Local Power Grid Research Articles

Microclimate Analysis of the High-Impact Weather for the Power Grid Operation in the Jibei Region of China

High-impact weather affects the safety and economic operation of power systems. In this study, to provide regional microclimate of high-impact weather for the local power grid system in the northern Heibei province (known as the Jibei region in China), ERA5-Land global reanalysis data during 1981–2020 with a 0.1° grid size (about 9 km) are adopted to analyze the climate statistics and changes of the disastrous weather that affects the power grids. The results show that there have been significant climate changes in the region, including a temperature increase of about 1 °C, evident humidity and precipitation reductions, for the Jibei region and the six sub-regions that concentrated with wind and solar energy development in the 40 years. Due to the differences in terrain, the climate changes differ significantly among the six renewable energy development regions. The main types of high-impact weather that affect the power grid in the region are heavy fog and icing events, followed by cold waves, snowstorms, and rainstorms. In general, with climate changes in the last several decades, the weather disasters in Jibei region have become more frequent. Since most high-impact weather events have a small scale, it is necessary to simulate the weather processes with high-resolution models to accurately quantify the characteristics of the weather processes that affect the power grid. Therefore, a refined regional meteorological model (with grid size of 2 km) based on four-dimensional data assimilation (JB-FDDA) is established for the Jibei region. With one year of model reanalysis data, we found that JB-FDDA can significantly improve the accuracy of the local meteorological fields, and properly depicted the details of severe weather that affect the power grid operation. This study provide an analytical approach for regional electricity meteorological disasters by using reanalysis data.

Analysis of Dynamic Capacity Increase Transmission Line Carrying Capacity under Temperature and Electromagnetic Field

This article mainly introduces that, as the proportion of renewable energy to total consumed energy increases further, with the large-scale development and construction of new energy, the local power grid may face the problem of conflicting consumption in the future, and the original transmission lines will no longer meet the power demand. For this reason, dynamic capacity increase technology is used to calculate the load capacity in real-time. Through simulation analysis under temperature and electromagnetic fields to ensure that the conductor has sufficient safety while increasing the load capacity, clear data results are obtained based on the analysis.

Short-term operation of cascade hydropower system sharing flexibility via high voltage direct current lines for multiple grids peak shaving

The escalating pressure for peak shaving presents a significant challenge for the power grid's operation, particularly with the rapid growth of renewable energies. Huge cascade hydropower stations (CHS) send power to the local power grid and multiple power grids via long-distance high voltage direct current (HVDC) transmission lines, how to share hydropower flexibility for multiple power grids in peak shaving while considering constraints of hydropower and HVDC lines challenges power dispatching management. This study proposed a multiple power grids peak shaving model of cascade hydropower stations with HVDC sharing flexibility for receiving power grids. Firstly, the objective of minimizing the peak-valley difference of multiple power grids is adopted. The model then takes into account the operation constraints of CHSs and HVDC tie-lines to share hydropower flexibility. Finally, the model is transformed into a Mixed-Integer Linear Programming problem through piecewise linearization. The case studies of practical examples in southwest China show that the proposed model reduces peak-valley differences by 23.3%, 46.9%, 99.1% and 19.6%, 34.3%, 99.5% for three receiving power grids in two typical days by sharing hydropower flexibility. Moreover, adjusting the HVDC daily power regulation times and electricity deviation tolerance helps coordinate power grids to improve their peak shaving performance.

Research on anti-islanding detection technology strategy

In recent years, the conditions and environment of China's economic development have undergone or are about to undergo many major changes. At the same time, China's electricity consumption ranks the first in the world with a huge volume and a considerable annual net increment. It is necessary to dialectically understand the profound impact of the new normal of economic development on the growth of China's electricity demand. Faced with the ever-increasing power demand, the power industry is still heavy to ensure steady supply, and the proportion of power consumption will also gradually increase. The central position of power in the energy field is gradually promoted, and the power security guarantee has gradually become one of the core elements of the new energy security strategy: in the actual operation of the power grid, there will be some unstable operation, and the local power grid accident can easily expand into a large-scale blackout. This will not only threaten the daily consumption of electricity, but also affect the national economy to a certain extent. The proposed distributed generation system solves this problem, but it also brings new problems. The appearance of island effect brings more harm to power grid operation. Aiming at the harm of island effect, this paper puts forward the detection technology strategy of related island effect.

A Multiphase Rail Launcher With Circular Geometry and Modular Design: Development, Construction, and First Experiments

Electromagnetic railguns allow to accelerate payloads to extremely high muzzle speeds ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;$</tex-math> </inline-formula> 2 km/s). Conventionally, the launcher design is based on two rails. The power supply consists of a capacitor bank and a pulse-forming network allowing unipolar operation. In this work, a different system setup is presented. The idea is to use multiphase alternating current instead of direct current to drive a rail launcher. The basic idea had been brought up in the past in connection with the use of compulsators as power supply. Here, it is suggested to connect the launcher to a (noncompensated) multiphase generator. An interesting but not obvious feature of such an approach is that a stationary acceleration force profile can be realized. However, the launcher becomes more complex as more than two rails are required and an appropriate power supply has to be developed. When considering this approach, an important finding is that if one aims at high speeds, several stages are required. It means that a modular or segmented setup is required. As the passage of the armature between the segments is expected to be a critical point, the idea came up to build a three-phase circular geometry, meaning that the armature leaves at the “muzzle” and re-enters at the “breech” of the launcher. This also allows using an electric motor for a preacceleration in order to minimize sliding contact problems during start. As power supply served a redesigned 100-kW high-current transformer, which can be connected directly to the local power grid. Experimental data including electrical parameters (e.g., an armature current of 20 kA) are presented and discussed. For the first time, it can be experimentally shown that stationary acceleration profiles can be realized, in principle.

The sustainability of green hydrogen: An uncertain proposition

Green hydrogen is increasingly considered a vital element for the long-term decarbonization of the global energy system. For regions with scarce land resources, this means importing significant volumes of green hydrogen from regions with abundance of renewable energy. In producing countries, this raises significant sustainability questions related to production and export. To assess these sustainability-related opportunities and challenges, the authors first present a review of renewable energy deployment in the electricity sector, and then extend it to the foreseeable opportunities and risks of green hydrogen production in exporting countries. The paper finds that questions of freshwater and land availability are critical from an environmental and a socio-economic point of view, and that the development of international standards for the governance of hydrogen-related projects will be crucial. These should also address potential conflicts between the deployment of renewable energy for the decarbonization of local power grids, and the export of green hydrogen.

Hierarchical Software-Defined Control Architecture With MPC-Based Power Module to Interface Renewable Sources and Motor Drives

A hierarchical control architecture is designed with model predictive control (MPC)-based power module for generalized renewable applications including single/three-phase grid, solar, battery, electric motor, etc. The hierarchical control architecture is composed of three layers: (1) Central control layer for mode recognition of different types of interfaced load/source, reconstruction of power converter topologies, high level current/voltage/power control, generating references for local power module control and grid services for utility support; (2) Local module control layer for implementing MPC algorithm to track references from central controller with improved dynamic performance, stabilizing common-mode voltage, collecting ADC samplings and generate PWM signals for local power switches; (3) Application layer for the interface with different types of renewable loads/sources including single/three-phase grid, solar, battery, electric motor and so on. The merits of the designed control architecture include: (1) the reconfigurability to be suitable for different types of applications; (2) all non-isolated topologies with common-mode noise attenuation capability for renewable energy interfaces; (3) improved dynamic performance by local MPC power module; (4) high accuracy and robustness of the multi-layer MPC-based control without being influenced by the parametric modeling error from various interfaced applications; (5) grid services for abnormal condition utility support. The experimental results verified the proposed hierarchical control architecture.

Organization of the rural electrification process in Ukraine during the Post-war period (second half of the 1940s – first half of the 1960s)

The article is devoted to the analysis of the characteristic features and peculiarities of the organization and implementation of rural electrification in Ukraine during the first post-war twenty years (1945-1965). The author considered the post-war Soviet government regulations on the development of rural electrification. The authorities envisioned the use of electricity primarily in production processes, betting on the use of renewable energy sources and/or local, cheap fuels. This process took place under the conditions of the administrative-command system, it was authorized and directed centrally, in a directive way at the highest state level. Three periods of implementation of this process are defined: - the second half of the 1940s – the beginning of post-war electrification in combination with the reconstruction of the most necessary production and infrastructure facilities; - the 1950s – active construction of autonomous power plants and creation of local power grids in rural areas; - the first half of the 1960s – complete electrification of villages with centralized connection to a single state power grid. The supply of equipment, installation, repair, supervision, and maintenance of rural power plants was carried out by the regional offices of the Republican Test (later the Main Directorate) of Rural Electrification ("Ukrsilelektro"/"Ukrgolovsilelektro"). However, its effectiveness remained quite low, and the quality of the work performed caused numerous complaints. Electrification cost considerable money, took place unevenly, and depended on many local conditions (the presence of nearby rivers, fuel deposits, industrial facilities, transport connections, etc.). The research is based on materials from the funds of the Central State Archives of Supreme Bodies of Power and Government of Ukraine and the Central State Archives of Public Associations and Ukrainians.

Application of Low Voltage Treatment Device Based on Electrochemical Energy Storage

With the rapid development of social economy, the power supply capacity of the existing power grid has been far from the increasing load demand, especially the summer (winter) peak period. The problems such as heavy overload of power grid equipment and low voltage of line are extremely prominent and seriously affects the safe and stable operation of the power grid. This problem is more serious in the rural power grid. In order to increase the progress, shorten the construction cost of upgrading and transformation of the traditional power grid, a technical scheme is proposed in this paper by using electrochemical energy storage technology to solve the overload and low voltage problems of local power grid equipment, and obvious results have been achieved through pilot project.

Algorithm Research on Minimum Inertia Demand of New Energy Sending Grid Generating Units Considering System Transient Stability

After a lot of conventional power-generating units at the local end-to-end power grid have been replaced, the new energy-generating units do not participate in the active response of the system through the grid connection of the converter, which reduces transient stability due to the reduction of the inertia of the local grid. Firstly, based on the principle of transient energy, the mechanism of the moment of inertia of the local power grid is established by affecting the fault removal angle, and then the acceleration energy during the fault and the deceleration energy after the fault is removed is revealed. Based on the equal area rule, the relationship between the inertia and the transient stability limit, and the static stability limit before and after the fault is deduced, and the minimum engineering moment of inertia required to ensure the transient stability of the system at a certain output power level at the transmitting-end grid is given. The algorithm and simulation example analysis verify the effectiveness and practicability of the proposed method.

A new approach for calculating the average frequency of power system based on the identification of regional inertia center nodes

The grid structure of the modern power system is complex and the space span is large. When the power system is disturbed to generate unbalanced power, the transient distribution process among the various synchronous units leads to the spatiotemporal distribution characteristics of the frequency response of the system. By measuring the generator Frequency and Inertia, the inertia center frequency can be calculated. Based on the two-generator system, the relationship between generator frequency and bus frequency is analyzed. A method for selecting the frequency inertia center node of the local power grid in the power system is proposed, and the inertia center frequency of the system is estimated based on the measured frequency at this point. Taking 10 machines and 39 nodes as an example, the simulation calculation is carried out to verify the effectiveness of the proposed method.

Accurate prediction of electricity consumption using a hybrid CNN-LSTM model based on multivariable data.

The stress placed on global power supply systems by the growing demand for electricity has been steadily increasing in recent years. Thus, accurate forecasting of energy demand and consumption is essential to maintain the lifestyle and economic standards of nations sustainably. However, multiple factors, including climate change, affect the energy demands of local, national, and global power grids. Therefore, effective analysis of multivariable data is required for the accurate estimation of energy demand and consumption. In this context, some studies have suggested that LSTM and CNN models can be used to model electricity demand accurately. However, existing works have utilized training based on either electricity loads and weather observations or national metrics e.g., gross domestic product, imports, and exports. This binary segregation has degraded forecasting performance. To resolve this shortcoming, we propose a CNN-LSTM model based on a multivariable augmentation approach. Based on previous studies, we adopt 1D convolution and pooling to extract undiscovered features from temporal sequences. LSTM outperforms RNN on vanishing gradient problems while retaining its benefits regarding time-series variables. The proposed model exhibits near-perfect forecasting of electricity consumption, outperforming existing models. Further, state-level analysis and training are performed, demonstrating the utility of the proposed methodology in forecasting regional energy consumption. The proposed model outperforms other models in most areas.

A New Decentralized Robust Secondary Control for Smart Islanded Microgrids.

Dealing with the islanded operation of a microgrid (MG), the micro sources must cooperate autonomously to regulate the voltage and frequency of the local power grid. Droop controller-based primary control is a method typically used to self-regulate voltage and frequency. The first problem of the droop method is that in a steady state, the microgrid's frequency and voltage deviate from their nominal values. The second concerns the power-sharing issue related to mismatched power line impedances between Distribution Generators (DGs) and MGs. A Secondary Control Unit (SCU) must be used as a high-level controller for droop-based primary control to address the first problem. This paper proposed a decentralized SCU scheme to deal with this issue using optimized PI controllers based on a Genetic Algorithm (GA) and Artificial Neural Networks (ANNs). The GA provides the appropriate adjustment parameters for all adopted PI controllers in the primary control-based voltage and current control loops and SCU-based voltage and frequency loops. ANNs are additionally activated in SCUs to provide precise online control parameter modification. In the proposed control structure, a virtual impedance method is adopted in the primary control scheme to address the power-sharing problem of parallel DGs. Further, in this paper, one of the main objectives includes electricity transmission over long distances using Low-Voltage DC Transmission (LVDCT) systems to reduce power losses and eradicate reactive power problems. Voltage Source Inverters (VSIs) are adopted to convert the DC electrical energy into AC near the consumer loads. The simulation results illustrated the feasibility of the proposed solutions in restoring voltage and frequency deviations, reducing line losses, as well as achieving active and reactive power sharing among the DGs connected to the MG.

Building a Sustainable Energy Community: Design and Integrate Variable Renewable Energy Systems for Rural Communities

This study proposes a decentralized hybrid energy system consisting of solar photovoltaics (PV) and wind turbines (WT) connected with the local power grid for a small Najran, Saudi Arabia community. The goal is to provide the selected community with sustainable energy to cover a partial load of the residential buildings and the power requirements for irrigation. For this, a dynamic model was constructed to estimate the hourly energy demand for residential buildings consisting of 20 apartments with a total floor area of 4640 m2, and the energy requirements for irrigation to supply a farm of 10,000 m2 with water. Subsequently, HOMER software was used to optimize the proposed hybrid energy system. Even considering the hourly fluctuations of renewable energies, the artificial neural network (ANN) successfully estimated PV and wind energy. Based on the mathematical calculations, the final R-square values were 0.928 and 0.993 for PV and wind energy, respectively. According to the findings, the cost of energy (COE) for the optimized hybrid energy system is $0.1053/kWh with a renewable energy penetration of 65%. In addition, the proposed system will save 233 tons of greenhouse gases annually.

A multi-objective peak regulation transaction optimization and benefits coordination model for multi-sources coupling system considering flexible load response

Based on the intermittent output and inverse peak regulation characteristics of wind power, a multisource peak regulation transaction optimization model that considers the feasibility of combining thermal power, energy storage, and demand response for both power generation and consumption is proposed in this paper. First, a multisource peak regulation transaction cost model is established by considering flexible load participation in peak regulation and price- and incentive-based demand responses. Subsequently, with the objective of minimizing both the peak regulation cost and wind curtailment rate, a reduced half gradient membership function is selected to transform the multiobjective model. Finally, by analyzing the roles of the different subjects in multisource peak regulation transactions, a compensation mechanism based on the Shapley method is designed, and a local power grid in northeast China is chosen as the simulation object. The results show the following: (1) When the thermal power generators (TPGs) transit from regular peak regulation to deep peak regulation, the wind curtailment rate decreases by 5.10%, and the peak regulation cost increases by $ 0.793 × 106. This indicates that the peak regulation cost of the TPGs and the income of the on-grid wind power need to be balanced. (2) When the energy storage and the demand response are combined for peak regulation, both the peak load regulation cost and wind curtailment rate reach the optimal values, decreasing by $ 0.642 × 106 and 5.72%, respectively, showing cooperative optimization. However, the TPGs require a higher regulation cost, whereas the other subjects achieve incremental benefits. (3) The compensation mechanism assists each subject in obtaining incremental benefits depending on the contribution rate. With the strengthening of the peak regulation of the TPGs, more energy storage and demand response output are introduced to meet the urgent peak regulation requirement, which leads to increased regulation revenue and optimal dispatching. In summary, the proposed transaction and compensation mechanism of multisource peak regulation can be used to balance the peak regulation ability and contributions of different subjects and establish the optimal peak regulation scheme.

A novel ensembling of deep learning based intrusion detection system and scroll chaotic countermeasures for electric vehicle charging system

The usage of Electric vehicle (EVs) has been exponentially growing due to its focus on eco-friendly means of transport, distributed charging platform and user dictated supporting infrastructures. The EVs are charged by the charging stations which equipped with Electric Vehicle Supply Equipment (EVSE) that contains Internet enabled computers. These systems are considered to be more important for controlling the function such as charging electric vehicles, authorization and smart connection to the local power grid using different wireless technologies such as green WIFI, Bluetooth and even 5 G. The cyber-attacks such as DoS and DDoS attacks can violate integrity, confidentiality and availability of the EVSE resources. Hence the intelligent Intrusion Detection System (IDS) is required to ensure the system for the robust and trustworthy deployment of EVSE resources. To meet the above challenge, this paper proposes new composite and intelligent system which contains the deep learning based IDS and high random chaotic generators to safeguard the data against the different cyber-attacks. The proposed IDS has been modelled based on Gated Recurrent Units (GRU) and counter measures are performed by adopting the Enhanced Chaotic Scroll attractor keys (ECSA). The contribution of this research paper is as follows: Novel Dataset Preparation for EVSE under different attack scenarios, Implementation of high accurate multi-objective accurate GRU based IDSs, Design of Enhanced Chaotic Countermeasure Encryption Schemes for the counterfeiting the attacks in Internet Enabled EVSE system. The extensive experimentation has been carried out into two important phases. In first phase algorithm centric metrics such as prediction accuracy, time of detection, whereas in second phase key centric metrics such as Number of Changing Pixel Rate (NPCR), Unified Averaged Changed Intensity (UACI), Key sensitivity and entropy are calculated and compared with the other existing methodologies. Results demonstrates that the proposed ensemble system has outperformed than the other methodologies and proves its strong place in designing the more secured Internet Enabled EVSE systems.

A low-carbon peak-load regulation trading strategy for large-scale wind power integration using information gap decision theory

It is critical for power system to uphold operation security while considering the cooperation of thermal power and new flexible resources, such as energy storage and demand response (DR). This paper investigates the integration of carbon emission trading with peak-load regulation trading to analyze the effects of carbon change generated using thermal power, energy storage, and demand response, and builds a deterministic multisource low-carbon peak-load regulation trading optimization model. To describe wind power uncertainty, we apply information gap decision theory (IGDT) to quantify the information gap between the predicted and actual data of wind power; subsequently, we construct a multisource low-carbon peak-load regulation trading optimization model based on IGDT considering the uncertainty. Finally, a local power grid in Northwest China is considered as a case study, and we establish regular, low-carbon, stochastic and comprehensive four peak-load regulation scenarios to analyze the impact of carbon emissions trading, energy storage, and DR involved in wind power peak-load regulation trading. The results show the following. (1) The individual application of the energy storage system (ESS) and DR can reduce peak-load regulation cost by 4.64% and 7.68%, respectively, whereas a 8.38% reduction is achieved when they are applied together. (2) When considering the uncertainty of wind power, the grid connected power of wind power is reduced by 2.15% and the total peak shaving cost is increased by 10%. With the increase in uncertainty, the cost of peak shaving trading scheme is always lower than the expected value, indicating that the IGDT method is effective. (3) When the price of the carbon emission trading ranges from 85–95 CN¥/t, the peak-load regulation cost of thermal power units are compensated; moreover, the peak-load regulation cost of wind power and allowable uncertainty reach optimum values when the acceptable price is less than 80 CN¥/t in the worst scenario. In summary, the ESS and DR can enhance the flexibility of the system for peak-load regulation, thus increasing wind power grid connection, and carbon emissions trading can improve the net economy of peak-load regulation of thermal power units. The IGDT method can describe the uncertainty risk of wind power output and establish a peak-load regulation trading scheme that satisfies the expectations of decision makers with different risk attitudes. The peak-load regulation trading scheme must carefully consider the carbon emission trading price: if the carbon emission trading price is excessively high, it will result in a retaliatory grid connection of wind power to compensate for the carbon trading costs, and the system cost will increase rapidly.

An inter-city energy migration framework for regional energy balance through daily commuting fuel-cell vehicles

Spatiotemporal energy interaction and sharing are promising solutions to penetrate renewable energy, enhance grid power stability, and improve regional energy flexibility. However, the current literature is restrained in a small-scale neighborhood level, without considering inter-city energy migration through spatiotemporal complementarity between renewable-abundant regions (like suburb or countryside areas) and demand-shortage regions (like city centers). In this study, the energy interaction boundary is extended from a neighborhood scale to an inter-city scale, to maximize the renewable energy penetration, demand coverage, and reduce regional energy imbalance. This study firstly proposes a holistic framework on inter-city transportation-based energy migration, consisting of a residential community with rooftop photovoltaic systems and electrical batteries, an office building, hydrogen vehicles (HVs), a hydrogen (H2) station, and local power grids, for the energy transmission between building groups in spatially different regions through the daily commuting of HVs. Optimal grid-regulation strategies are thereafter proposed and adopted to stabilize the grid power and reduce energy costs. Parametric analysis on energy trading strategies and prices has been conducted, to improve the participation motivations of different stakeholders. Results indicate that, compared to the reference case with isolated buildings and vehicles, the transportation-based energy migration framework covers 23.2 % of the office energy demand and elevates the community’s renewable self-use ratio from 72.7 % to 98.6 %. Meanwhile, the maximum grid-export power in the renewable-abundant region (suburb residential community) and the annual grid-import power in the demand-shortage region (city-center office) are reduced by up to 86.9 % (from 155.7 to 20.4 kW) and 29.4 % (from 49.0 to 34.6 kW), respectively. Moreover, even considering the fuel cell degradation cost of HVs, the transportation-based energy migration framework reduces the operating costs of the office building and HVs (the H2 cost and the fuel cell degradation cost) by 16.4 % (from $52791.3 to $44154.7) and 1.7 % (from $27172.5 to $26707.4), respectively. Afterward, compared to the reference case, the peak-shaving and load-shaping grid-regulation strategies can decrease the peak grid-export power of the community by about 71.6 % (from 155.7 to 44.2 kW), and the maximum grid-import power of the office by 23.7 % (from 49.0 to 37.4 kW), respectively. Furthermore, the transportation-based energy migration framework is economically feasible, only when the renewable export price for H2 production is 0.07 $/kWh, the onsite-renewable-generated H2 lower than 6.5 $/kg for the HV owners, and the vehicle-to-building electricity lower than 0.3 $/kWh for the office building. This study provides a novel inter-city energy migration framework with hydrogen networks to enhance district energy sharing, improve regional energy balance and reduce carbon emission, together with frontier guidelines on energy trading prices to promote participation motivations from different stakeholders.

Complete operational voltage assessment of Shandong pilot offshore wind project

AbstractThis article presents a thorough methodology for the voltage assessment of pilot offshore wind project in Shandong province, China. The results presented in this paper can be considered as the milestone of the offshore wind research in Shandong Province since there is still no grid codes for offshore wind power plant grid connection in the local electrical power grid. It mainly consists of three parts. In the first part, a detailed model of the offshore wind farm created in the DIgSILENT PowerFacotry simulation platform is presented, including wind turbines, power converters, transformers, submarine cables and relevant control schemes. In the second part, nonlinear time‐domain simulations were performed to analyze the wind farm's active power, reactive power, and voltage conditions under different wind scenarios. Based on the simulations results, a dynamic reactive power compensation system was proposed, and the consequence of the reactive power compensation was also demonstrated using nonlinear time‐domain simulations.

Importance Assessment of Communication Equipment in Cyber-Physical Coupled Distribution Networks Based on Dynamic Node Failure Mechanism

Electrical power communication networks undertake complicated power services. They interact with physical power grids all the time, which will result in a high risk to power grids when their electric power communication network is attacked. Therefore, to improve the reliability of power systems, it is of great significance to identify the key links of communication networks. Existing research studies focus more on the risk of power communication services undertaken by communication links, which ignores the frequent interaction between power grids and communications networks. In this paper, from a multi-layer network perspective, an assessment method of communication equipment is proposed in view of the operation characteristics of nodes in different systems as well as the dynamic fault propagation between homogeneous communication nodes. Firstly, we build a model of cyber-physical power interdependent network. Then, for communication nodes, a dynamic model is adopted for cascading failure among the nodes based on the load-capacity model. Afterward, we define an index to evaluate the node importance considering characteristics of the operation of both communication networks and power grids. Finally, a local power grid is taken as an example for verification by comparing the effects of different indexes. The simulation results demonstrate the validity of the evaluation method proposed.