A Renewable DG Planning Method for Active Distribution Network Based on Improved PSO

Abstract

The invention relates to a renewable DG planning method for active distribution network based on improved PSO, which performs mathematical modeling on the uncertainty of load and renewable DG output; determines the optimal installed capacity according to the total amount of renewable resources; calculates through the power flow Determine the optimal location and capacity of renewable DG connected to the active distribution network; establish the upper layer model with the goal of economy, and build the lower layer model with the goal of minimizing network loss; combine the PSO algorithm and genetic algorithm to solve the upper model, and use the initial information Pass to the lower model; solve the lower model and return the result to the upper model; continue to solve the upper model until the requirements are met. Compared with the prior art, the present invention first determines the optimal location and capacity of the renewable DG connected to the active distribution network, then establishes a two-layer programming model of the active distribution network, and uses the improved PSO algorithm combined with the tracking center trajectory interior point method The bi-level programming model is solved to obtain the optimal access location and capacity of renewable DG to the active distribution network.

Description

technical field [0001] The invention relates to the field of distributed power supply planning in electric power systems, in particular to an improved PSO-based renewable DG planning method for active distribution networks. Background technique [0002] Energy is an indispensable part of human survival and social development. With the continuous growth of power demand, the deepening of traditional energy shortages and the increasingly prominent environmental problems, distributed generation (DG, Distributed Generation) In particular, the development of renewable energy generation technologies has received broad support. Distributed power generation has many advantages such as high energy utilization efficiency, cleanness and environmental protection, and flexible installation locations. It can effectively solve many potential problems such as high cost and difficult operation in the current power grid. Active distribution network (Active Distribution Network, ADN) is an eff...

AI Technical Summary

Problems solved by technology

However, due to the fluctuation of the output power of renewable DG, there is currently no suitable model or method that can fully describe the uncertain changes in the output power of renewable DG. Simply treating renewable DG as a distributed power source with stable output will lead to Ignore its specific impact on the system, resulting in a large difference from the actual grid operation

The demand for renewable DG to participate in the dispatching operation of the distribution network and the intermittent and uncertain output of renewable DG have brought great challenges to the coordinated control of renewable DG in active distribution networks.

[0004] In addition, when solving the renewable DG planning of the active distribution network, the active distribution network planning model is generally described by establishing an objective function and constraints, and the use of mathematical methods to solve the objective function will lead to excessive calculation and may even lead to inaccurate Convergence; when using a single intelligent algorithm to solve the objective function, such as using Particle Swarm Optimization (PSO), it is very likely to fall into the problem of local optimum, and the convergence speed and convergence are poor

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