The Design of an Efficient Distributed Collaborative Scheduling Method and the Optimal Planning Strategy for Providing Photovoltaic Access Capacity

The output power of distributed photovoltaic power generation has strong randomness due to the influence of the natural environment. With the increase of its permeability in the distribution network, it is bound to cause complex random changes in the system power flow, leading to the voltage limit of the system nodes. This article provides an opportunity constraint model based on voltage balance, harmonic distortion limitation and protection coordination, the model considers a series of equation constraints, inequality constraints and opportunity constraints, can maximize photovoltaic access capacity, and can be solved by particle swarm optimization algorithms. After modeling, Latin hypercube sampling is used to solve the probability density function of node voltage, particle swarm optimization algorithm is used to optimize the model, the photovoltaic penetration rate of the distribution network is maximized, and finally an optimal planning strategy is established to maximize the photovoltaic access capacity, solve the power grid loss and resource waste caused by small probability events, and then improve the operation efficiency of photovoltaic access to the power grid, improve resource utilization and the economic benefits of the power grid.