In the future, high proportion of renewable energy will be connected to the power system, wind and photovoltaic are developing in a high proportion, and flexible resources such as energy storage and interruptible load play an important role in peak load regulation. In this paper, a planning method for wind power and photovoltaic absorption considering flexible resources is proposed. Under the limitation of power development capacity, combining with the experience of experts, we give priority to the development of peak-regulating power supply, energy storage, interruptible load and other flexible resources, maximize the adjustable capacity of the system, and consider reasonable power abandoning space to improve the capacity of accepting new energy. On the balance method, the period of balance check is selected based on the regional load, wind and photovoltaic characteristics. Based on the historical data, the wind and photovoltaic output rate in the peak shaving equilibrium period is judged, and the wind and photovoltaic abandonment rate is calculated respectively by integrating the typical daily power abandonment. This method considers the adequacy of system capacity and the capacity of new energy absorption comprehensively, and constructs a comprehensive planning method of wind and solar energy absorption based on the balance method. It also considers certain power abandonment to promote the development of new energy. Finally, an example of 2025 and 2030 power supply planning for a provincial power grid in Northeast China is given to verify the effectiveness of the above model and algorithm.

Since the randomness and correlation of PV output and load have an important impact on the accurate evaluation of power system operating characteristics, this paper studies the probabilistic power flow of power system considering the randomness and correlation between PV output and load. Firstly, based on the distribution characteristics of PV output and load, a mathematical model of nonparametric probability distribution is proposed. Secondly, Kendall correlation coefficient and least square Euclidean distance are used as correlation measure and fitting index, which is constructed by Copula theory. Taking into account the joint probability distribution model of PV output and load correlation, a probabilistic power flow calculation method that can accurately consider the correlation between the two is proposed, and the influence of PV output and load correlation on the operating characteristics of the system is analyzed. Finally, a simulation is carried out with the measured data of a PV power plant of China and the IEEE 34 node power distribution system. The simulation results show that the proposed probability distribution model can more accurately reflect the randomness and volatility of PV output and load, and verify the accuracy and effectiveness of the probabilistic power flow method which takes the correlation of PV output and load into consideration.

FDNE (frequency dependent network equivalent) is widely applied on external system equivalent in electromagnetic transient simulation, which takes responses of electrical networks in a specific frequency band into consideration. Since FDNE is linear and time invariant, which cannot be directly used on external systems including asynchronous wind turbine. In order to solve this problem, this paper neglects electromagnetic transient process in stator and rotor windings of a wind turbine, representing which with a reduced model composed of passive and linear components with a current source. A case study is given to verify the effectiveness of the reduced model, and the accuracy of FDNE is verified through responses in both frequency and time domain. This paper provides a practicable solution to build a FDNE for external system with asynchronous wind turbine generator, reducing whose port number compared to existing method based on removing wind turbine from external systems, which helps to improve the simulation efficiency.

Predictive gross error management mode has been widely used in large-scale grid-connected wind farms. However, this mode can't stimulate farms to improve wind power quality and enhance schedule execution on the premise of guaranteeing the revenue of power generation, also can't help the grid to improve wind power absorption on the basis of reducing the burden of regulation or effectively controlling the marginal cost of regulation. From the subject status equality of wind power market, this paper explored how to enhance the commercial credit of schedule or contract through improving wind power quality for competing higher price and revenue, and proposed a new stepped pricing and penalizing mechanism based on the wind power quality. The mechanism evaluates wind power grades based on the trend curve characteristics, deviation tolerance, and credibility and deviation penalty of power generation schedules declared by wind power farms. For different grades of schedules, the corresponding stepped prices and penalties are adopted. On this basis, an optimal declaring model of daily power generation schedule of wind farm was proposed for maximizing its revenue. Results of case analysis show that the proposed new mechanism can more effectively stimulate wind farms to sell high-quality wind power, and hence to reduce the regulation burden of grid and create a win-win market environment for farms and grids.

With the rapid development of renewable energy represented by wind power generation and photovoltaic power generation, the installed capacity of renewable energy in the power system is increasing day by day.When the installed capacity of wind and photovoltaic power account is for a small proportion of the total power supply installed in the system, wind and photovoltaic generation can be fully accepted by the power system. However, when the installed capacity of wind and photovoltaic power reaches a certain scale, the influence of intermittentity and fluctuation of their generation on power system can not be neglected. It is necessary to study the capacity of renewable energy integration. Based on the historical load and renewable energy output of a region, load and the renewable energy generation output curves were predicted in this paper. Based on the grid aggregation model, the rationality of power planning in this area was evaluated. On the basis of the evaluation, the limits of the accommodation capacity of renewable energy in this region were studied.

Analysis of non-water RES(renewable energy sources) absorption will contribute to achieve the index quota of high proportion of renewable energy generation in all regions of China in 2020. Firstly, considering various restrictive factors on non-water RES power generation: wind and solar resources and their spatial and temporal distributions, available land resources, regional economic development level, spatial and temporal distribution characteristics of regional load, capacity of power grid equipment and constraints on safe operation, etc. Secondly, with various restrictive factors as the boundary conditions, a bottom-up theoretical analysis is carried out on the acceptable non-water RES capacity and the non-water RES amount of electricity that can be absorbed in a specific region (voltage level below 220/110 kV). Finally, whether the top-down indicators allocated to each region by the State Energy Administration can be fully absorbed and the regions not satisfied need to be coordinated and allocated. In view of the above analysis, this paper discusses the location and capacity determination model of non-water RES, the measures to increase installed capacity, and the scheduling optimization model 24 hours before the day of power grid access to non-water RES, and discusses the solving method of this mathematical problem.

The research on power system planning, scheduling and control often relies on the power data of each power station supply in the system. When the power system is actually running, it is difficult for each plant station to operate under a unified time base, resulting in time series of multi-source output power data do not match. Aiming at the problem of multi-source data point mismatch, this paper proposes a multi-source data fusion method based on multi-source data time point matching. Firstly, the reference time series is determined, and the expressions of each power output power time series relative to the reference time series are established. Secondly, determine the time series common domain of each power output, and construct a multi-source output power point matching model. finally, correct the time series of each power output according to the model solution result, and fuse each power output data. The example analysis shows that the method can accurately integrate the power data of power system, which is of great significance for the research of power system planning, scheduling and control.