Reactive power dispatch considering voltage stability with seeker optimization algorithm

The Approach of Genetic Algorithms Application on Reactive Power Optimization of Electric Power Systems

“…The reactive power optimization of power system up to now, many domestic and foreign experts and scholars carried out a lot of research work, a series of effective algorithms and mathematical model is proposed to solve the reactive power optimization problem, made a lot of achievements. Especially in recent decades, with the development of modern artificial intelligence algorithms and the rapid development of computer science and technology, people will use these advanced theory to solve the problem of reactive power optimization, provides a new theoretical method for the research and analysis of reactive power optimization [5][6]. So far, the solution methods of reactive power optimization can be divided into two categories: conventional optimization algorithm and modern artificial intelligence algorithm.…”

Two Population-Based Heuristic Search Algorithms and Their Applications

“…Then, the real-value position is changed into a mixed-variable vector which is used to calculate the objective function value by equation (23) based on NewtonRaphson power flow analysis [45]. The reactive power optimization based on SOA can be described as follows [17].…”

“…The active power loss minimization in the transmission network can be defined as follows [16,17,44]: difference between bus i and j, Gi P is the injected active power at bus i, Di P is the demanded active power at bus i, i V is the voltage at bus i, ij G is the transfer conductance between bus i and j, ij B is the transfer susceptance between bus i and j, Gi Q is the injected reactive power at bus i, Di Q is the demanded reactive power at bus , E N is the set of numbers of network branches, PQ N is the set of numbers of PQ buses, B N is the set of numbers of total buses, i N is the set of numbers of buses adjacent to bus i (including bus i), 0 N is the set of numbers of total buses excluding slack bus, C N is the set of numbers of possible reactive power source installation buses, G N is the set of numbers of generator buses, T N is the set of numbers of transformer branches, l S is the power flow in branch l, the superscripts "min" and "max" in equation (17) denote the corresponding lower and upper limits, respectively.…”

“…In this chapter, two recently proposed swarm intelligence algorithms are introduced. They are seeker optimization algorithm (SOA) [3,[14][15][16][17][18][19] and stochastic focusing search (SFS) [20,21], respectively.…”

Research of Distribution Network Reactive Power Optimization Based on Improved Cloud Particle Swarm Optimization BP Neural Network

“…Reactive power optimization is a constraint, large-scale and nonlinear combinatorial optimization problem and is a reactive regulatory method which meets all the constraint condition and obtains one or more optimization performance index of the system through the optimization of some control variables, when the structure parameters of the power system and the load are given [1]- [3]. Conventional optimization methods are mainly composed of classical algorithm and artificial intelligence methods.…”