Research And Application Of Crisscross Optimization Algorithm On Reactive Power Optimization Of Regional Power Grid

In recent years, with the rapid development of the economy as well as power industry, and the expanded scale of the increasing complicated power system, reactive power plays an essential role on the safety,stability and economical operation of the whole power system. Under the constraint of state variables such as voltage and reactive power output, reactive power optimization of the grid reduces active power loss, improves voltage quality and stability by adjusting the adjustable control state quantities like the tap voltage of the motor, the tap position of the on-load voltage regulating device and the reactive compensation capacity etc.Reactive power optimization is a certain problem of the optimization involved multiple constraints, multiple variables, nonlinearity and high dimensionality.It’s of the mixture of the integer and the real,together with incontinuity.On the aim of the main objective function of the least active network loss,this paper proposes the mathematical model of reactive power optimization.At the same time, penalty function is used to deal with the problem of the off-limits of the node voltage and reactive power output.Intelligence algorithms of superior performance like Particle Swarm Optimization(PSO) are widely used in the reactive power optimization. It’s simple to be realized and has high convergence speed in the early stage. However, these algorithms are easy to run into local optimum when dealing with the practical problems such as multiple dimensions and multiple peak values.As a result,they hardly ensure the convergence precision.To overcome it, a new intelligence algorithm named Crisscross Optimization algorithm(CSO) is proposed in this paper.CSO introduces the competition operators to ensure the convergence precision and vertical crossover’s acting on the different dimensions of the same individual particle effectively prevent running into local optimum in the optimization process of some certain dimension. In PSO, under the lead of the globally optimal value, the rate of pre-convergence become faster. Inspired by this, optimization algorithm combined with CSO and PSO come forward in this paper,which owns the ability of Global search without blind search as well as rapid convergence like PSO.In the software platform of matlab, we apply CSO and CSO-PSO to solve the problems of reactive power optimization, we adopt numerical examples of the standard node namely IEEE14,IEEE57,IEEE118. Compared with other algorithms,optimization results show that the two algorithms hardly fall into local optimum, and enhance the stability of convergence.More important, the number of iterations is also reduced. On another hand,optimization results indicate that the more nodes, the advantages of the two algorithms is more obvious.At last,we put these two algorithms into the practical use of regional power grid(including 180 nodes、148 optimization variables),which proves that the proposed methods in dealing with reactive power optimization of power system are of rationality, practicability and maneuverability.