can be summarized as the follows: Firstly, current methods for assessing the dispatchable regions (DR) of EVs remain inadequate, lacking systematic frameworks and classification methods. Secondly, current multi-level coordinated control strategy often overlooks the holistic nature of coordinated control, which spans multiple levels, including the power grid, garage, and users. Merely considering factors related to EVs and their users is insufficient, as it fails to provide a comprehensive guidance for all coordinated control participants, such as the power grid and garage.
This paper addresses the aforementioned issues by conducting the following works. Firstly, methods for establishing multi-stage electric vehicle dispatchable region (MEVDR) for both EV and EVA are proposed and further investigated. Secondly, the probability density functions of various EV data in different regions and time periods of clustering centers are captured using Gaussian mixture model (GMM). Thirdly, the MEVDR of EVAs in different regions and time periods are established and comprehensively analyzed. Furthermore, the proposed MEVDR model can be used to construct multi-period constraints. Based on this, a vehicles-garage-grid multi-level coordinated control system (VGGMCCS) based on MEVDR can be constructed, which consists of two levels and can therefore be considered a bi-level model. After a thorough analysis, VGGMCCS incorporates two mixed integer programming (MIP) problems, allowing the use of commercial solvers for rapid and efficient problem solving. Finally, in order to provide further validation of the effectiveness of the VGGMCC system based on MEVDR, a comparison was made between the proposed method and the contrasting strategies.
The case study shows that, when compared to two contrasting strategies, the proposed VGGMCCS has been demonstrated to reduce the grid network loss by 12.17% compared to comparative strategy 1 and by 8.69% compared to comparative strategy 2 during peak electricity demand periods. And to reduce users′ average daily charging costs by 7.88% compared to comparative strategy 1, and to increase operators′ revenues by 17.63% compared to comparative strategy 2. Meanwhile, the load fluctuation amplitude of the transformer at the garage node has been significantly reduced. During peak electricity consumption periods, the power fluctuation of transformers under VGGMCCS decreased by 96.36% compared to comparative strategy 1 and by 82.59% compared to comparative strategy 2. Last but not least, VGGMCCS also has a high solution speed, ensuring decision accuracy while quickly responding to dispatching requests from lower-level garages, effectively reducing both the time and economic losses caused by rescheduling requests after EVs are integrated into the power grid. The results show that VGGMCCS can effectively reduce users′ costs, improve the economic benefits of the garage and enhance the operational efficiency of the power grid, while ensuring the long-term stable operation of the power system, thus achieving a win-win situation for users, garage operators and power grid companies.
In summary, this paper provides a thorough establishment and analysis of EVA′s MEVDR across a diverse range of geographical and temporal contexts. Furthermore, when compared to the contrasting strategies, the proposed VGGMCCS promises to enhance both the economic benefits and operational efficiency of the power system significantly.

With the increasing volatility and randomness of uncertain variables such as load and new energy, how to rationally dispatch multiple equipment such as cogeneration, gas boiler and energy storage equipment in integrated energy system (IES) according to the response characteristics of the existing potential response resources in IES to cope with the changes of uncertain variables has become the key to explore the differentiated response ability of IES multiple equipment. To solve the above problems, this paper proposes an economic optimal scheduling method for integrated energy systems, which takes into account variational mode decomposition (VMD) of uncertain variables and green certificate-carbon joint trading. By analyzing and mining the potential differential response ability of multiple devices in IES, the response ability of IES system to uncertainty variable volatility and randomness is improved.
Firstly, according to the commonness and difference of multiple types equipment operating response in time scale and regulatory amplitude in IES, uncertain variables such as wind power, electricity/heat/gas load are decomposed into low/medium/high frequency components with different amplitude and frequency through VMD to adapt to the response characteristics of multiple types equipment. Secondly, on the basis of considering the green certificate trading mechanism (GCT) and the carbon trading mechanism (CET), quantitatively calculate the carbon emission reduction of new energy compared with fossil energy in the process of online access, and offset part of the carbon emission through the carbon emission reduction caused by the green certificate, so that the carbon emission source can be reduced to a certain extent in the calculation of carbon emissions, which indirectly affects the carbon trading mechanism. Based on this, the green certificate-carbon joint trading mechanism is constructed. Finally, the medium and large-sized equipment with large inertia responds to the low-frequency component with low frequency and large amplitude, and the energy storage equipment that needs repeated charging and discharging responds to the medium/high-frequency component with small amplitude and positive/negative periodic oscillation, and then an economic optimisation scheduling model of the IES with the objective of minimising the comprehensive cost is established on the basis of the model, which is then passed layer by layer and iteratedly solved based on the order of VMD's low/medium/high-frequency components.
Through theoretical analysis and case simulation, the following conclusions are drawn: (1) The predicted power, electrical load, thermal load and gas load of wind power are decomposed into low, medium and high frequency components through VMD, which are suitable for the operation characteristics and response characteristics of energy storage equipment. The scheduling method proposed in this paper reduces the operation state of overcharge and overdischarge of energy storage equipment, which can effectively improve the utilization rate of energy storage equipment and further improve the system's ability to absorb new energy. (2) Compared with a single energy storage device, the hybrid energy storage system can better smooth and absorb wind power in different frequency bands according to the different frequency characteristics of wind power, so as to eliminate more wind abandonment and reduce the comprehensive cost of the system. (3) Compared with the single CET or GCT mechanism, the GCT-CET linkage mechanism can not only improve the absorption capacity of renewable energy in the integrated energy system, but also promote the further reduction of carbon emissions of the system.