Application Of Particle Swarm Algorithm In Grid Planning

The electric power industry provide the basic power for industry and the nationaleconomy and other departments. Along with the electricity and the electricity industry’s rapiddevelopment, the development of electric power industry will have a profound impact. In theconstruction of the transmission grid. Correct and reasonable network planning will be greateconomic benefits and social benefits. On the contrary, Power grid planning unscientificcould generate more pre investment and post electric greater energy loss. Therefore, Do agood job in the grid planning. The result will directly affect the safety and reliability of gridoperation.With the development of the transmission grid, which is becoming more and morelarge-scale, more and more constraints, its planning has become more complex. Combinationwith conventional mathematical optimization method is not only computationally intensive,and inefficient. And the use of modern heuristic algorithm to solve this problem provides anew research direction. PSO determines the global optimal by following the current search tothe optimum value, with high accuracy, fast convergence and so on. To solve the transmissionnetwork planning constraints and discrete variables with nonlinear integer programmingproblem especially suitable.This paper studies the mathematical model of the various transmission network planning.Using the static planning model with minimal loss of investment and network costs as theobjective function, and the DC power flow equation as the constraints. The article also studiesthe particle swarm algorithm and its mathematical model. Using the linear differentialequations to change the mathematical model of standard PSO algorithm. Making it become alocation update only updates the formula. And compared to the standard particle swarmoptimization, the model parameters decreased. Obtained by a numerical example. The newalgorithm is a higher dimension or larger populations. Evolutionary particle swarm algorithmhas higher global search capability in the early, late local search capability with higher. Theevolutionary algorithm is applied to the transmission network planning. By IEEE-6system tocalculate and analyze numerical examples, thus proving the feasibility of the algorithm intransmission planning applications.