Abstract:The carbon peaking and carbon neutrality goals promotes the development of green power in China, and also puts forward new requirements for green power consumption. In the existing research, there is a gap in the field of green power consumption responsibility allocation. Focusing on this problem, the necessity of green power flow is discussed, and the corresponding relationship of carbon emission flow, power flow analysis and green power flow is outlined. Based on power flow calculation, the basic concepts and important conclusions of green power flow analysis is proposed. The proposed method is verified by IEEE 14-bus system, and the distribution characteristics of green power flow in each node of the system under different conditions are analyzed. Finally, the authors discuss the application directions of green power flow analysis.

Abstract:Under the power spot mode, power selling companies participate in the medium and long-term and spot market at the wholesale side and sell electricity to retail users at the retail side. It is urgent to establish a perfect electricity price transmission mechanism from the wholesale side to the retail side. By quantifying the cost of electricity buying and selling under different electricity price transmission modes, power selling companies can seek the maximum profit of electricity buying and selling, so as to help power selling companies reduce market operation risks and enhance market vitality. Three electricity price transmission mechanisms, namely proportional transmission, real-time transmission and delayed transmission are proposed. The feasibility of the three electricity price transmission mechanisms is verified by the results of the example, the power consumption characteristics of several typical users are analyzed, and the choice of electricity price transmission mechanism for several typical users is given.

Abstract:With the explosive growth of user-side distributed energy, the number of prosumers with dual attributes of sources and loads is gradually increasing, and begin to participate in the power market as an emerging subject. Aiming at the clearing problem of oligopoly power market with prosumers,model is proposed based on the Cournot model. Furthermore,a prosumer market transaction a hybrid robust and stochastic method are used to deal with the uncertainty of renewable energy output within prosumers, so that a consumer robust and stochastic market transaction model is established. Finally, the effectiveness of the proposed model and method is verified on the IEEE-39 bus system, and the market power of producers and consumers is evaluated.

Abstract:With the deepening of China’s power system reform, the rapid development of distributed power technology and the increasing demand of users for green and low- carbon power,the research of distributed power trading has ushered in a huge opportunity. A transaction mechanism suitable for the day-ahead market of distributed power is studied based on the blockchain technology. It is composed of transaction contract chain and transaction settlement chain. The transaction contract chain realizes the functions of sealed quotation, transaction matching and transaction release, while the transaction settlement chain realizes the functions of electricity metering, electricity fee settlement and transaction result evaluation. A consensus mechanism suitable for the transaction contract chain and a new method of electricity charge accounting suitable for the transaction settlement chain are designed to safeguard the interests of those who abide by the contract and encourage both parties to abide by the contract and reasonably declare the transaction demand. Finally, the feasibility of the trading mechanism is verified by simulation experiment.

Abstract:Accurate grasp of future electricity price information is of great significance to obtain the operation state of the market, support all parties involved in the market to make effective decisions, and promote market players to reasonably optimize resource allocation. Hence, a comprehensive model is constructed for day ahead price forecasting based on blending integrated learning mechanism. The model fully considers the high volatility of electricity price and adopts Ashin transform to reduce the impact of input data volatility on the prediction model. Four mature single electricity price forecasting models, SVM, Lightgbm, EWNN and SARIMAX are selected as primary learners to ensure the forecasting accuracy based on blending integrated learning model. The actual operation data of American PJM power market is selected to verify the above electricity price prediction model. The comparative analysis of the prediction results shows that the electricity price comprehensive prediction model based on blending integrated learning mechanism integrates the advantages of a variety of traditional prediction models and has good accuracy and stability.

Abstract:Virtual power plants are able to participate in the competition of various types of power markets as the main body due to the gathering of distributed energy. In order to maximize the benefits of virtual power plants, it is considered that non-cooperative game and multi-type market design virtual power plant’s twolevel bidding mechanism, and promotes the simultaneous optimization of the virtual power plant’s“internal coordination and external unification”. Based on this, firstly, the internal bidding mechanism of the virtual power plant based on the marginal cost method is designed. Secondly, an external bidding mechanism for virtual power plants based on multiple types of power markets is designed,KKT is used to optimize the two-stage model constructed. Finally,an example is analyzed with a virtual power plant. The results of the calculation example show that the two- level bidding mechanism of the virtual power plant can reduce the operating cost and deviation penalty cost of the virtual power plant.

Abstract:Under the background of energy transformation,the development and utilization of demand-side resources will play an increasingly important role in ensuring safe supply of electricity, promoting development of the new power system, and contribute to achieve“dual carbon”goal. However, there is currently no systematic quantitative measurement method of its huge value, making it difficult to fully incorporate demand-side resources in power system planning. A demand-side resource value calculation method is proposed based on production simulation and sub-sectoral output value unit consumption, which can calculate the value of demand- side resources on power supply side, grid side, and user side. This method measures the value of demand-side resources within the scope of State Grid in 2025 and 2030, and analyzes the corresponding economics. By 2025, the installed capacity of new energy can be increased by 8 million kW, the maximum peak-valley difference ratio can be reduced by 4.6 percentage, the cost of users can be reduced by 40 billion yuan, the total investment of energy storage can be reduced by 60 billion yuan, and the carbon dioxide emission can be reduced by 800 million tons. Compared with new power plants, the annual income can reach 28.7 billion yuan.

Abstract:Rural industry is not only an important field for rural economic development and electrification, but also an important regional resource to interact with power grids through demand response. Different from large-scale industrial loads, rural industrial loads often require human assistance and have the characteristics of fixed and repeatable production processes. In order to exploit the adjustability of rural industrial loads, a load model considering rural production characteristics such as working hours and output requirements is established. For a more detailed description, the specific model is built based on the liquor-brewing industry. Based on this, a multi-scenario demand response strategies and operation optimization model are constructed for the rural distribution network to manage the demand response resources without affecting user production output. A case study is carried out to verify the proposed strategy based on the realistic load data of a 10 kV rural distribution network in Guizhou. The proposed strategy could exploit 36.1% of the example rural industry’s capacity for peak shaving without affecting user production output.

Abstract:With country’s attention on the development of “digital new infrastructure”, the use of urban substation resources to build“multi-station integration”scenarios and operation models has been initially explored and used due to the advantages of high land utilization and resource intensification. However, there are problems such as ownership, information asymmetry, privacy leakage, and high trust cost in the transaction process of multi-station transaction entities. The solutions to these problems are highly compatible with the technical characteristics of the Fabric blockchain. Therefore, aiming at the key business requirements of“multi-site integration”, based on the Fabric blockchain technology, a transaction platform architecture including multiple transaction entities participating in mutual assistance and sharing is constructed, and the back-end interaction subsystem, blockchain subsystem, and green power traceability core modules are designed to realize“Three Streams in One”of resource flow, information flow and business flow. Through the nearby integration of resources and the coordination and complementation of operation, the cost of construction and operation and the trust of transaction entities is reduced.

Abstract:Under the background of the double carbon target,a regional carbon emission prediction method is proposed for urban carbon emission path prediction. Firstly, based on Markov model and long-range energy alternatives planning system（LEAP）model,the energy consumption structure and energy demand of various industries in the region are predicted. Secondly, by calculating the carbon emission factors of each energy source and considering the impact of energy structure optimization and energy demand reduction on carbon emissions, the regional carbon emissions are calculated under different scenarios. Finally, a case study of regional carbon emission path prediction is carried out with a certain city in China as an example. The results show that the proposed method can effectively predict the regional carbon emissions and the impact of different policies and technological development on the carbon emission path.

Abstract:The implementation of the strategic objectives of carbon peaking and carbon neutrality requires the accurate measurement of user side carbon emissions. Limited by objective conditions, the existing carbon measurement methods focus more on the power generation side but ignore the impact of social production and consumption behavior on carbon emissions. The energy consumption behavior on the power demand side requires more elaborate carbon metering devices to realize real-time tracking and traceability. The time- varying and unbiasedness of carbon value are brought into the actual carbon measurement to realize the real-time measurement of carbon emission on the user side. A complete set of carbon metering device and platform has been developed to actively control and guide users to choose lower carbon production and business activities by using the collected real-time carbon data. After more than half a year of monitoring, operation and reform of an enterprise, the practicability of the developed carbon metering device and platform is verified.

Abstract:AC fault arcs, especially series fault arcs, are an important cause of fire in AC power supply systems. Their causes are complex, the production process is hidden, and the characteristic phenomena are not obvious. If not detected and dealt with in a timely manner, it may lead to catastrophic fires, posing a serious threat to personal safety and property. It first analyzes the mechanism and typical fault characteristics of AC fault arc hazards；secondly, the methods for detecting and locating fault arcs in AC power supply systems are systematically elaborated; finally, from the perspective of practical applications, the current urgent problems that need to be solved for AC power supply systems are pointed out, and future application scenarios and research directions for AC fault arc detection and fault arc localization are prospected.

Abstract:With the landing practice of electricity spot market, carbon emission allowances of distribution network and electricity spot prices will become factors that cannot be ignored in the Dispatching operation of the distribution network. dispatchable resources such as electric source, storage, and load, gradually become more and more abundant. Firstly, the model of“source-network-load-storage”on the distribution network side are proposed in the spot market environment, and at the same time, the paper conduct carbon emission benefit modeling for various power sources. Then power purchase benefits and carbon emission benefit optimization optimization scheduling model with multi- objective of power purchase cost and carbon emission benefit is established by considering the impact of the carbon trading price and regional quota limit. The effectiveness of the model is proved by using the pattern search algorithm to optimize the solution based on actual data. Finally, influence of the“source, load, storage”scale ratio,carbon emissions trading prices, the price of Chinese certified emission reduction and carbon allowances on dispatch operations is analyzed.

Abstract:Integrating distributed photovoltaic in charging stations will help reduce the operating costs of charging stations and promote low-carbon development in cities. The charging load impact of the charging station and the uncertainty of the distributed photovoltaic output make the total load power of the charging station have greater fluctuations. For centralized charging stations for electric buses with photovoltaic power generation systems, a multi-stage optimal dispatch model is constructed. In the first stage, according to the bus travel plan, an orderly charging model with the goal of maximizing the charging margin is established, and the intermittent charging period of the bus is calculated. In the second stage, a multi-level optimization model with the goal of reducing charging costs and grid fluctuations is established. On the basis of ensuring the lowest operating cost of bus charging stations, the overall energy quality of charging stations is improved. The simulation results show that the optimization strategy can reasonably arrange the charging behavior and charging power of electric buses, so that the charging cost of the bus station is the lowest, and the overall power curve remains stable during different electricity price periods.

Abstract:In order to reduce the impact of weather factors on short-term power load forecasting and improve the forecasting accuracy of the model, a short-term load forecasting model based on weather classification and convolutional neural networks is proposed. Firstly,through the preliminary classification of weather types, the model divides the original data sample set into four types such as sunny,cloudy, cloudy and rainy days. Secondly, in order to identify similar meteorological conditions, the correlation coefficient and k- means clustering method are used to find the meteorological factors that have the greatest impact on the new load output, cluster them, and select high similarity data samples. Then, according to the result of feature selection, the neural network input data set is constructed. Finally, the data set is input to the convolutional neural network for training and prediction. The proposed model has higher prediction accuracy through verification and analysis of numerical examples.

Abstract:Large- scale blackouts in cities affects a wide range of areas, and it is difficult for a single industry or department to deal with it. It is necessary to analyze the power failure scenario through scientific methods and build an emergency linkage mechanism covering multiple subjects. A scenario analysis model is constructed to describe power outage events from three dimensions:risk evolution, event classification and logical level. Based on the theory of urban system and the principle of scenario construction,through empirical analysis and logical deduction, key scenario chains such as power failure, communication interruption, oil supply interruption, water supply interruption and traffic paralysis are constructed, and the needs and deficiencies of emergency linkage are analyzed combined with cases. Based on the perspective of “scenario-response”, and taking electric power emergency repair and restoration as the main body, the emergency linkage mechanism covering the power grid enterprises, between the power plant and the grid, between the government and enterprises and between people’s livelihood industries is constructed, and the specific and feasible comprehensive linkage mechanism and strategy for higher effects on large-scale power outage events is proposed.

Abstract:In order to improve the effect of user access control in the power marketing system, a power marketing system user authority distribution method based on role based access control model is proposed. Trust attribute is used to extend the access strategy expression, obtain the global trust of the information resources of the power marketing system by monitoring the user’s access behavior, and control the access authority. According to the access authority control result, based on analyzing the autonomous access control model and mandatory access control. On the basis of RBAC model, and the concept of role is introduced. By quantitatively calculating the trust of different access behaviors among users in the assignment of permissions, the access level of user permissions is obtained, and the power marketing system is completed. The experimental results show that the proposed method has shorter user access authority control time and lower user authority allocation error rate, which improves user satisfaction.

Abstract:In recent years, the rapid growth in demand for electricity as a result of increased levels of terminal electrification has furtherly amplified the peak-to-valley and seasonal characteristic of the electricity demand curve, and increased the scarcity of energy during seasonal peak periods. In order to reflect the value of peak hour units power supply, and to prevent unreasonable price spikes when supply and demand are tight or congestion is severe so that protecting the consumer’s interest, price caps are created.Most of the price caps currently used in China’s pilot spot markets are set with reference to peak hour tariffs and lack complete design principles and processes. By summarising and comparing the experience of offer caps and clearing price caps in worldwide dayahead electricity markets, a method for setting offer caps and clearing price caps in different development scenarios in China is proposed, with the aim of reflecting the true value of electricity and protecting the interests of consumers.