Source-grid collaborated multi-objective optimization based on virtual power plant

TL;DR: In this paper , a multi-objective optimization method is presented, which takes minimizing system voltage deviation, network loss and auxiliary service cost as objectives, and the Pareto solution set is solved by the improved particle swarm optimization algorithm.

Abstract: The high proportion of renewable distributed power in the distribution network has a series of impacts on the safety and economy of the power grid. Based on the output characteristics and cost characteristics of distributed energy, this paper proposes the evaluation model of the aggregated output range of VPP and the quotation model of VPP. An optimization method is proposed to encourage distributed energy to participate in voltage regulation auxiliary services. In this paper, a multi-objective optimization method is presented, which takes minimizing system voltage deviation, network loss and auxiliary service cost as objectives. The Pareto solution set is solved by the improved particle swarm optimization algorithm. Taking an area with a high proportion of distributed energy as an example, the effectiveness of the model and algorithm is verified, the relationship between optimization objectives is discussed, and flexible optimization options are provided.