CAJ | 학술논문

针对电力系统经济负荷分配（ economic load dispatch ，ELD）这一典型的非凸、非线性的多约束优化问题，提出一种自适应混沌粒子群算法（self adaptive chaotic particle swarm optimization， SACPSO）。在混沌粒子群算法（ CPSO）的基础上，先利用引入变异算子和社会因子的粒子群算法进行全局搜索，再对搜索得到的先验解进行基于Tent映射的混沌细搜索（ CLS），并将逆映射回的决策变量和全局最优粒子的线性组合作为CLS的搜索结果输出。通过6机组、15机组电力系统的仿真，验证了该算法的有效性。
침대전력계통경제부하분배（ economic load dispatch ，ELD）저일전형적비철、비선성적다약속우화문제，제출일충자괄응혼돈입자군산법（self adaptive chaotic particle swarm optimization， SACPSO）。재혼돈입자군산법（ CPSO）적기출상，선이용인입변이산자화사회인자적입자군산법진행전국수색，재대수색득도적선험해진행기우Tent영사적혼돈세수색（ CLS），병장역영사회적결책변량화전국최우입자적선성조합작위CLS적수색결과수출。통과6궤조、15궤조전력계통적방진，험증료해산법적유효성。
A self adaptive chaotic particle swarm optimization ( SACPSO) algorithm was presented on the basis of economic load dispatch , which is of a problem of non-convex , nonlinear and complex constrained .Based on the chaot-ic particle swarm optimization (CPSO), a global search made by the basic particle swarm optimization (PSO) which introduced mutation operator and social factor was not stopped until premature happened , then the optimal solutions of global search were used as initial population of chaotic local search (CLS) with Tent map.A linear combination of the decision variable returned by inverse mapping and the best particle of population was output as CLS ’ s results.In the end, the effectiveness of the new algorithm was verified by the system simulations of 6 and 15 units.