结合粒子群算法和遗传算法求解机组投用问题

2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA) Pub Date : 2014-12-01 DOI:10.1109/STA.2014.7086752

Sahbi Marrouchi, S. Chebbi

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引用次数: 2

摘要

解决单元承诺问题(Unit Commitment problem, UCP)是对生产单元的作业组合进行优化，确定各生产单元的适当作业计划，以满足从一天到一个月不等的预期消耗。并对每个生产单元进行约束，使问题变得复杂、组合、非线性。本文提出了一种基于粒子群优化方法和遗传算法相结合的新策略，应用于一个包含5个生产单元的IEEE电气网络14总线，解决一侧的单元承诺问题，另一侧的优化组合调度使总生产成本最小化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Combined use of Particle Swarm Optimization and genetic algorithm methods to solve the Unit Commitment problem

Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination of the Particle Swarm Optimization method and the genetic algorithm applied to an IEEE electrical network 14 buses containing 5 production units to solve the Unit Commitment problem in one side and to find an optimized combination scheduling in the other side leading to minimize the total production cost.

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2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

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