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卷 49 ， 期 4 ， 2025
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Electric Power and Energy Balancing System for Power System with Renewable Energy in Extreme Weather
摘要：Frequent extreme weather events pose significant challenges to the balance of electric power and energy in the renewable energy power system. The system security risks caused by extreme weather are gradually increasing. Starting from the impact of extreme weather on the source-grid-load aspects of the power system with renewable energy, this paper analyzes and discusses the electric power and energy balancing system in extreme weather. It covers multi-source data integration of resources, meteorology, environment, and power grids, renewable energy resource assessment, and power prediction of renewable energy, electric power balance, energy balance, and optimal scheduling in extreme weather. First, this paper reveals the interaction influence mechanisms of data of resource, meteorology, environment and power grid in time and space, proposes a method for expanding small samples in extreme weather, and establishes a model for assessing renewable energy resources in extreme weather. Based on this, this paper establishes a theoretical system of multi-timescale source-load combined prediction in extreme weather and proposes a vector-based evaluation method of prediction errors, to provide decision support for the optimization of electric power and energy balance of the power system with renewable energy. Based on prediction, taking frequency security as the main factor, this paper proposes methods and strategies for electric power balance in extreme weather and analyzes the influences of extreme weather events on the energy balance at different timescales, to ensure energy balance from multiple perspectives, including the generation side, power grid side and load side. The optimal dispatching framework for the renewable energy power system in extreme weather is proposed. Finally, this paper prospects the research topics for the power system with renewable energy in ensuring the balance of electric power and energy in extreme weather.关键词：extreme weather;active power forecasting of renewable energy;electric power balance;energy balance;renewable energy accommodation;active control;optimal scheduling7|6|0更新时间：2025-06-16 - 摘要：The global warming trend has increased the occurring probability of compound disasters. Accurate evaluation of the failure rate for transmission lines under compound disasters is the quantitative basis for the power grid risk warning and emergency decision-making. The method of cumulative failure rate based on independent events of disaster types cannot reflect the time-varying nature of disaster evolution or the coupling characteristics of mutual influence between disaster types. It is difficult to objectively reflect the fault risk faced by transmission lines in the compound disaster scenarios. Whole reductionism thinking (WRT) integrates the global view of holism with the mechanistic view of reductionism, and it is a new paradigm for studying complexity problems. The complexity root of compound disasters is analyzed from the perspective of time-varying and coupling characteristics. From the perspective of disaster-type independent analysis and compound-disaster analysis, the current status and problems faced by evaluation technologies of the failure rate for transmission lines under natural disasters are reviewed. A research approach for the WRT-based comprehensive disaster analysis method is then proposed, and an evaluation framework of “offline optimization based on classification features, and online execution based on actual disaster situations” is established. Several key technologies of comprehensive disaster analysis method are finally discussed.关键词：compound disaster;failure rate;whole reductionism thinking (WRT);transmission line;adaptive decision optimization5|3|0更新时间：2025-06-16
- 摘要：In response to the problem that the disaster-type independent analysis is difficult to adapt to the time-varying and coupling characteristics of the complex external environment of the power grid, the first paper in the series established a comprehensive disaster analysis framework based on whole reductionism thinking (WRT). As a sequel, an online evaluation algorithm of failure rate for transmission lines based on comprehensive disaster analysis is proposed. Firstly, according to the coarse-grained characteristics of the time series of the meteorological disaster status and trends, the compound-disaster status and trends are classified and encoded. Secondly, by dividing compound disaster areas, compound geographic feature areas, and overlapping areas of compound disasters and geographic features, a granularity adaptive division method for line segments is proposed. Then, according to the mechanism of “offline optimization based on classification features, and online execution based on actual disaster situations”, the failure rate of each line segment under each type of compound-disaster status and trends is evaluated. Taking the disaster causing process of compound disasters as a whole, the time series of failure rate of each transmission line is obtained by aggregating the failure rates of line segments. Finally, the effectiveness of the proposed method is verified by taking the actual power grid operation data of a certain province in China as a case.关键词：compound disaster;failure rate;whole reductionism thinking (WRT);transmission line;online evaluation;adaptive decision optimization3|1|0更新时间：2025-06-16
- 摘要：With the high proportion of renewable energy, extreme weather events bring great risks and challenges to power production. Among these extreme weather events, extreme steady weather, as a special atmospheric feature, usually tends to result in continuous low renewable energy output for days, which greatly impacts the long-term supply-demand balance of new power systems. Aiming at the risk of long-term supply-demand imbalance caused by extreme steady weather, a quantitative risk assessment and control method is proposed from the perspective of optimal planning. Firstly, the extreme steady weather for power security is defined, and extreme scenarios are identified and extracted. Then, based on the extracted scenarios, the power production simulation is carried out, and the evaluation index system of long-term power supply-demand imbalance is constructed. On this basis, a risk assessment model of long-term supply-demand imbalance in extreme steady weather based on chance constraints is proposed. Finally, the above-mentioned model is embedded into the traditional power planning model to realize the optimal allocation of long-term flexible resources for the risk management of long-term supply-demand imbalance. Based on the IEEE RTS-79 case analysis, the effectiveness of the proposed method is demonstrated, and the role of long-term energy storage in the risk management of long-term supply-demand imbalance in extreme steady weather is explored.关键词：new poer system;steady weather;supply-demand balance;risk assessment;risk management;long-term energy storage8|4|0更新时间：2025-06-16
- 摘要：Due to the differences in operation conditions during dry and wet seasons, complex relations between water power and electric power, and comprehensive utilization demands such as flood control, ecology, navigation and so on, it is difficult to solve how to evaluate the defense capability of 10 GW-level large-scale cascade hydropower stations against long-period extreme fluctuations of renewable energy. First, the analytical characterization method of extreme fluctuations of renewable energy is proposed, and the extreme fluctuation events are mined from the historical data so that the characteristics of wind power-photovoltaic extreme fluctuations can be revealed. On this basis, a perturbation optimization evaluation model of defense capability of cascade hydropower plants against extreme fluctuations of renewable energy is established. The 0-1 mixed-integer linearization modeling technique is adopted to efficiently solve the mathematical model. Taking a river basin cascade hydropower stations station of a Southwest provincial power grid in China as an application case, the defense capability of cascade hydropower stations against extreme fluctuations of renewable energy and its sensitivity to the renewable energy installed capacity are analyzed, and the results can provide guidance for electric power and energy balance scheduling under extreme weather in power grid.关键词：cascade hydropower station;renewable energy;extreme fluctuation;defense capability;electric power and energy balance6|1|0更新时间：2025-06-16
- 摘要：In the context of frequent occurrence of multiple types of extreme weather and the continuous increase in the proportion of renewable energy, to ensure the safe and stable operation of the future power system under extreme weather conditions, a full-scenario risk assessment method of new power system planning scheme for multiple types of extreme weather is proposed. Firstly, potential extreme weather that causes actual regional power grid risks is screened from historical information, and the mapping relationship between meteorological factors and power grid status is analyzed to propose a power grid risk scenario recognition method based on extreme meteorological conditions. Secondly, a multi-uncertainty model for risk scenarios is established for factors such as source and load power, equipment failures under extreme weather conditions, risk scenarios and their probabilities are generated. At the same time, considering the characteristics of the future power grid and the impact of extreme weather, a targeted risk consequence index system for planning schemes has been proposed from the perspectives of adequacy, flexibility and safety stability. In response to the problem of inaccurate and efficient simulation of the operation status of the actual power grid risk assessment in the future, a practical power grid consequence calculation method based on the state grid planning simulation analysis and calculation platform has been proposed. Finally, the planned power grid in Northeast China in 2025 has been evaluated, and its high-risk areas and risk categories under high-temperature and windless, and blizzard weather conditions have been analyzed.关键词：risk assessment;new power system;weather extreme;full-scenario;meteorological factor;multiple uncertainties;planning6|2|0更新时间：2025-06-16
- 摘要：Energy storage technology provides an important technical means for the new power system to deal with the problem of insufficient system supply adequacy caused by the randomness and volatility of high proportion of renewable energy generation. However, low-probability long-period meteorological events of low wind-speed and low irradiation bring a high-risk impact on the reliable power supply. Considering the spatial complementary characteristics of the event occurrence law, the overall optimization of the renewable energy base location in the planning stage is one of the important technical means to improve the adequacy of renewable energy generation in the receiving area. Based on the high-resolution long-period historical meteorological analysis data set, focusing on the temporal-spatial distribution characteristics of long-period low-wind-speed steady weather events, the definition index of the long-period low-wind-speed steady weather events is proposed, the steady weather screening is completed, and the temporal distribution characteristics of a single geographical grid point are quantitatively analyzed. On this basis, the calculation results of the electric power meteorological region in China based on the spatial morphological characteristics of the event are proposed, and the influence of long-period low-wind-speed steady weather events on the power supply adequacy and the location and layout of renewable energy is quantitatively evaluated .关键词：new-power system;long-period low-wind-speed event;steady weather;temporal-spatial distribution;power adequacy;planning;renewable energy3|5|0更新时间：2025-06-16
- 摘要：The resilience enhancement of power systems under natural disaster conditions is of great significance to ensure the safe and stable operation of power systems. Designing the corresponding marketization mechanisms is an important way to enhance the power system resilience and incentivize the investment of electric power resources. Therefore, a marketization mechanism framework for the resilience enhancement of power systems is proposed, and the detailed definitions and modes of resilience insurance and pre-disaster electricity futures markets are given. Subsequently, insurance theory is introduced to establish the resilience insurance model, and the model of the pre-disaster electricity futures market is also proposed. Furthermore, a case analysis is conducted on the resilience insurance model, and the analysis results show that the proposed marketization mechanism can achieve the goal of maximizing the net profit of the insurance company and enhancing the power system resilience at the same time. Finally, the preliminary laws of balancing the resilience and economy of power systems are presented.关键词：power system;resilience;extreme weather;electricity market;insurance;electricity futures market4|2|0更新时间：2025-06-16
- 摘要：In recent years, the increasing extreme weather such as the continuous high-temperature draught and low-temperature ice-coating has caused the power supply-demand imbalance in regional power systems, resulting in the occurrence of large-scale power outages or load curtailment. The main reason is that in the new power system, extreme weather has higher impact on supply-demand balance. Aiming at the long-term climate change, a framework of resilience assessment and enhancement of the power system is illustrated. Firstly, a compact operation model of power systems considering the climate parameters is established to characterize the impact of different types of extreme weather on various power sources, power grids, and loads. Secondly, an extreme scenario generation method based on the modular denoising variational autoencoder (MDVAE) algorithm is proposed. Finally, a multi-type power source expansion planning method of new power systems is proposed for power supply-demand guarantees under the continuous extreme weather. Based on the typical source-load scenario set generated from the extreme weather data in a province in South China, the proposed collaborative planning method is verified by the simulation with IEEE standard cases.关键词：new power system;resilience;supply-demand balance;extreme weather;scenario generation;power source planning4|2|0更新时间：2025-06-16
- 摘要：When the arrival of a cold wave triggers a sudden drop in weather temperature, the energy consumption of the load increases, the output of renewable energy sharply decreases and the system backup and the power supply capacity of the higher-level power grid are insufficient, resulting in a significant power supply shortage problem within the power grid in a short time. With the increasing number of electric vehicles on the load side and the improvement in the responsiveness of flexible resources, the load-side flexibility resources are adjusted to compensate for the power shortage caused by the cold wave. This paper first clarifies that the flexibility resources varies with changing scenarios, explores and constructs models of flexible resources such as electric vehicles during cold wave. Secondly, considering that electric vehicles as flexibility resources need to participate in power grid scheduling through aggregation, a method for aggregating electric vehicles with uncertain connection times is developed. Subsequently, based on the flexibility resources during cold wave weather, non-residential loads and residential loads, a rolling optimal scheduling method for the power grid during cold wave weather is proposed with the objective of minimizing social losses. The electricity adjustment of various resources in the grid during cold wave weather is determined. Finally, through case studies, the proposed method is shown to effectively address power supply shortages in the power grid during cold wave weather.关键词：flexibility resource;electric vehicle;cold wave;optimal scheduling;vehicle-to-grid (V2G)6|1|0更新时间：2025-06-16
- 摘要：As the proportion of the renewable energy access continues to increase, traditional thermal power is gradually replaced. Ensuring daily peak regulation under conventional conditions and power supply support under adverse weather conditions with limited flexibility is the basis for the safe operation of new power systems. On this basis, a multi-timescale balancing method for power systems considering renewable energy accommodation and power supply support is proposed. Firstly, the optimal scheduling curve of long-term energy storage in several year-round net load scenarios is calculated and taken as the operation experience. Then, in the week-ahead stage, according to the renewable energy power prediction to determine whether it is adverse weather conditions, the power supply support strategy is designed for adverse weather conditions, and a flexibility-based scheduling strategy collaborating day-ahead, intra-day and real-time stages is designed for conventional scenarios. The proposed method does not require the accurate output curve prediction of the renewable energy, and can realize the organic coordination of multi-time scale scheduling from year-round to real-time scheduling, as well as the multi-source coordination of long-term and short-term energy storage and conventional units. Finally, a numerical case is given with reference to a regional power grid data and compared with the traditional rolling optimization method to verify the advantages of the proposed method and the effectiveness of the power supply support strategy.关键词：long-term energy storage;renewable energy accommodation;multi-timescale balancing;power system with high-proportion of renewable energy;flexibility;power supply support5|3|0更新时间：2025-06-16
- 摘要：The climate change is intensifying, while the daily variation characteristics and relationships of wind, photovoltaic, and other renewable energy outputs and loads under regional-scale extreme temperature events remain unclear. Therefore, this paper uses independent models to simulate the impact of weather on load and wind, photovoltaic, and hydro power outputs. The joint probability and confidence intervals of outputs are calculated using Copula functions. Based on climate model data, the daily variation characteristics of power output and load as well as the power supply-demand relationship are estimated under heat waves and cold waves in typical provinces of North China and Southwest China by 2030, the target year for China’s carbon emission peak. A novel boosting ensemble learning model is proposed to predict the impact of weather on photovoltaic output, and calibrated with historical measured data. The validation shows that the model achieves a mean daily output error of 1.27% under actual extreme weather conditions, and the mean absolute error is significantly lower than other ensemble learning methods. The medium- and long-term forecast indicates that in 2030, typical provinces in North China and Southwest China are prone to experience power supply shortages during the evening hours of days under heat waves and cold waves, and indicators such as peak values and time of power supply and demand under extreme temperature events in the relevant regions in the future are given.关键词：photovoltaic power generation;heat wave;cold wave;extreme weather;source-load characteristic;confidence interval;power supply and demand4|3|0更新时间：2025-06-16
Risk Assessment of Electricity Power Balance and Improvement of Power Protection Capability of New Power System Under Extreme Weather Conditions
- 摘要：The operation of photovoltaic-energy storage plants includes two parts: photovoltaic power forecasting and resource optimal scheduling. The photovoltaic power forecasting is usually carried out first with the goal of the highest forecasting accuracy, and then the optimal scheduling of the photovoltaic-energy storage plant is carried out based on the forecasting curve. However, there is a nonlinear and asymmetric relationship between the objective function value of optimal scheduling problem and the photovoltaic power forecasting error. At the approximate forecasting error level, the photovoltaic power forecasting result aiming at the highest accuracy does not necessarily lead to the maximum operation revenue of the photovoltaic-energy storage plant. In this regard, a value-oriented photovoltaic power forecasting method for improving the operation revenue of photovoltaic-energy storage plants is proposed. Firstly, a bi-level optimization problem is constructed, which includes photovoltaic power forecasting and power plant operation. The upper layer is the training problem of the day-ahead photovoltaic power forecasting model, and the lower layer is the two-stage optimal scheduling problem of day-ahead bidding and intra-day operation for the photovoltaic-energy storage plant under the conditions of given photovoltaic power forecasting model. Then, the upper forecasting problem is transformed into a combined forecasting form, and the forecasting model parameters are set as weight coefficients. A parameter solving method for the forecasting model based on iterative optimization is designed. Finally, using actual photovoltaic power plant data and electricity price data for case analysis, and compared with the photovoltaic power forecasting method that aims to achieve the highest forecasting accuracy, the effectiveness of the proposed method in improving the operation income of power plants is verified.关键词：photovoltaic-energy storage plant;value-oriented forecasting;photovoltaic power forecasting;optimal scheduling;combined forecasting;bi-level optimization;self-organizing map5|4|0更新时间：2025-06-16
- 摘要：As wind power is widely integrated into transmission systems and distribution systems in centralized and distributed forms, it is a new challenge how to implement the coordinated economic dispatch of integrated transmission and distribution systems to ensure the economy and security of the whole system considering the uncertainty of wind power outputs. In this paper, firstly, a robust economic dispatch model of integrated transmission and distribution systems considering the wind power uncertainties is proposed, and a polyhedral uncertainty set is adopted to describe the uncertainty of wind power outputs. Secondly, under the framework of the column and constraint generation (C&CG) algorithm, a distributed algorithm based on Lipschitz dynamic programming and analytical target cascading is proposed for the C&CG master problem and C&CG sub-problems, respectively, to ensure the relative independence of information between the transmission system and distribution system. Finally, the simulation is carried out on a small integrated transmission and distribution system and an actual integrated transmission and distribution system. The results verify the correctness and effectiveness of the proposed algorithm.关键词：transmission system;distribution system;uncertainty;wind power;robust optimization;economic dispatch;column and constraint generation (C&CG);Lipschitz dynamic programming;analytical target cascading4|1|0更新时间：2025-06-16
- 摘要：The medium- and long-term scheduling of traditional microgrids is difficult to take into account the energy cycle process of energy storage during the daily energy balance, which may not only lead to the inability of the daily energy balancing scheme to support the charging and discharging strategy of energy storage during the initial period of the day, but also cannot adapt to the high loss of the electricity-hydrogen conversion process. Therefore, a two-stage stochastic optimal scheduling method combining adaptive period division and variable-resolution is proposed. Firstly, for the “near small and far big” problem of uncertainty, a model of source-load output characteristics based on the modified martingale model is established. Secondly, a two-stage variable-resolution stochastic optimization architecture for the medium- and long-term scheduling of micro-energy networks with hydrogen is constructed. At stage one, an adaptive time division method based on deep neural network is proposed. At stage two, with the goal of minimizing the system operation costs and combining with time-segment chance constraints, the stochastic optimal scheduling models with coarse and fine resolutions are established, respectively. The latter arranges the hourly equipment output plans based on the state of charge of hydrogen storage equipment decided by the former, and a solution scheme based on sampling method is proposed. Finally, the effectiveness of the proposed model and method is verified through numerical simulations.关键词：adaptive time division;medium- and long-term scheduling;martingale model;uncertainty;time-segment chance constraint;micro-energy network4|0|0更新时间：2025-06-16
- 摘要：The untrustworthiness issues of artificial intelligence (AI) algorithm hinder its practical application in the scenarios such as power grid stability analysis and control. At present, there are no specific trustworthiness evaluation indicators applicable to the intelligent assessment model for power grid stability. Regarding the characteristics of the electric power industry, the trustworthiness evaluation for AI stability assessment models is carried out, and the five sub-indicators of correctness, complexity, robustness, transferability and interpretability are chosen to construct the trustworthiness evaluation indicator system of the intelligent assessment model for power grid stability, and the specific calculation methods for each sub-indicator are summarized. Meanwhile, the fuzzy analytic hierarchy process is introduced and combined with subjective and objective evaluation to determine the weights of each sub-indicator and calculate the comprehensive trustworthiness indicator. Finally, by taking the voltage support strength, broadband oscillation, and frequency stability assessment models as a case, the trustworthiness evaluation and analysis are carried out, and the results verify the effectiveness of the proposed method.关键词：artificial intelligence;power grid stability;trustworthiness;transferability;interpretability;fuzzy analytic hierarchy process7|1|0更新时间：2025-06-16
- 摘要：The voltage drop on the source side in the distribution network will lead to the transient instability of droop-controlled grid-connected inverters. Subsequent traditional unchecked reclosing will bring overcurrent problems, posing significant challenges to the safe operation of the inverter. To address the problems of transient power angle instability and overcurrent in the droop-controlled inverters due to the source-side voltage drops in the distribution network, as well as the impulse current generated by traditional unchecked automatic reclosing, this paper proposes an optimal control method for droop-controlled inverters during the full cycle of the fault transient. This method effectively improves the grid-connected operation stability of inverters and reduces the impulse current during reclosing to achieve a smooth grid connection. Firstly, the paper analyzes the transient characteristics of the inverter during the fault, and the relationship between the instantaneous overvoltage of the reclosing and the voltage amplitude, phase angle and frequency deviation on both sides of the high-voltage-side circuit breaker. Secondly, during the voltage drop phase, the reference value of the inverter power is dynamically adjusted based on the relationship between the active power of the droop-controlled inverter and the voltage output characteristics of the point of common coupling, as well as the influence of reactive power on the line current amplitude. This adjustment is made according to the actual working conditions, and the transient power angle stability before and after the fault is controlled to limit the output current of the inverter below the safety threshold. During the reclosing transition phase, the comprehensive adjustment mechanism of the frequency-phase angle is introduced to reduce the voltage frequency and phase angle difference. This mechanism reduces the number of proportional-integral controllers in the command calculation link and greatly shortens the time required for quasi-synchronization compared to the existing grid-connected control mechanism. Finally, the correctness of the theoretical analysis and proposed method is validated by combining simulation and experimental results.关键词：droop-controlled inverter;transient power angle control;fault current limiting control;quasi-synchronization;automatic reclosing4|3|0更新时间：2025-06-16
- 摘要：Super-resolution reconstruction for low-frequency power data is helpful to realize the accurate situation awareness and decision analysis of power systems. The existing super-resolution reconstruction algorithms have problems such as imprecise reconstruction result and weak generality. Therefore, a super-resolution reconstruction technology for power data based on improved diffusion model is proposed. The diffusion model can capture subtle and complex features in the data, and can gradually generate high-frequency power data under the guidance of low-frequency data. By combining the long short-term memory network with the diffusion model, the ability of the model to mine time series data is further enhanced, and the ability of super-resolution reconstruction is improved. The power data in load and harmonic scenarios are used for case verification, and the experiments show that the proposed method can accurately reconstruct high-frequency data. At the same time, the model has good generalization and flexibility, which can be applied to untrained electrical parameters and buildings’ data, and can also reconstruct data with different precision.关键词：renewable energy;super-resolution reconstruction;diffusion model;power data;high-frequency data4|0|0更新时间：2025-06-16
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