Reactive Power Optimization Based On Niching Particle Swarm Optimization Algorithm In Distribution Network

Reactive power compensation and reactive power balance in thepower system is one of the basic conditions to ensure the voltage quality.It plays an important role in guaranteeing the power system’s safe, stableand economy operation. In this respect, do reactive power planning on thegrid, arrange the reactive power reasonably, and select the appropriateoptimization objective function are great of significance for grid securityand stability.In this thesis, it introduces the mathematical model of the commoncomponents of the power system firstly. And then, the impacts of voltageloss, active power, loss power factor which is caused by the reactivepower will be described to illustrate the importance of reactive powercompensation. After that, there is a brief description of the conventionalpower flow calculation method named forward and backwardextrapolation. At the end, a mathematical model in the distributionnetwork will be established. Its objective function is designed to be thecost of active power loss of the system and the invest of reactive power compensation equipment, in which the node voltages beyond limited andthe generator reactive power output beyond limited are considered in theway of penalty function.In order to optimize the model, a new method called TopologicalRing Niche Local-best Particle Swarm Optimization (TRNLPSO) will beproposed. In the algorithm, a topological ring will be added into thelocal-best PSO to control the velocity of the particles. Then severaladjacent particles are selected into the topological ring to form localparticle group. As a result, the global optimal is replaced by local optimal.In that way, it can avoid being dropped in the local-best caused by theexcessive velocity search in the local space more exactly. So it is moreeffective in searching the global optimal solution than that of the PSOmethod.Additionally, in order to avoid repeating the search process, the lawof the golden section and chaotic traversal algorithm will be added intoTRNLPSO, which is called Gold Chaotic Niching Particle SwarmOptimization (GCNPSO). By the property of Chaos traversal algorithm,particles can avoid repeated search in the solution space. Finally, the roleof gold criterion will be added. So the original particle swarm is dividedinto Chaos particle and standard particle, which reduces the redundancycomputation.At the end, a software system of reactive power planning optimization for distribution network will be displayed. In the software system, GCNPSOis adopted as the core algorithm and the mathematical model, which isdesigned to be the cost of active power loss and invest of reactive powercompensation equipment, is treated as the core model. The system is ableto quickly realize the optimization calculation, parameter configuration,data storage and other functions. System programs follow the designprinciples of modular. So it is easy to be maintained. System is stable andreliable and can improve the quality of the voltage of the power systemeffectively. Meanwhile it can reduce system losses. The reactiveequipment can be used in efficient way, and it provides an importantguarantee for the power system in security and stability. Therefore, thesoft system would have great prospects in application.