Studies On Multi Time Scale Risk Assessment Of Power Grid And Acceleration Algorithm Considering Wind Power Integration

With the energy crisis and environmental problems becoming increasingly severe in recent years, renewable energy has attracted more attention than before.As one of the mature technologies for renewable energy power generation, wind farms have been widely established globally.Wind resource is abundant in C hina, but it is restricted by geographical and meteorological conditions.In China,we prefer centralized large-scale wind farms.Wind energy has the character of randomness, which is mainly showned as the fluctuation of wind power output.After the wind power integration, the operational risk of the power grid is greatly affected.There were a lot of accidents in China, which caused the trip-off of wind turbines and relay protection device malfunction. All these problems could threaten the safe operation of the power grid.The classical power grid static stability assessment method can calculate the fluctuation of the power load, the fault of generators and transmission lines.Then it can illustrate the level of power grid operational risk.However, these results are evaluations which are past-oriented and static.In short time, the output of the wind farm may have a large range of fluctuations, and at different time scales, the output of the wind farm will show different characteristics.The classical risk assessment method of power grid can not reflect the above conditions timely and accurately.Aiming at this problem, this paper researches the combination of wind farm output forecasting and power grid risk assessment.The main topics of this paper are multi-time scale risk assessment of power grid and its acceleration algorithm considering wind power integration.On the topic of multi-time scale risk assessment of power grid considering wind power integration, in order to study the impact on power grid operation risk of wind farm output on different time scale in future, this paper will focus on the following works. Firstly, based on the classical power grid static stability analysis theory, wind power output prediction technology, and The theory and method of future asset loss analysis model(Va R) in the field of financial risk measurement, three different types of risk assessment indexes are designed.The first type of indexes reflect the level of power grid load reduction. And the second type of indexes illustrate the overload condition of the bus voltage and the power flow of transmission line. Then the third type of indexes can show the influence of wind power integration in multi- time scale in future. In wind farm output prediction, the time series forecasting model is used to test and forecast the power data of a wind farm.Meanwhile,the code of this program is designed and comp iled on MATLAB software.The results of this work can not only give the static data of the future power grid risk assessment, but also can reflect the dynamic change process of the overall risk level of the power grid based on wind power forecast data.And t hen, after the wind farm is connected to the power grid, the operational control personnel can take preventive measures in advance to provide the reference for the possible fluctuation of wind farm in different time scales.On the topic of accelerating algorithm, the work of this paper is mainly focused on two aspects: hardware acceleration algorithm and software acceleration algorithm.Firstly, based on the multi-core CPU computing platform, this paper discusses the effects of different tasks allocation strategy and communication mode.Then, the graphics processor unit(GPU) is introduced to accelerate the computational efficiency. And different workload distribution strategies are designed to optimize the integrated heterogeneous hardware accelerated algorithm.Secondly,in the aspect of software acceleration, the study is focused on the most time-consuming part of the power grid risk assessment method, which is power flow calculation.New improved sampling method is designed to reduce the number of operating states sampling, which is combined with the Latin hypercube sampling method and the average scattered sampling method.At the same time, the heuristic approach to local load shedding scheme method is used to accelerate the calculation process of the first type of evaluation indexes.Finally, the software acceleration algorithm is combined with the hardware acceleration algorithm to accelerate the program. Case study shows that the proposed acceleration algorithm can guarantee the accuracy of the results and shorten the calculation time.This work is a useful exploration for the on- line application of power grid risk assessment system.