Research On Reactive Power Optimization Of Distribution Network Based On Improved Teaching And Learning Algorithm

Nowadays,the society has paid more and more attention to the energy shortage,environmental pollution and ecological problems.The development of electric power industry has brought serious energy crisis,and adjusting energy structure,reducing the proportion of thermal power,vigorously develop clean and renewable energy generation are the significant way to solve the problem of energy shortage and environmental pollution.The distributed generation which uses clean energy and renewable energy to generate electricity is characterized by small,discrete and flexible etc.,is the generation system that can be directly connected to distribution network or the user side,to some extent,can relieve the pressure and environment pollution,cut down power transmission loss,and enhance the reliability of power supply.The distributed generation being connected to grid can bring great influence to the voltage quality and voltage regulation mode of grid,and the power system reactive power planning and reactive power optimization are the significant control measures.This paper studies the reactive power optimization problem of distribution network with distributed generetion.(1)The connecting way of different types of distributed generation are also different,so the classification processing is carried out in the distribution network power flow calculation.Considering the characteristics of distribution network,the concept and mutual relationship of the joint-branch matrix and the road matrix are introduced in,and a three-phase power flow calculation algorithm based on the road matrix for the distribution network is adopted.The paper chose the minimization of the active network loss as the optimization objective and build the mathematical model of reactive power optimization problem with the node voltage penalty factor,meanwhile,chose the minimization of the active network loss and voltage deviation as multi-objective optimization function,and determine the control variables,state variables,and variable constraints.(2)The paper adpot teaching-learning based optimization(TLBO)which rise in recent years,that is simple and has better convergence ability and quick convergence rate,more importantly,it doesn't need the control parameters that exist in other intelligence algorithms.And the basic concepts and concrete realization steps of TLBO are introduced in detail.For the shortcomings of dealing with the high dimensional peak and more complex optimization problems,the elitist strategy has been introduced in TLBO to further strengthen the searching ability and improve stability of the algorithm,and the elitist TLBO is proposed.Finally,the basic principle of the standard PSO algorithm with inertial weight is presented.TLBO,elitist TLBO and PSO algorithm are applied to single objective reactive power optimization problem of distribution network,and the concrete steps of ETLBO for solving reactive power optimization problem have been analyzed.With the simulation of 33-nodes example system in distribution network and the comparison of calculation results of three algorithms,the results show that the ETLBO can effectively solve that TLBO fall into local optimum in early time,also has higher convergence and robustness and better optimization results.(3)For multi-objective reactive power optimization model,the paper introduce Pareto optimal solution to deal with multi-objective optimization problem.Based on the Pareto optimal and the crowding distance,by applying the non-dominated relation to construct the non-dominated solution,the computational complexity of the multi-objective problem has been reduced.To improve the distribution of the solutions by the crowding distance sorting,and introduce in elitist to enrich non-dominated solutions.Finally,the optimal solutions are obtained based on the crowding distance sorting and clipping of non-dominated solutions,so we got the improved multi-objective TLBO.The IEEE 33-node system is adopted to test the algorithm,the results show that the feasibility and effectiveness of the improved algorithm in multi-objective reactive power optimization.The paper provides a new method and some ideas to solve the reactive power optimization problem of the distribution network.