Studies On Finite Control For Large-Scale Wind Power Ramping

As the global energy interconnection requires the energy consumption to turn to electricity and green, the renewable energy integration, such as wind power, is becoming more and more important. As a mature renewable energy integration technology, wind power generation develops rapidly in recent years. With the increasing penetration, it becomes an indispensable power supply to power grid. On one hand, wind power can bring clean electricity to power grid. On the other hand, due to the uncertainty and fluctuation, it brings significant challenges to the operation and security of power grid. In China, large-scale wind power integrated into power grid improves the long distance trans-regional power transfer proportion. However, it may lead to serious risks of wind power ramping events. Wind power ramping events will lead to a large power unbalance in a short time interval. In some extreme circumstances, wind power ramping events may lead to serious power outage, which impacts the operation of power grid. In order to integrate more wind power, the integration capacities of traditional units are limited. Once the wind power ramping events occur, it will bring great challenges to the operation of power system. In order to reduce the adverse influences on the power grid, reduce the regulation burden of traditional units and improve the control performance of wind power generation, it is important to study the large-scale wind power finite control strategy.Based on the hierarchical coordination and competition, centralized dispatch, regional competition and multi-source coordination control are launched in this paper, which form the key components of large-scale wind power finite control method. Firstly, for the centralized dispatch, a wind power ramping finite control strategy based on unit classification is proposed. Secondly, for the regional competition, the competitive game theory is introduced and the competitive game mechanism is presented. Single time interval Nash equilibrium condition is derived by payment matrix to set the proposed contribution indexes of wind farms, which makes wind farms compete for the regulation schedule of virtual power plants.Then, a wind farm cluster coordination control strategy using game theory is presented. On the basis of the contribution indexes of wind farms, the regulation profit function is proposed and a multiple time interval Nash equilibrium is derived, which makes wind farms respond to regulation schedule of wind farms cluster. Thirdly, for multi-source coordination, a wind-photovoltaic-storage hybrid system coordinated optimal control strategy is put forward. Main contributions and innovations are described as follows:1) A wind power ramping finite control strategy based on unit classification is proposed. A framework of finite control method to deal with highly-concentrated wind generation ramping events is presented, which can be classified into preventive control stage, ramping control stage and restorative control stage. The preventive control stage aims to optimize the schedule of wind farm cluster and provides new wind power reserve; the ramping control stage aims to coordinate different types of wind turbines and improve the ramping characteristics; the restrorative control stage aims to restore the outputs of wind farms in order. A unit classification method based on extreme weather conditions and controllability of wind generators is put forward, which divides wind generators into six types. In the ramping control stage, a control priority of wind generators is designed based on unit classification. Then the regulation schedule for different types of wind generators is distributed in order to fully utilize their control potential. In order to encourage wind farm with good control performance to take part in ramping control method, the wind farm controllable coefficient and uncontrollable coefficient is put forward based on the proportion of different types of wind generators. Then according to the regulation schedule for different types of wind generators, the wind farm controllable coefficient and uncontrollable coefficient, the regulation schedule for wind farms is given. The simulation verifies the effectiveness of the proposed strategy.2) A novel wind power ramping control strategy based on competitive game theory is proposed to improve the ramping characteristics. Firstly, the impacts of wind power uncertainty on active power control are analyzed.The advantages and problems of coordination control are discussed, in which the key problem of the coordination control is how to distribute profits to each wind farm to encourage them to respond. Then, the competitive game theory is introduced and the competitive game mechanism is presented. Wind farms compete for the regulation schedule of virtual power plants or wind farm cluster. Considering power regulation amounts of wind farms and the ability to maintain power outputs, a contribution index is proposed to evaluate the contribution of wind farms and to distribute profits reasonably in the competitive coordination process among wind farms. The detailed derivation of Nash equilibrium is presented based on payoff matrix to set the contribution index, which makes the effective regulation strategy the Nash equilibrium. In the end, wind farms will respond to the regulation schedule plan of virtual power plants and reduce the control errors of virtual power plants.3) A coordination strategy based on the game theory is proposed for the regulation of a wind farm cluster (WFC). On the basis of the contribution index of wind farms, a regulation profit function is put forward in order to distribute the profit among wind farms. Firstly, the total schedule of wind farm is divided into two types: the base schedule and regulation schedule. The wind farm bids for the base schedule of wind farm and the generation profit is calculated based on the fulfillment of the base schedule. When the base schedule of wind farm is fulfilled, the regulation schedule of wind farm is obtained by the competition in the regulation schedule of the WFC.The regulation profit is calculated based on the regulation schedule in the competition process. Finally, the Nash equilibrium is derived to ensure that wind farms are willing to respond to the regulation schedule of the wind farm cluster by setting proper parameters of the regulation profit function. The simulation verifies the effectiveness of the proposed strategy.4) A wind-photovoltaic-storage hybrid system coordinated optimal control strategy is presented, which consists of online rolling optimization and active power real-time control. The aim of online rolling optimization module is to minimize the average power deviation and charge-discharge times of battery energy station and maximize the residual capacity of battery energy station in the end of optimization through NSGA-Ⅱ algorithm. Active power real-time control part consists of wind/photovoltaic trimming scheduling power module and battery energy station real-time control module. The aim of wind/photovoltaic trimming scheduling power module is to balance the excess scheduling plan based on real-time wind speed and illumination intensity. Dynamic power output limit is given in battery energy station real-time control module to improve its ability to deal with wind/photovoltaic ramping.