Abstract:With the acceleration of the work of electric energy substitution in China, a large number of multiple electric energy substitution loads have been connected, which has brought great challenges to the safe and stable operation of the distribution network. Assessment of load hosting capacity is of great significance to the distribution network planning. Firstly, the main load types of electric energy substitution are analyzed, and their operation models are established. Then, taking the maximum load capacity of the distribution network as the objective function, considering the flexible resource operation constraints of source network load storage side and the safe and stable operation constraints of the distribution network, an optimization model for the load hosting capacity of the distribution network is established, which is transformed into a second- order cone programming model through the second- order cone relaxation method. Finally, through the simulation of a 141 node example of an actual power grid, the quantitative evaluation of the load hosting capacity of the distribution network is realized,and the role of the optimal scheduling and load regulation capacity of flexible resources in improving the load hosting capacity of the distribution network is verified.

Abstract:As an electric energy alternative technology, regenerative electric heating will affect the safe operation of the distribution network in the process of application, with people’s attention to distributed energy resources and the development of electric heating related technologies, the research of electric heating is becoming more and more important. In order to fully exploit the adjustable potential of regenerative electric heating in the distribution network, the analysis is carried out from the two levels of regenerative electric heating unit and cluster. Firstly, the quantitative indicator of adjustable potential is proposed, including capacity, charge and discharge power, energy storage status, up-regulation capacity and down-adjustment capacity. Then the mathematical model of the adjustable potential indicators of regenerative electric heating units is analyzed. And then fuzzy clustering algorithm is used to cluster electric heating users based on the energy consumption characteristics of users, and the upward adjustment capacity and downward adjustment capacity of electric heating clusters are analyzed. Finally,the mathematical model is verified by specific examples.

Abstract:Electric ship is one of the most promising technology directions for the development of shipbuilding industry. It's an important measure to achieve carbon peaking and carbon neutrality goals under the field of waterborne traffic. Focusing on the current situation of the promotion of the electric ship in recent years,taking examples of the application practice of electric ships in Jiangsu, the characteristics of the electric ship, such as high construction cost, low operating cost, and significant environmental emission reduction benefits, are analyzed through experimental data. Based on the main features, the promotion mechanism of the electric ship is further analyzed. The relevant measures and results of Jiangsu practice are expounded. Through the construction of charging/battery swap infrastructure facilities for the electric ship and the reduction of the using cost of electric ships, new directions for the large-scale promotion of the electric ship are provided.

Abstract:With the rapid development of IoT and smart grid,the role of demand-side resources in supply- demand balance is gradually increasing. However, a large number of disorderly applications of demand response techniques can affect the reliability of distribution networks. To address such problems, a virtual power plant economic optimal scheduling method combining baseline load forecasting with load reduction and load transfer is proposed.Firstly, based on the historical data, the output of wind/optical power station and the baseline load of electric vehicles are forecasted by using the triple exponential smoothing method, and the adjust-able capacity of power users is observed. Then, based on the timesharing tariff mechanism with the objective of virtual power plant economic optimum, system constraints such as power balance,wind/light new energy forecast output and energy storage system operation cost are added to establish the electric virtual. Finally,the accuracy and effectiveness of the proposed method are verified by the actual data of 5 centralized charging stations and wind power stations in Zhengzhou, Henan Province.

Abstract:Under the background of vigorously developing renewable energy, in order to coordinate the interest relationship between the upper comprehensive energy system and the lower electric heating load demand. First of all, a dynamic pricing mechanism to deeply explore the potential interaction between the upper and lower layers is proposed. The upper layer of the system gives the prices of various energy sources. After the prices are transferred to the lower layer, the lower layer optimizes the output of each unit to achieve mutual benefit and win-win results for multiple stakeholders. Secondly, the comprehensive demand response capability of flexible electric load and flexible thermal load is considered to achieve better consumption of renewable energy. Finally, CPLEX is used to solve the two-layer model iteratively to verify the effectiveness of the proposed model and algorithm.

Abstract:With full implementation of the rural revitalization strategy and the accelerated development of agricultural modernization industrialization, China’s energy has gradually promoted the green and low-carbon transformation, the energy revolution has been put on the agenda, and the rural electrification led by the rural energy revolution has entered a new stage of development.The development status of rural electrification in China, and its problems under the background of dual carbon objectives, low-carbon clean transformation and rural revitalization strategy is analyzed. Combined with high proportion of new energy, some suggestions are put forward on rural power grid construction, work promotion mechanism, power universal service, investment innovation drive and so on.

Abstract:It is becoming more and more important to identify the correlation between electricity consumption and economic growth with the continuing electrification in China. It is constructed the Panel vector utoregression model and the impulse response function to identify economic growth, electricity consumption and structural change in China based on a provincial level panel data,in order to compare the difference of the correlation between the national level and Jiangsu province. There is a stable correlation between electricity and economic characteristics both nationwide and in Jiangsu. The national economic growth has a greater influence on electricity consumption in the short term and a weaker one in the long term, while there is a more consistent impact of economic growth and structural change on electricity consumption in Jiangsu,which reflects a more coordinated interaction between the electricity market and the economy and structure in Jiangsu. The difference of the correlation suggests that policy makers ought to make electricity investment plans according to the regional economic development level.

Abstract:Under the influence of the“dual carbon”policy,clean energy has become the type of energy advocated by the country. With the continuous development and application of renewable energy, the waste of renewable energy has attracted extensive attention, and energy storage technology has emerged. Between shared energy storage and micro-grid alliance, the distribution of benefits is of common concern to all parties. Therefore, an asymmetric Nash negotiation model for the benefits of micro-grid and energy storage power station based on the consideration of the responsibility absorption introduced by the state is proposed. Then, the nonlinear problem is transformed into two sub-problems of benefit maximization and benefit allocation of the micro-grid alliance. The alternating direction method of multipliers is used for distributed solution.The asymmetric Nash negotiation proposed is compared with the symmetric Nash negotiation. Through the comparative analysis of cooperative negotiation before and after, it is concluded that the proposed asymmetric Nash negotiation model considering the weight of absorption responsibility and the involvement of shared energy storage can not only reduce the cost of each subject, but also promote the absorption of renewable energy and effectively solve the problem of energy waste.

Abstract:In order to effectively solve the problem of consumption loss in the electric energy information acquisition system,a method of filling missing data based on regular self- encoders is proposed. Firstly, the energy data according to the characteristics learned by the regular autoencoder is reconstructed, and the repair of the missing data is realized. Then, regularization by adding the L21- norm is realized and orthogonal constraints to the loss function, the generalization ability of the model and uses Optuna to realize the automatic optimization of hyperparameters is improved. Finally, the test results of the actual data set show that compared with other autoencoders, the regular autoencoder can accurately fill in the missing data.

Abstract:Due to the existence of power and thermal energy in regional integrated energy system, it is difficult to couple and analyze multiple energy flows. A multi-energy flow calculation method of regional integrated energy system based on time series and coupling analysis is proposed. Firstly, the frequency modulation characteristics of the system are analyzed by using time series to obtain the operation frequency of the system. Steady- state network model of regional integrated energy system is constructed. Secondly, power flow of power system and thermal system is calculated respectively and through electrothermal coupling analysis, multi-energy power flow calculation results of the system are obtained. Finally, experimental results show that this method can accurately calculate the heating temperature and regenerative temperature of different pipelines in the thermal system, and can also calculate the voltage, active power and reactive power during the operation of the power system, so as to realize a more comprehensive multi- energy power flow calculation.

Abstract:Aiming at the integrated WG- PV- ESS planning problem of distribution network considering the uncertainty of distributed power and load. Firstly, the uncertainty of distributed power and load is characterized by a probabilistic model, and the probabilistic power flow was solved based on the improved semi-invariant method. Then, considering the investment cost, carbon cost, economic benefits and voltage improvement, and aiming at maximize the comprehensive benefit, the comprehensive planning model of WG- PV- ESS comprehensive planning model considering reactive power compensation device is established. A carnivorous plant algorithm based coevolutionary algorithm is proposed to solve the model. In this algorithm, the multi-agent comprehensive planning problem to be solved is decomposed into three sub-planning problems:distributed generation, energy storage and reactive power compensation devices, and each sub-problem is solved based on CPA, and the optimal planning scheme is obtained by coordinating the evolution of various groups through the ecosystem. Finally, the rationality of the proposed model and the efficiency and universality of the solution algorithm are verified by IEEE33 and IEEE69.

Abstract:In the scheduling decision-making process of load aggregator, ignoring user comfort level or determining user comfort level based on subjective preference will lead to non-ideal scheduling model results. Fuzzy optimization is introduced to solve the conflict between economy and comfort in scheduling decisions.Based on game theory, an aggregator decision model is established to balance user comfort and economic cost scheduling. At the same time, in order to speed up the solving speed of the game model, game model is linearized and solving algorithm is formulated.Finally, an example is given to verify the validity of the decision model. Meanwhile, the scheduling results are analyzed from multiple angles to verify the fuzzy optimization boundary conditions and influence of comfort threshold and energy storage substitution are analyzed.

Abstract:Different utilization approaches in the integration and consumption of clean energy are taken as the research object,and an economic benefit evaluation index system for multi- agent demand response is constructed to participate in the integration and consumption of clean energy from the three main bodies of power users, power grid enterprises and power generation enterprises. The model evaluates economic benefits. The research results show that the economic benefit evaluation level of participating in the multi- energy complementary system consumption is excellent,the economic benefit evaluation level of participating in the microgrid and virtual power plant consumption is good, and the economic benefit evaluation level of participating in the wind and solar storage and consumption is unqualified. On the basis of considering the degree of evaluation grade bias, it is further found that the economic benefits of participating in the generation and consumption of virtual power plants are slightly higher than those of participating in the generation and consumption of microgrids. The research conclusions are helpful to optimize the integrated con sumption and utilization of different clean energy sources, and provide an effective decision-making basis for the establishment of utilization methods based on the results of economic benefit evaluation.

Abstract:In order to explore the energy consumption characteristics and consumption technical routes in the nearly zero-energy consumption public building in the summer cold area, model selects a nearly zero- energy- consuming office building in Wenzhou as the research object, uses eQUEST building energy consumption simulation software and relevant provisions in the national standard GB/T51350. First of all, it stipulates that the energy consumption simulation of the project and design building of the project yearly, analyzes its energy consumption composition and energy consumption characteristics. Then it studies the largest outer window load, electricity composition and consumption technology path in winter and summer. Finally, it calculates the level of carbon emissions, the energy saving rate of the body, the comprehensive energy saving rate and the utilization of renewable energy, through the above channels, and achieves the design goals of the nearly zero energy consumption building of the project, also judges the carbon emission level of the building. The results of the research energy-saving professionals selects the technical route reasonably, and provides reference suggestions for the design of nearly zero energy consumption public buildings.

Abstract:At present, the demand response mode dominated by the seller’s market still has high reliability and enforceability.The response reliability models of different types of demand side loads are analyzed in order to reduce the impact of user behavior randomness on dispatching reliability. Dynamic response reliability evaluation models of different users are analyzed in order to improve the response enthusiasm of users. Finally, a dispatching model with the lowest operation cost and the highest reliability of dispatching capacity on the power grid side is constructed, which is constrained by the minimum clearing interests of users. The model can not only improve users’response enthusiasm, but also obtain the optimal dispatching operation mode of power grid interests.The effectiveness of the scheduling optimization model is verified by an example.

Abstract:In recent years, influenced by reforms of electric power system, economic transformation and upgrading, increased environmental protection efforts, frequent extreme weather events,and coronavirus pandemic, customers face problems such as declining output and difficult sales that increases the electric charge recycling risk. A regression model based on industry development trend is proposed to predict the electric charge recycling risk. Firstly, the seasonal adjustment algorithm is used to extract the trend item of the historical industry electricity sales, and then the affecting factors are comprehensively and quantitatively analyzed. On this basis, a prediction model is built to perceive the industry development trend. Using the perception result, combined with data such as user’s payment behavior and capacity change, an early-warning model for the electric charge recycling risk is built. The model objectively quantifies the risk probability of user’s electric charge recycling. Finally, the example verification result shows that the model has good predictive ability.

Abstract:In order to improve the operation efficiency and resource utilization of the power grid, improve the accuracy of budget and cost control, at the same time, help users to develop reasonable power supply plan and electricity consumption strategy, promote the continuous optimization of electricity service and electricity business environment, and build a power connection cost prediction model based on big data analysis of power. Firstly, analysis the data types in the power data, and using the MapReduce parallelization processing cluster mining algorithm, mining from the power system and the power cost related power data, obtain the clustering results. Then, through the time series analysis method build the total cost prediction model, and through the multivariate regression method to build the cost of factors prediction model, after the model prediction, get the best cost prediction results. Finally, by experiment, the model can accurately predict the power connection cost generated when enterprise users access, and can also effectively predict the change of power connection cost under different equipment prices and different voltage levels.

Abstract:Fully exploring the value of user data to identify user energy quality needs and promoting differentiated value-added services are of great value for improving user satisfaction and the competitiveness of power grid companies. Firstly, based on multidimensional user data, user profile theory to establish a multi-dimensional high- quality power user profile label system to identify users’power quality needs is introduced. Secondly, K-means clustering algorithm is used to profile high- quality power user groups,achieve user group division, quantify user power quality requirements based on prospect theory, and based on this differentiated value-added service package design is carried out. Finally, the effectiveness of the proposed method is verified through case analysis.