Virtual-power-plant day-ahead-optimization scheduling method of considering demand response

Abstract

The invention discloses a virtual-power-plant day-ahead-optimization scheduling method of considering demand response. The method includes the following steps: 1) estimating a probability density parameter of renewable distributed power supply output according to historical information; 2) using income change quantity before and after the demand response of a virtual power plant to calculate response costs of the two types of demand response; and 3) using opportunity constraints in a form of probability to describe uncertainty of renewable distributed power supply and the demand response, using virtual-power-plant income maximization as a goal to establish an optimization scheduling model based on opportunity constraint conditions, and using a particle swarm optimization algorithm based ona microbial behavior mechanism for solving. Therefore, the distributed power supply is integrated in a form of the virtual power plant to access a power network, geographical location limitation of amicro power network can be broken, and coordinated scheduling of the distributed power supply of different regions, different types and different capacities can be realized; and the particle swarm optimization algorithm based on a microbial symbiosis mechanism is adopted to solve the optimization model, and global convergence performance and convergence speed of the algorithm are significantly improved.

Description

technical field [0001] The invention belongs to the field of smart grids, and in particular relates to a day-ahead optimization scheduling method of a virtual power plant considering demand response. Background technique [0002] Nowadays, distributed power generation has received extensive attention because of its good environmental protection, reliability, flexibility and other characteristics, and the access of distributed power generation in the distribution network is increasing day by day. However, while distributed power generation has the above advantages, it also needs to face shortcomings such as small capacity, large quantity, scattered access locations, and uncertainty in power generation. The access of a large number of distributed power sources brings new challenges. At this stage, distributed power is usually connected to the distribution network in the form of a micro-grid to achieve effective management of distributed power output, and the micro-grid will b...

AI Technical Summary

Problems solved by technology

On the one hand, because the user load on the demand side will be affected by many uncertain factors such as production and life, emergencies, etc., the demand side response will show uncertainty. On the other hand, the output of renewable distributed power in distributed power Affected by environmental factors, there will also be randomness and uncertainty in output

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