Abstract:In order to meet the requirements of“carbon peak”and“carbon neutralization”, relying on the rich resources of substations, the multi-station integration has become an important way for power grid companies to expand comprehensive energy services.Therefore, it is necessary to summarize the architecture designing,modeling theory and strategy optimization method of multi-station integration. On the basis of summarizing the development of multi-station integration, the existing main architecture is classified by AC and DC power supply, and both the overall architecture and the local architecture are summarized. Then, the mathematical models of energy storage power station, data center and charging station in multistation integration are analyzed and summarized. Next, the objective functions and constraints in capacity optimization and strategy optimization are classified and summarized. In addition, the existing problems are also analyzed, and the development and prospect of the key technology of multi-station integration are discussed.

Abstract:High penetration of wind power is a prominent feature of novel power system, while the randomness and anti- peak shaving of wind power lead to a greater demand for flexibility. Energy storage system（ESS）can effectively improve power system flexibility to cope with wind power uncertainty.Analyzing the impact of ESS on system flexibility is conducive to ESS planning and utilization. Based on the source- load-storage interactive economic dispatch model, considering the participation of ESS in system peak regulation, climbing and spinning reserve, the wind power dispatchable region is calculated by iterative generation of off- limit constraint boundary. The contribution of ESS to system regulation ability was quantified by comparing the positive and negative deviation boundary of system wind power dispatchable region under different ESS capacities and locations. IEEE 30-node system case study analyzes the influence of the distribution and capacity proportion between ESS and other flexible resources on system flexibility improvement, which provides decision supports for configuring ESS participating in power grid dispatching.

Abstract:In the new energy environment, the uncertainty of load demand and new energy power generation puts forward higher requirements for reserve capacity, and new energy and reserve replacement receive increasing attention. Based on the relationship between expected energy not supplied（EENS）and reserve capacity, total reserve capacity of the power system is determined and capacity is allocated among various types of generating units in a preferential way. Based on EENS and operation cost, the evaluation index of comprehensive substitution benefit of photovoltaic power generation system replacing thermal power units is constructed. The value of comprehensive substitution benefit evaluation index is minimized as the objective function, and the optimization model of backup capacity of power system considering the photovoltaic power generation system replacing thermal power units in backup operation was constructed. The piecewise linear theory is used to linearize the objective function with quadratic characteristics, and the branch-and-bound algorithm is used to solve the nonlinear integer programming problem. Taking the IEEE- 30 system as an example, the calculation results show that the photovoltaic power generation system replaces the thermal power unit in the standby operation, which can reduce the comprehensive substitution benefit and reserve capacity.

Abstract:Reasonable use of the flexible regulation characteristics of distributed power sources and adjustable loads is the key to realize active control of active distribution network, but the randomness and fluctuation of distributed power sources among them affect the reliability of real-time dispatching. To realize real-time optimal dispatching of active distribution network, an optimization strategy for real-time dispatching of active distribution network is proposed based on model prediction control and opportunity constraint. Firstly, the small time scale scheduling system of the active distribution network is analyzed. Based on this, the optimal economic dispatch is used as the optimization target, and the model predictive control combines the system future state sensing with real-time state feedback to perform rolling optimization of real-time dispatch and minimize the influence of distribution network uncertainty. Opportunity constraints are used in the rolling optimization to further reduce the influence of random fluctuations of distributed energy and adjustable loads, thus high reliability and high economy of active distribution network real-time dispatching are realized. Finally, the applicability and superiority of the proposed strategy are verified by a comprehensive operation example.

Abstract:Under the influence of the reform of transmission and distribution price, the profit model and operation mode of power grid enterprises have undergone major changes. It is urgent to transform the operation concept and investment decision of enterprises. The reformed power grid investment demand and investment capacity coordination optimization model provides a direction that can be optimized for power grid investment decision-making.Firstly, the investment demand of the power grid is analyzed, and the power grid investment capacity is devided into distributable profits, financing funds, and depreciation costs, and then a power grid investment capacity calculation model based on the transmission and distribution price reform is built. Then the coordination coefficient of power grid investment capacity and investment demand is calculated, considering multiple constraints, an optimization model of power grid investment demand and investment capacity is established, and particle swarm optimization algorithm is introduced for coordination optimization. Finally, simulation analysis is carried out considering whether the investment demand and investment ability are coordinated, and the corresponding investment management strategy is proposed according to the simulation results. The verification of the example shows that the model can provide a more effective reference for power grid enterprises to formulate a reasonable investment plan.

Abstract:Residential load has become the main component of power peak load due to the characteristic of concentrated consumption time. Meanwhile, with the development of the integrated energy system, demand side response has become an effective way to alleviate the contradiction between supply and demand. Taking the community integrated energy system as the research object, considering the potential of the economy, low carbon and residents’demand side response comprehensively, the fuzzy membership function is used to construct a scheduling model aiming at the optimal satisfaction. An empirical study is carried out in a residential area of a certain region in China. The results show that the profit of service providers is increased, the cost of residents is reduced by 27.50%,and the carbon treatment capacity is reduced by 25.35% , which proves that the proposed model can achieve a win-win situation between the energy supply side and the energy consumption side, and provides support for realizing the dual carbon goal at an early date.

Abstract:CCHP-MG has important application value to improve energy efficiency and achieve the goal of double carbon. At the same time, the complexity and uncertainty of resource aggregation also bring challenges to its operation optimization. Based on this, a two-stage scheduling model of CCHP-MG considering the uncertainty of wind and solar output is constructed. In the day ahead stage, the operation strategy of each equipment of the integrated energy system is optimized with the lowest operation cost as the goal,the scenario method is used to deal with the uncertainty of wind and solar output, and the system operation risk is objectively quantified based on the conditional value at risk method. Within the day, the predicted value of the wind and rain is more accurate, and the output of some equipment is adjusted to stabilize the power deviation of the tie line, so as to ensure the safe and stable operation of the power grid as much as possible while ensuring the economy. Finally, an integrated energy system is taken as an example to verify the effectiveness of the model.

Abstract:In order to promote the application of load demand response technology in the distribution network and improve the efficiency of the distribution network transaction operation, a multiagent transaction strategy of the distribution network considering the load demand response potential is proposed. Firstly, a calculation method for load participation in demand response potential is established based on Minkowsky sum, the distributed active loads are aggregated into generalized loads for unified scheduling. Then,according to the profit model of each transaction entity in the distribution network, the mathematical model of each entity is established, and the two-layer multi-objective optimization model is constructed with the largest overall income of the distribution network and the largest income of each entity as the objective function. Finally, MultiGPO algorithm is used to solve the optimization problem.The results show that the constructed distribution network model can reasonably distribute the benefits of each entity under the premise of the maximum benefit of the distribution network, thereby improve the economy of the distribution network as a whole and a single individual. At the same time, the MultiGPO algorithm is compared with traditional algorithms can obtain better optimization results.

Abstract:Under the background of increasing penetration of new energy in the power grid and the emergence of flexible load as a means of regulation, an appropriate dispatching mode is selected to enable a large number of distributed load resources to participate in the power grid regulation. This mode can help achieve the goals of peak shaving and valley filling and smoothing the load curve. Based on the cooperative control structure of load aggregator model, the load resources including electric vehicle, air conditioning load and energy storage equipment are aggregated, and the day ahead economic scheduling model is established. In the cluster internal control of load aggregator, considering the scheduling potential of equipments, a state queue priority algorithm based on margin index is proposed to realize partial load priority response. Finally, the simulation example shows that the load aggregator participates in the day ahead collaborative dispatching operation plan of the power system, and verifies the feasibility of the optimization method and regulation strategy.

Abstract:The topology of low-voltage distribution network is of great significance to realize the application functions such as line loss analysis, fault diagnosis, power theft early warning and demand response. Aiming at the problem of inaccurate and missing topology of low-voltage distribution network, a topology identification method of low- voltage distribution network based on segmented current characteristics and random forest algorithm is proposed. Firstly,based on the current similarity mechanism, the current characteristic index is proposed, and the current time series is segmented for feature extraction. Secondly, the feature vector set is generated according to the segmented current characteristics, and the topology recognition model based on random forest algorithm is established,which can quickly and effectively identify the relationship between users and transformers. Finally, an example is analyzed by using the measured data of the actual distribution network. The results show that the topology recognition accuracy of this method is 98.02%, the sample time is short, and it can quickly and effectively identify the topology relationship of low-voltage distribution network.

Abstract:Growing with the development of the county micro grid scale, there is a micro network operating expenses cost and distributed renewable energy cannot be given rate at the same time and optimal problem, a day operators spending cost minimum and maximum double objective function of photovoltaic given rate are established, and power balance, power range and other constraints, micro grid optimal operation model are established. The multi- objective particle swarm optimization is introduced to solve the two-objective problem. Finally, taking the predicted data of total electricity load and PV of an industrial park as an example, the results are compared with the optimization results of standard particle swarm optimation under single objective to verify the effectiveness of the proposed model and algorithm.

Abstract:Space station energy system and new power system are important application scenarios for future energy systems in China. In terms of key technologies, the system structures of the two systems tend to be complicated, the capacity levels tend to be large,and the performance requirements tend to be high reliability and high security. At the same time, the two systems have different connotation characteristics, different power types, different application scenarios, different technical and economic priorities. On this basis,the relationship between the two systems are furtherly discussed,from the macro strategy, both are part of the national strategy. From the technical route, the space station energy system is a special, zero carbon emission, miniature new power system. From the perspective of academic research, both have many academic fields worthy of scientific research. From the perspective of future development, they have mutual reference significance in terms of safety and reliability and technical economy.

Abstract:With the rapid development of Internet of Things technology and the new generation of mobile communication technology, the interaction between electric vehicles and distribution systems has expanded from a single time dimension to time-space multi-dimensional coordination, which significantly affects the power supply reliability of the new power distribution system. Based on this background, the cluster management strategy of large- scale electric vehicles is analyzed, the mathematical representation method of the temporal and spatial schedulable characteristics of electric vehicles in the distribution system is revealed, and the reliability of the distribution system that considers the temporal and spatial schedulable characteristics of electric vehicles assessment method is proposed. In order to verify the effectiveness of the proposed method, based on the improved IEEE-RBTS BUS6 main feeder F4 system, corresponding calculation and analysis are carried out on the reliability of the distribution system considering the time-space schedulable characteristics of electric vehicles before and after the connection and under different discharge capacities of electric vehicles. The calculation and analysis reveal the influence of electric vehicle access on the power supply reliability of the distribution network under the new situation, which can provide effective theoretical support for the reliability improvement of the power distribution system under the electric vehicle access.

Abstract:Under the background of the rapid construction and development of the Chinese electricity spot market, the flexibility and economic requirements of spot market for power grid make the traditional power grid planning methods not applicable.The challenges of power grid planning under spot market are analyzed. The economic benefits are represented by social welfare, including generation surplus, power user surplus and blocking surplus, and the benefit/cost index is constructed to represent the economic benefits of power grid planning. By calculating the shadow price of the line which can reflect the extent of the line congestion,sorting it to determine the extent of the blocking, determining the location of the planning and upgrading equipment and upgrading priority of the device, the power grid planning method which is suit able for the starting and mature stage of the spot market and considering the economic benefits of the spot market is put forward. Finally, an example is constructed to show the flow of economic verification method of planning scheme.

Abstract:mechanism according with China National unified electricity market is an important’s energy transition. As the first stage of the national unified electricity market,“two-level declaration and two-level clearing”model of the inter-provincial and intraprovincial spot market has undoubtedly raised the difficulty of market participation. As an intermediate agent, the provincial grid has become an influential research issue in balancing inter-provincial and intra-provincial interests. From the perspective of sending end,a trade decision with the objective of coordinating and balancing the two levels of market transactions is proposed, and an optimization decision model based on two- tier spot markets for outward transmission transactions is constructed in order to quantify the effect inter-provincial spot market has on intra-provincial spot markets, and to support the trading decisions of the sending provinces in the two-level spot market environment.

Abstract:Clustering plays an important role in the big data analysis of power grid customers. With the promulgation of China’s Data Security Law, how to give consideration to data privacy and clustering quality in power customer data clustering analysis has become a difficult point to be solved. The existing k-means clustering method based on differential privacy is difficult to balance data privacy and clustering quality. The method of adding noise to data distance is proposed. By extracting the data distance and adding noise satisfying differential privacy constraint to the distance value, a noise matrix is constructed to realize the privacy protection of the data distance. Furtherly, the kq-means clustering method based on noise matrix is designed, the concept of k nearest neighbor is introduced, and the clustering division strategy is designed. The data records are distributed to the expected intervals of several nearest central points, which reduces the clustering error caused by the accumulation of differential noise in the process of multiple iterations.Our solution can achieve both privacy and clustering accuracy of power grid customer data.

Abstract:In the power grid outage user sensitivity and complaint prediction, the inaccurate prediction results affect the precise service of the power grid company, so a situational awarenessbased grid outage user sensitivity and complaint prediction method is designed. Through the Enterprise Miner workstation module and the Enterprise Guide module in the SAS software, the grid power outage user sensitivity and complaint-related data are collected, including the power outage sensitive user tag data, fault handling data, power outage event data, customer call data, and 95598 work order data. Perform preprocessing on the mining data such as missing data processing, abnormal data processing, and alarm false positive and false negative data processing. Based on situational awareness technology and random forest algorithm, a grid outage user sensitivity and complaint prediction model is constructed to realize user sensitivity to outage and complaint prediction. The method is used to predict the sensitivity and complaints of users about power outages in a power grid in a certain area, and the prediction performance of the method is tested. The test results show that the method has a precision and recall rate higher than 90%, the F-measure data value is high, the AUC area is large, and the data sensitivity is always greater than 97%, indicating that the design method has superior grid outage user sensitivity and complaint prediction performance.

Abstract:With the gradual advancement of the digital transformation of power grid, the power marketing service mode has been continuously improved. In order to solve the problems of single service mode and poor user experience in power marketing service, a power user service method based on cohesion hierarchical cluster ing is proposed. Firstly, the power data and behavior data of powerusers are cross analyzed to obtain the typical data characteristics of power users. Secondly, the agglomerative hierarchical clustering algorithm is used to analyze the power users, evaluate the preference and power consumption trend of power users, and draw a picture of power users. On this basis, different marketing service strategies are formulated for different types of power users to improve the satisfaction of power users. Finally, when the method is applied in a city,the online penetration rate of power users is increased from 38.2%to 69.1%, and the user satisfaction is increased by 41.5%. The results verify the effectiveness of the power user service method.