China Power Grid Research Articles

Multi-time scale stochastic production simulation under VHVDC long-term contract trading electricity quantity constraint

A two-layer multi-time scale stochastic production simulation framework is constructed to account for the long-term contract electricity quantity of ultra-high voltage direct current (UHVDC) transmission. On the upper layer, based on the characteristics of load demand and renewable energy output extracted from the historical operating data, monthly and daily production simulation models are carried out considering the seasonal characteristics of hydropower during a high-water period and low-water period to optimize the distribution of contract electric quantity sending through UHVDC transmission in the target year or month. According to the DC transmission electric quantity optimized by the daily production simulation in the upper layer, together with the forecast scenario, the lower layer of the framework provides the optimization of day-ahead scheduling and intra-day rolling dispatch in the implementation process. The day-ahead dispatch optimization makes full use of the adjustment capability of transmission and optimizes the DC transmission electric quantity correction. Its compensation is based on the result of the daily production simulation, then the correction will be returned to the upper layer to restart the optimization of the remaining UHVDC contract electric quantity of the subsequent period and its distribution plan. Combined with the day-ahead DC transmission plan, the intra-day rolling optimization is carried out to adjust the output of the unit using more accurate forecasting scenarios. The distributionally robust optimization model is used in the lower layer to convert an uncertain problem into a deterministic quadratically constrained quadratic programming (QCQP) problem according to the form of an uncertain distribution set. Then the QCQP problem is further converted into a linear programming (LP) problem by using the reformulation linearization technique (RLT). A test system with the energy composition and distribution referring to a real provincial power grid in northwest China is established for verification. The results show that the proposed method can effectively improve the economics of system operation and the accommodation of renewable energy based on ensuring security.

Photovoltaic project investment based on the real options method: An analysis of the East China power grid region

Photovoltaic project investment based on the real options method: An analysis of the East China power grid region

Data-Driven Dynamic Stability Assessment in Large-Scale Power Grid Based on Deep Transfer Learning

For data-driven dynamic stability assessment (DSA) in modern power grids, DSA models generally have to be learned from scratch when faced with new grids, resulting in high offline computational costs. To tackle this undesirable yet often overlooked problem, this work develops a light-weight framework for DSA-oriented stability knowledge transfer from off-the-shelf test systems to practical power grids. A scale-free system feature learner is proposed to characterize system-wide features of various systems in a unified manner. Given a real-world power grid for DSA, selective stability knowledge transfer is intelligently carried out by comparing system similarities between it and the available test systems. Afterward, DSA model fine-tuning is performed to make the transferred knowledge adapt well to practical DSA contexts. Numerical test results on a realistic system, i.e., the provincial GD Power Grid in China, verify the effectiveness of the proposed framework.

Research on Construction Technology of Deep Foundation Pit of High Voltage Transmission Line in Plateau Area

With the further expansion of China power grid, it is the current and future trend of power system development to set up high-voltage or even ultra-high-voltage transmission lines. Because the construction environment of high-voltage transmission lines is very complex and changeable, how to ensure the construction quality and progress of transmission lines according to the construction drawings provided by the design unit is the key to the construction of transmission lines. The quality level of deep foundation pit excavation is a representative factor that profoundly affects the construction quality level of high-voltage transmission line projects in plateau areas. Only by managing the construction quality of all sub-projects in the power system can the stability of power operation be effectively guaranteed. This paper expounds the key points of deep foundation pit excavation construction technology, in order to analyze the deep foundation construction technology of high-voltage transmission lines in plateau area, and provide theoretical support for the deep foundation pit construction of high-voltage transmission lines in plateau area.

A Method for Evaluating the Impact of Controllers and Wind Turbine Generators on Low-Frequency Oscillation

Based on the celebrated Generalized Nyquist Criterion, this paper presents a new frequency-domain method to analyze the impact of governor-turbine systems (GTSs), power system stabilizers (PSSs) and wind turbine generators (WTGs) on small disturbance stability in power systems. Compared with other common analysis method, the new method can avoid the calculations of eigenvalues, eigenvectors and residues, and the impact of multiple controllers or WTGs can be obtained using simple matrix operations. In addition, the method is intuitive for users since the stability analysis results can be displayed in the complex plane directly. The new method indicates that the impact of controllers and WTGs on power system is determined by the phase of certain elements in the transfer function matrices of controllers, WTGs and synchronous grid. Based on the information provided by the afore-mentioned transfer function matrices, the parameters of controllers can be optimized properly. The proposed method has been tested using the data of a four-machine two-area system and a regional power grid in China. The results demonstrate that the effect of controllers and WTGs can be conveniently identified, and the effectiveness of parameter tuning for controllers is verified.

Construction of an evaluation index system for power market considering economic-environmental multi-objectives

At present, China's electricity market has been initially built, direct trading of electricity continues to increase, and the mode of "multiple purchase and multiple sale" has emerged in the market, which enables the electricity market to compete effectively and make the optimal allocation of resources. Therefore, it is necessary to evaluate the operation of the electricity market. The article firstly studied the indicators of power market operation from three aspects: economic value, green value and security value; secondly, established a three-level evaluation index system of power system; on this basis, proposed a comprehensive evaluation model of power market based on fuzzy comprehensive evaluation. It provides a reference basis for the evaluation of China's power grid operation and is of great significance to promote the healthy development of China's power market.

Analysis of carbon emission status in Gansu Province and suggestions on electric power transformation under the goal of "dual carbon"

As an important transmission corridor of "West-east power transmission" and the central hub of the power grid in northwest China and has obvious resource advantages in the power and location of the country. And it will accelerate the construction of a new power system to adapt to the gradual increase in the proportion of new energy, from the traditional energy consumption structure dominated by coal power to the new energy consumption structure, new energy will enter the stage of high-quality leapfrog development, in order to achieve the "double carbon" goal as soon as possible. Based on the analysis of carbon emissions in Gansu province, especially in the power industry, this paper demonstrates the overall situation of carbon emissions in Gansu province, and points out the status of new energy in Gansu province combined with the latest energy resources and the existing regional development situation, and puts forward relevant suggestions to adapt to the development of new energy in Gansu province under the "dual carbon" goal.

Analysis of influence of energy storage system parameters on HVDC commutation failure overvoltage

Overvoltage is a common fault in high voltage direct current (HVDC) transmission systems, which directly affects the safe and stable operation of the system. Energy storage system has been widely used in power system because of its fast response speed, high precision and bidirectional energy transmission. As a variable parameter, the low voltage traverse active power coefficient directly affects the overvoltage of commutation failure in HVDC system. In this paper, the influence of transient characteristics and energy storage parameters on commutation failure overvoltage of energy storage system connected to HVDC is analyzed. Based on PSASP simulation, combined with the actual characteristic setting parameters of a power grid in northwest China, the positive correlation between energy storage low-pass active power and transient overvoltage of HVDC system commutating failure is verified by dynamic trajectory sensitivity analysis, and the optimization space of HVDC energy storage system is expanded.

Graph Convolutional Network-Based Interpretable Machine Learning Scheme in Smart Grids

Smart grid is a typical application of industrial cyber-physical systems (ICPS) in the electric power industry. Due to the exposure to different kinds of uncertainties and unpredictable faults, how to reliably assess the short-term voltage stability (SVS) of smart grids to prevent the occurrence of large-scale blackouts is still of primary concern. To tackle this challenging problem, this article develops a novel machine learning scheme to achieve accurate and interpretable online SVS assessment in two steps. First, it utilizes time-series shapelet transform to extract key dynamics and convert the postfault time series into flat features. Second, it designs a graph convolutional network (GCN) to incorporate these features with topology information for SVS assessment. The GCN explores the spatial-temporal dynamics of power system via graph convolution and introduces a system layer to derive the final assessment result. Compared with conventional methods, this novel scheme makes full use of the spatial-temporal information in SVS dynamics, resulting in higher assessment accuracy and stronger adaptability. Besides, it is capable of discovering certain valuable underlying rules and patterns related to SVS. Test results on the IEEE 39-bus system and real-world Guangdong Power Grid in South China verify the effectiveness of the proposed scheme. Note to Practitioners—To achieve accurate and interpretable online short-term voltage stability (SVS) assessment in the challenging environment of smart grids, this article develops a novel machine learning scheme with full consideration of the spatial-temporal information in SVS dynamics. First, it utilizes the time series shapelet transform to convert the postfault time series into flat features. Second, it designs a graph convolutional network (GCN) to incorporate these features with topology information. The full consideration of spatial-temporal information in SVS dynamics can improve the assessment accuracy, and the integration of topology in the scheme can promote its adaptability to topology changes. Apart from the decent performances under changeable environments, the proposed scheme can provide certain valuable underlying rules and patterns related to SVS. Therefore, not only the proposed scheme for SVS assessment can work well in the practical challenging environment of smart grids, but also it helps the dispatchers in smart grids better understand and trust the proposed SVS assessment scheme.

Geomagnetically induced current uncertainty quantification based on the earth conductivity models constructed by the Kriging method

• Proposed and verified the superiority of Kriging method in constructing earth conductivity model. • Illustrate the necessity of uncertainty analysis for GIC. • Obtained the sensitivity of GIC input parameters(transformer parameters, transmission line parameters and ground resistance parameters) in 1000kV UHV Northern China power grid. With the expansion of power grid, the hazard of geomagnetically induced current (GIC) has attracted more attention. Due to the small number of Magnetotelluric detection points, the earth conductivity model based on limited data cannot be adapted to the GIC calculation of large-scale power grids. In addition, it is necessary to consider the effect of simultaneous changes in multiple input variables on GIC calculation results. Therefore, this paper presents a method for modeling the conductivity of the earth which is used in the case of less data, and uses the model to quantify the uncertainty. Based on the existing Magnetotelluric data in Northern China, the conductivity model within the power grid region is established using the Kriging method. The uncertainty quantification model of the GIC is constructed based on the Polynomial Chaos Expansions(PCE) method. The uncertainty quantification analysis is carried out for the 1000 kV ultra-high voltage Northern China Power Grid. The statistical information of the GIC and its sensitivity to each input parameter are obtained.

A novel partitioning method for the power grid restoration considering the support of multiple LCC-HVDC systems

The restoration of the modern alternating current-direct current (AC–DC) hybrid power grid after a blackout is difficult and complex. By using the partitioning restoration strategy and the support of high voltage direct current (HVDC) system, the restoration speed of the blackout power grid can be greatly accelerated. Aiming at this problem, this paper proposes a partitioning method for the power grid restoration with multiple line commutated converter-based HVDC (LCC-HVDC) systems. Firstly, by introducing the system strength indices to quantify the interaction between AC and LCC-HVDC systems in the restoration process, a partitioning model considering multiple LCC-HVDCs is proposed. Wherein, the transmission power is optimized to make full use of LCC-HVDCs’ support capability. Then, by combining the system strength characteristic and community structure characteristic of the power grid, a partitioning method based on an improved Girvan Newman (GN) algorithm is proposed. Finally, the results are studied based on a modified IEEE 39-bus system and a realistic partial power grid of southwest China. Compared with two typical partitioning methods for the AC power grid restoration, the results show that the proposed method can effectively use the DC support power and speed up the restoration progress.

Study on Quantitative Evaluation Index of Power System Frequency Response Capability

Frequency stability is an important factor for the safety and stability of the power system operation. In a traditional power system, the operation stability is ensured by the inertia response, primary frequency modulation, and secondary frequency modulation. In recent years, in order to achieve the goal of carbon neutralization and carbon peaking, China has made great efforts in new energy development. With large-scale new energy connected to the power grid, the proportion of traditional conventional synchronous units has gradually declined. At the same time, a large number of power electronic devices have been used in the power grid, which led to the capability decline of the inertia response and primary frequency modulation. For example, the East China Power Grid has experienced a sharp frequency drop in such an environment. In order to solve the above problems, the operation principle and control mode of various new energy resources are analyzed in this paper. Moreover, the process and principle of power grid frequency response are studied and the evaluation index of frequency response capability is proposed. The research results can quantitatively evaluate the system inertia response and primary frequency modulation level and provides a judgment tool for dispatching operators and system planners.

A Review on Fire Research of Electric Power Grids of China: State-Of-The-Art and New Insights

A Review on Fire Research of Electric Power Grids of China: State-Of-The-Art and New Insights

The Fuel Cycle Carbon Reduction Effects of New Energy Vehicles: Empirical Evidence Based on Regional Data in China

With ever-growing energy demands and increasing greenhouse gas (GHG) emissions, carbon emission reduction has attracted worldwide attention. This article establishes a bottom-up method using regional data from 2010 to 2020 to quantify the carbon reduction effects of new energy vehicles (NEVs) in the fuel cycle. From this, a generalized Bass model with outstanding performance was created (with a goodness-of-fit of 99.7%) to forecast CO2 emission reduction potential in 2030 and 2050. The results are as follows: (1) there are regional differences in the fuel cycle carbon reduction effects of NEVs in all six regions, with the Central China power grid having the strongest ability to reduce emissions, while the Northeast and Northwest grids have relatively low carbon reduction effects. (2) Battery electric vehicles (BEVs) have the strongest CO2 emission reduction effect, while fuel cell vehicles (FCVs) have the most potential. (3) Under the baseline scenario, the carbon reduction of NEVs will be 2992 million tons in 2030 and reach 11,559 million tons in 2050, which is far from carbon neutrality. Further, policy implications, including the tailoring of policies to specific regions and upgrading the energy mix, are proposed to reduce further carbon emissions.

An Efficient Power System Planning Model Considering Year-Round Hourly Operation Simulation

High renewable energy penetration increases the electricity seasonal imbalance in the long-term timescale. Power system planning needs to consider the optimal configuration of various flexibility resources and electricity balance in different timescales. The coupling of multiple timescales largely increases the computation complexity of the power system planning problem. Thus, this paper presents an efficient source-grid-storage co-planning model which incorporates a year-round hourly operation simulation. To improve the computation efficiency of the planning model, from the temporal scale, a self-adaptive compact panorama time series (CPTS) model is applied, which greatly reduces the number of variables related to short-term decisions. From the spatial scale, a network-constrained relaxed clustered unit commitment (NC-RCUC) model is introduced, which significantly reduces the number of variables related to unit commitment decisions. Case studies on the modified Garver’s 6-node system and HRP-38 system prove the validation and efficiency of the proposed model (“HRP” stands for high renewable penetration). The studies on the China power grid in 2035 demonstrate the future planning results of generation, transmission and storage in China power systems based on the proposed model.

A Modified Multiparameter Linear Programming Method for Efficient Power System Reliability Assessment

Power systems face adequacy risks because of the high integration of renewable energy. It is urgent to develop efficient methods for power system operational reliability assessment. Conventional power system reliability assessment methods cannot achieve real-time assessment of system risk because of the high computational complexity and long calculation time. The high computational complexity is mainly caused by a large number of optimal power flow (OPF) calculations. To reduce the computational complexity, this paper transfers the optimal power flow model as a multiparameter linear programming model. Then, the optimal power flow can be obtained by linear calculations. Furthermore, this paper proposes a state reduction method considering the importance index of transmission lines for further improving the calculation efficiency. Case studies are carried out on IEEE standard systems and a provincial power grid in China. Compared with the conventional reliability assessment method, the reliability assessment efficiency of the proposed method increases by 10–40 times, and the assessment error is less than 1%.

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.

Who shapes the embodied carbon dioxide emissions of interconnected power grids in China? A seasonal perspective

With the rapid development of interregional power transmission, the redistribution of fossil and renewable energy resources has changed sharply, and its complexity poses a challenge to the evaluation of power carbon emission responsibility. This study constructs an interprovincial power transmission framework to measure the seasonal carbon emissions embodied in regional electricity consumption over the period of 2008–2015 based on quarterly data. Then, a structural decomposition approach was developed to identify the influential factors of carbon emissions embodied in provincial electricity consumption from a seasonal perspective. The results show that the assessment for embodied emissions of power consumption based on different levels of data may vary by as much as 20%, and the carbon emissions and carbon intensity of power consumption exhibit significant seasonal characteristics. Furthermore, it is revealed that the economic scale in the fourth quarter makes the most significant contribution to the emissions increment, especially in underdeveloped provinces, while the change in energy efficiency of power generation reduces more carbon emissions in the first and second quarters. In addition, the impact of the power transmission scale is more significant in the third and fourth quarters, and it has been close to or even more than the impact of traditional factors in some quarters. Finally, the impact of economic scale, power generation energy intensity, power generation mix and electricity utilization efficiency on the emissions of regional power grids shows a relatively stable increasing trend, but this trend of directional stability is not reflected in the effect of the power transmission structure and transmission scale. This study contributes to the identification of the impact of the power transmission structure and transmission scale. Moreover, this study highlights the importance of considering seasonal characteristics when estimating the carbon emissions of power consumption and formulating specific emission reduction policies. Additionally, it provides a more accurate evaluation of carbon emissions and proposes several prominent recommendations for policy makers.

Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism

As one of the power auxiliary services, peak shaving is the key problem to be solved in the power grid. With the rapid development of DGs, the traditional peak shaving scheduling method for centralized adjustable energy is no longer applicable. Thus, this paper proposes two-layer optimization methods of allocating the peak shaving task for DGs. Layer 1 mainly proposes four evaluation indexes and the peak shaving priority sequence can be obtained with modified TOPSIS, then the DG cluster’s task is allocated to the corresponding DGs. On the basis of dynamic evaluation and the self-renewal mechanism, layer 2 proposes a peak shaving optimization model with dynamic constraints which assigns peak shaving instructions to each cluster. Finally, the effectiveness of the method is verified by using the real DGs data of a regional power grid in China based on the MATLAB simulation platform. The results demonstrate that the proposed methods can simply the calculation complexity by ranking the DGs in the peak shaving task and update the reliable aggregate adjustable power of each cluster in time to allocate more reasonably.

Development and prospect of monitoring and prevention methods of icing disaster in China power grid

Icing disaster is one of the most serious threats to power grid security in China. This article provides a brief glance of current China's monitoring and prevention methods of icing disaster (MPI) development status. Despite a late start, China's research and development on MPI have made outstanding achievements, including formation mechanism causing ice disaster, key technologies and characteristics, and anti/de-icing approaches development and application. It is apparent that Chinese scientists and engineers confronted the worldwide problem of anti/de-icing, and put forward a comprehensive solution, which plays a more critical role in icing disaster prevention and reduction of power grid during the past 15 years. The article states that the anti/de-icing devices have been applied successively to severe icing issues. These achievements are leading the world in the development and application of MPI. However, it is only at the extreme ice and snow conditions that can test and verify whether prevention methods are comprehensive and perfect or not. And the authors discovered the application limitations in the existing achievements. The article also discusses the overall development trends of MPI in the areas of key technological and technical breakthroughs and application scenarios etc. These discussions serve as references for MPI's future technological advancement and its ever-expanding applications.