Power System In China Research Articles

Integration of smart charging of large-scale electric vehicles into generation and storage expansion planning: a case study in south china

This paper studies how to integrate the smart charging of large-scale electric vehicles (EVs) into the generation and storage expansion planning (GSEP), while analyzing the impact of smart charging on the GSEP of a real power system in south China. For this purpose, a random simulation-based method is first developed to provide the tractable formulations of the adjustable charging load and reserve provision from EVs. This method avoids the unrealistic assumption that EVs drive and charge every day, which often exists in prior relevant approaches. Based on the random simulation, this paper proposes a novel GSEP optimization model which incorporates the weekly adjustable charging load of EVs. In the proposed model, the total charging load of EVs can be co-optimized with the investment and operational decisions of various generation and storage units. This GSEP model is applied to a provincial power system in south China. The numerical results show that the implementation of smart charging can significantly alter the decisions of GSEP. As the participation rate of smart charging improves from 0% to 90%, there is an additional 1,800 MW installation in wind and solar power, while the need to build new batteries is noticeably reduced; also, depending on the level of EV uptake, the annualized total system cost decreases by 5.11%–7.57%, and the curtailment of wind and solar power is reduced by 10.34%–19.64%. Besides, numerical tests reveal that the traditional assumption that EVs drive and charge every day can mislead the evaluation of adjustable charging load and overestimate the daily charging power peak by averagely 24.72%.

Short-term voltage stability analysis in power systems: A voltage solvability indicator

This paper presents an analytical study for short-term voltage stability based on a novel indicator. First, it is shown that the reduced Jacobian matrix of network equations can be transformed to obtain an approximately symmetric matrix which is usually positive definite when the system under study is stable. The minimum eigenvalue of the matrix is suggested as a short-term Voltage Solvability Indicator (VSI). Then, properties of the reduced conductive matrix and susceptance matrix which have significant impacts on VSI are examined. The focus of the study is power systems with multiple constant power injections, while VSI can also be applied to analyze the impact of generic power system models. It is shown that as the penetration level of constant power injections increases, VSI decreases and the system becomes more vulnerable to voltage collapse. Finally, the relationship between the eigenvalues of the reduced Jacobian matrix and the structure-preserving Jacobian matrix is established. As a result, the suggested VSI can be efficiently computed by exploring the sparsity of structure-preserving Jacobian matrix of network equations. Case studies of several test systems including a simplified 575-machine 8117-bus East China power system are reported, demonstrating the effectiveness and practicability of the proposed method.

Development of low-carbon technologies in China's integrated hydrogen supply and power system

Hydrogen and electricity are crucial and interdependent energy carriers in China's pursuit of carbon neutrality, suggesting the necessity of utilizing cost-effective low-carbon technologies that facilitate their integrated development. The cost-optimal, provincial level, deployment of low-carbon technologies under this long-term goal remains to be determined. This study employs the REPO model to identify the cost-optimal, low-carbon hydrogen production mixes and the evolution of the integrated power system of China from 2020 to 2050. The integrated planning and operation of hydrogen supply and power systems are explored at the provincial level. The role of high-temperature gas-cooled reactors in this integrated energy system is also analyzed. The results reveal that electrolytic hydrogen would dominate China's hydrogen supply after 2040, with alkaline, proton exchange membrane, and solid oxide electrolyzers produce over 1 Mt of hydrogen in the short term, by 2035, and in 2050. Leveraging the low-carbon heat production of high-temperature gas-cooled reactors in addition to its electricity generation to meet the thermal requirements of solid oxide electrolyzers could boost the output to 4.2 Mt in 2050 and reducing the total system CO2 emissions and costs by 2.28% and 0.05%, respectively. By 2050, the integration of hydrogen supply and power systems also generates up to 2194 TW h of flexible electricity demand by electrolyzers, which raised the renewable energy penetration by 4 percentage points while decreasing the need of flexible natural gas power generations and energy storages. This study is valuable for proposing the analytical framework and performing the provincial-level study of decarbonization of China's integrated hydrogen supply and power system.

Economic and environmental feasibility of coupled wind power-subsurface compressed CO2 energy storage system in China: An LCA approach

Energy storage is a crucial solution for addressing the uneven distribution of renewable energy sources, including wind, hydropower, and solar. A novel technology that combines energy storage with underground CO2 storage is introduced, building upon compressed CO2 energy storage (CCES), an advancement of compressed air energy storage systems. Through a case study and literature review, a life cycle assessment (LCA) is conducted to evaluate the economic and environmental performance of a wind power—CCES coupled system. The results indicate that the global warming potential (GWP) and acidification potential (AP) of the CCES system coupled with wind power are 19g CO2-eq/kWh and 0.13g SO2-eq/kWh, respectively, which are significantly lower than those of coal power and are lower than those of wind power alone. Currently, the power output of this energy storage system is limited. However, in an optimistic scenario, the cost to build and operate a wind power—CCES coupled system can be recovered within 16 years based on current electricity prices in China. Therefore, utilizing CO2 storage reservoirs to store excess electricity from wind power is a feasible approach in China's power system from both economic and environmental perspectives.

Intelligent Power System Stability Assessment and Dominant Instability Mode Identification Using Integrated Active Deep Learning.

Simulation analysis is critical for identifying possible hazards and ensuring secure operation of power systems. In practice, large-disturbance rotor angle stability and voltage stability are two frequently intertwined stability problems. Accurately identifying the dominant instability mode (DIM) between them is important for directing power system emergency control action formulation. However, DIM identification has always relied on human expertise. This article proposes an intelligent DIM identification framework that can discriminate among stable status, rotor angle instability, and voltage instability based on active deep learning (ADL). To reduce human expert efforts required to label the DIM dataset when building DL models, a two-stage batch-mode integrated ADL query strategy (preselection and clustering) is designed for the framework. It samples only the most helpful samples to label in each iteration and considers both information contents and diversity in them to improve query efficiency, significantly reducing the required number of labeled samples. Case studies conducted on a benchmark power system (China Electric Power Research Institute (CEPRI) 36-bus system) and a practical large-area power system (Northeast China Power System) reveal that the proposed approach outperforms conventional methods in terms of accuracy, label efficiency, scalability, and adaptability to operational variability.

Comprehensive analysis of carbon emission reduction technologies (CRTs) in China's coal-fired power sector: A bottom-up approach

Carbon dioxide (CO2) reduction technologies (CRTs) in the coal-fired power sector play an imperative role in the mitigation of environmental challenges and reducing CO2 emissions to help achieve the 2 °C target. However, a compelling necessity persists for a unified framework that can effectively and accurately estimate the costs and potentials associated with CRTs, arising from the diversity of technologies and unit types. Therefore, this study employs a bottom-up approach to analyze the costs and potential of 25 advanced CRTs in the coal-fired power sector, excluding CO2 capture, utilization and storage (CCUS), across 19 types of coal-fired power units. This analysis amalgamates the CO2 reduction supply curve (CRSC) approach with levelized cost of CO2 reduction (LCOC) and a broken-even analysis which could reflect the sector's average carbon reduction cost. The outcomes reveal the following key insights: (1) These technologies collectively harbor a substantial CO2 conservation potential amounting to 925.61 Mt CO2, with a broken-even price of CNY 410.1/tCO2. This reduction could potentially lower 20%–25 % of CO2 emissions in China's power system in 2022, highlighting the crucial role of CRTs in achieving a low-carbon transition and national climate targets; (2)Steam turbine flow path retrofit (T8) not only offers a relatively high CO2 reduction potential (>60 Mt CO2), but also features a low cost (<CNY 150/tCO2) and high profit (>CNY 0.85/MWh). Prioritizing the development of this technology can significantly accelerate the low-carbon transition of coal power; (3) Carbon price have a paramount influence on the cost-effectiveness of CRTs and driving their adoption.

Peak-shaving cost of power system in the key scenarios of renewable energy development in China: Ningxia case study

Renewable energy has developed rapidly in Ningxia, and it has become the first provincial power system in China whose renewable energy power generation output exceeds the power load of the whole region. The access of a high proportion of renewable energy puts forward higher requirements for the peak-shaving capacity of the Ningxia power system. In order to solve the problem of calculating the peak-shaving cost in the key scenarios of renewable energy development in Ningxia, a quantitative model of the peak-shaving cost of the power system considering time-of-use price is proposed. We take Ningxia power system as an example to study. First, the key scenarios of the Ningxia power system peak-shaving are obtained, and the technical cost characteristic boundaries of various peak-shaving resources are determined. Second, according to the characteristics of typical daily renewable energy and load in Ningxia, the quantification model of the power system peak-shaving cost is established. The model takes the minimum total cost of the power system as the objective function and considers the constraints such as technical output of thermal power units, charge-discharge characteristics of energy storage and time-of-use price mechanism. Finally, the model is solved and the peak-shaving cost and unit output under the optimal scheme are obtained. This example shows that the model can effectively evaluate the peak-shaving cost and unit output of the Ningxia power system under the key scenarios of peak-shaving.

Study on Preparation and Application Technology of Micro scale New Foam Ceramics for Power Equipment

With the proposal of a new type of power system in China, the new environment-friendly insulating medium micro nano foam ceramic is urgently needed to replace SF6, epoxy resin and other insulating materials in the GIS/GIL key power equipment. The new material technology can prepare: foam ceramic design method. Preparation method of foam ceramics and the functional modulation of micro/nano structures. The electrical performance of the foam ceramics was improved. Achievable: the stable performance of micro/nano structures under the high field strength. Excellent thermal conductivity under high current action. It has local replacement function in insulation material applications such as SF6 and epoxy resin. Detectable: Starting from the electrical performance of the UHV hybrid insulation material system, UHF technology and photo-acoustic spectroscopy technology are applied to the high sensitivity detection of the decomposition products and partial discharges of foam ceramics, focusing on types of fluorocarbon decomposition gases, making use of strong correlation between the decomposition products and the partial discharge detection data, and combining the multi-source data fusion algorithm to achieve the prediction of insulation structure data sequence and online detection of the latent faults for the special GIS/GIL.

Complex network theory and game theory-based partitioning decision-making of parallel restoration for resilient power grid

The ability of fast restoration reflects power system resilience and safety. This paper proposes a partitioning decision-making method for parallel restoration based on the label propagation algorithm and the cooperative game theory. The topological and physical characteristics of blackout systems are considered as the edge weight and the node importance simultaneously for formulating the partitioning model. By the label propagation algorithm, various labels representing different subsystems mark all buses. To accelerate the speed of convergence and prevent the label oscillation, this paper proposes a game strategy of cooperation between buses and subsystems by evaluating the Shapley value of buses. The partitioning constraints are integrated into each label propagation process to assess the feasibility of the partitioning strategy. Finally, case studies on the IEEE 39- and 118-bus test systems and an actual urban power system in South China verify the effectiveness of the proposed method.

Potential way to plan China's power system (2021–2050) for climate change mitigation

Planning power system (PS) towards renewable energy is crucial for reducing carbon dioxide (CO2) emission as well as mitigating climate change. However, the inherent uncertainty and hierarchical structure of PS pose intractable challenges to the planning process. This study develops a multi-GCM-based interval bi-level programming (MIBP) method that can balance two-level decision-making conflict between CO2-emisison reduction and system cost minimization. MIBP can also deal with uncertainties expressed as interval values in objective functions and constraints. Then, a MIBP-PS model is formulated to plan PS for China (2021–2050), where the upper-level objective is to minimize CO2 emission and the lower-level objective is to minimize the system cost. The major findings are: (i) the CO2 emission for PS would reach peak value before 2030 and then reduce by [10.2, 20.4]% in 2050, which is mainly owing to the curtailment of fossil fuel; (ii) compared with the conventional model, CO2 emission from MIBP-PS model could decrease by [3.1, 4.8]%, which shows the superiority of the developed model; (iii) the fossil-fuel power would be gradually replaced by renewable energy, and the proportion of coal-fired power would decrease by 38.8% by 2050, especially small coal-fired facilities (i.e., below 0.3 GW) should be gradually phased down.

Structure and path analysis of digital transformation of power grid development under the background of new power system

Under the development trend of economic globalization, the new power system with new energy as the main body develops faster and faster. After China's power system enters the intelligent development environment of the Internet, a new generation of digital technologies such as artificial intelligence, mobile Internet, big data and cloud computing begin to transform the traditional power grid system, which not only speeds up the pace of digital transformation of power grid development. New development goals and effective measures are also proposed. Therefore, after understanding the practical significance of the digital transformation of power grid development in the context of the development of new power systems, this paper mainly studies the problems faced by the new power system and the design framework, and deeply discusses the commonly used digital technical means and development paths, so as to provide an effective basis for the reform and development of the power industry.

Calculation of the available transfer capability of trading channels based on power network congestion forecasting

Against the backdrop of increasing renewable energy penetration, frequent power network congestion has become a key issue limiting the available transfer capability of trading channels. In order to avoid power network congestion while improving the overall utilization of trading channels, we propose a method for calculating the available transfer capability of a trading channel based on power network congestion forecasting. First, this study uses a histogram-based gradient tree boosting (HGTB) model to forecast the severity and probability of power network congestion, which enables power system operators to determine the specific circumstances of congestion occurrence. Second, we analyze the sensitivity of the power trading network and generating units to transmission lines, aiming to calculate the available transfer capability of the trading channel on the basis of taking into account the control of transmission line congestion and the balance of supply and demand in the power market. Finally, the validity of the validation methodology is verified based on a case study of the power system in central China.

Application of Electronic Information Engineering Technology in Intelligent Communication

As a representative of advanced science and technology, communication intelligence technology has developed steadily in the past few years. At present, the wide application of electronic information engineering technology in electric power industry has a very important impact on the development and construction of electric power communication network. Electronic engineering technology provides a good solution to solve the problem of unstable power supply in China's power system, which not only promotes the development of the power industry, but also plays an important role in the maintenance of China's power system. In recent years, with the steady development of artificial intelligence technology, its application is also increasing, and it has gained more and more widespread social attention. Nowadays, with the continuous development of Internet technology and electronic computers, people's cognition of artificial intelligence technology and artificial intelligence products has slowly changed. The continuous progress of science and technology has made artificial intelligence walk in the front of today's scientific and technological development, and has attracted high attention and application from all walks of life. As the main communication technology produced in today's society, electronic engineering technology provides great convenience for People's Daily life. Electronic engineering technology is constantly innovating and breaking through on the basis of existing, and developing in the direction of intelligence.

Current Distortion and Sensitivity Calibration Problems of Rogowski Coil

Driven by technology, China's power system has been greatly improved, and has been gradually transformed and upgraded, bringing great improvements to performance in all aspects. Current distortion and sensitivity misalignment of Rogowski coils have always been the key problems to be solved in practical applications. This paper summarizes the methods of calibrating the sensitivity of the Rogowski coil in the shape of the single ring arbitrary skeleton, the Rogowski coil of the double ring skeleton and the Rogowski coil in the shape of the round skeleton, which provides the basis for other improvements of the Rogowski coils. The existing method to solve the current distortion of the Rogowski coil has a single method in the output of the differential current signal, which will reduce the limitation of the measurement range, and the suppression problem still cannot be solved well. This paper summarizes the solutions to current distortion in Rogowski coils, introduces the causes and solutions of current sensor and transistor current distortion, and puts forward certain correlations to provide reference and direction for follow-up research.

Development Strategy of Flexible Resources in China's Power System under the Carbon Peaking and Carbon Neutrality Goals

Development Strategy of Flexible Resources in China's Power System under the Carbon Peaking and Carbon Neutrality Goals

Power System Relay Protection Based on Faster R-CNN Algorithm

The technology of relay protection in China's power system has gradually changed from the traditional operation mode to the development direction of informatization, intelligence, and automation. As a result, the role of relay protection in the power system has become more and more important. It brings higher requirements to the reliability of relay protection; effective reliability assessment of the relay protection system and the corresponding condition operation, minimize or avoid accidents, and ensure the safety of power grids. Starting from the operating characteristics of relay protection, it is suitable for practical engineering applications. Aiming at the problems of low work efficiency and low inspection quality in manual inspection of relay protection pressure plate switching state, The Faster R-CNN image processing algorithm will be come up with. This method uses grayscale, binarization and filtering techniques to preprocess the platen photos, and uses RPN.

Renewable Electric Energy System Planning Considering Seasonal Electricity Imbalance Risk

The growing renewable integration significantly enhances the seasonal electricity imbalance of the electric energy system. However, traditional power system planning methods usually take into account the hourly power balance within typical days but seldom consider the seasonal imbalance risk in the long-term timescale. Therefore, this paper proposes a generation-transmission-storage co-planning model considering the seasonal imbalance risk brought by the long-term uncertainty of renewable generation in the power system. The Conditional Value at Risk (CVaR) method is introduced to quantify the seasonal imbalance risk. The power system energy balance constraints are decoupled into short-term (i.e., hourly) and long-term (i.e., monthly) energy balance so that the operation of the power system can be considered within different timescales and the seasonal imbalance risk could be calculated. The validity of the proposed model is first investigated via a modified Garver's 6-bus system case study. Furthermore, the research on the HRP-38 system (HRP represents high renewable penetration) illustrates that our proposed model could effectively control the energy imbalance risk from multiple timescales. Finally, the proposed method is applied to the whole China power system at the province level, proving that the proposed planning method could effectively enhance the reliability of China's power system, decreasing both the average annual short-term and long-term energy imbalance by 30%.

Environmental efficiency evaluation of China's power system considering factor's spatial dependence: A dynamic spatial network DEA approach

Evaluating and improving the environmental efficiency of the power system is the key to achieving sustainable development. However, the classic DEA approach is susceptible to producing biased results due to its inability to address spatial dependence across factors. Considering the spatial dependence of inputs and outputs, this paper proposes a dynamic spatial network DEA model with slacks-based measure (SNSBM) to examine the environmental efficiency of China's power systems, with a focus on the undesirable outputs of CO2, NOx, and SO2. The investigation incorporates the Moran's I test to account for the spatial interactions of patent counts, coal consumption, CO2 emissions, and renewable power generation. Compared to the classic network DEA, the SNSBM results reveal distinct spatial characteristics and a heightened level of differentiation, which highlights the importance of eliminating spatial dependence. From a dynamic perspective, environmental efficiency shows a visible surge in transmission and distribution divisions after 2015, confirming the success of China's market-oriented reform. In addition, CO2 is the largest contributor to the environmental inefficiency of the power systems, followed by NOx and SO2. This study highlights the importance of spatial dependence and provides many insightful policy recommendations for improving the environmental efficiency of China's power systems.

Role of demand response in the decarbonisation of China's power system

Realising China's carbon peaking and neutrality commitments requires a fundamental transformation to a renewable-dominant power system, presenting new challenges to the balance between power supply and demand. In addition to enhancing flexibility on the supply side, it is necessary to fully exploit the flexibility resources on the demand side. Accordingly, flexible load resources using a demand response (DR) mechanism are expected to play a crucial role. In this study, a DR module was developed for an optimal capacity expansion and operation model, the China renewable energy planning and operation (REPO) model. Three different DR behaviours were modelled, namely load shedding, short-term load shifting, and long-term load shifting. Under a forecasted carbon price, DR in eight major industries can achieve an annual cost saving of approximately 16.8 billion yuan and reduce carbon emissions by approximately 106 million tons by 2030. Investment in DR is cost-effective, particularly because the cost saving is nearly 3 times the present value in 2025 and about 4.3 times in 2030. Moreover, DR has a positive effect on reducing the installed capacity demand of coal power and energy storage, which is conducive to increasing the proportion of renewable energy generation and restraining the fluctuation of marginal power generation cost.

A novel dispatch adaptation load feature mapping network for multi-timestep load forecast

Power system dispatch (PSD) greatly depends on load forecast (LF) with high accuracy. However, since load curve evolving along time axis is affected by long-term trendy and short-term stochastics electricity consumption modes, it is not easy to forecast load under accuracy requirement of PSD especially for high-proportion renewable energy power system. Therefore, a novel dispatch adaptation load feature mapping network with coordinated memory (LFMN-CN), which can forecast multi-timestep load values in future dispatch span at a time, is proposed. It adopts layered mapping network structure: 1) load features based on periodicity are mapped into two-dimension input matrix in the first layer; 2) nodes in the hidden layer with long-term and current memory, which denote long-term trendy and short-term stochastics electricity consumption modes respectively, are fully connected to construct recurrent LF network; 3) multi-timestep LF values in outer layer are obtained by LF output vector adaptive to timesteps of dispatch span. It has advantages of improved accuracy and dependence only on historical load series. LF results in power system of China show that the proposed model can perform multi-timestep LF more accurately than single-timestep LF.