| 摘要: |
| 将模糊集理论应用于暂态稳定约束最优潮流问题，结合电力系统实际特性，对传统暂态稳定约束最优潮流模型进行改进，将功角约束、电压约束及目标函数模糊化处理，采用最大最小算子建立了以求解满意度最大化的暂态稳定约束最优潮流模糊新模型。构建了适于大规模非线性优化问题的协同进化粒子群算法，用于TSCOPF模糊优化问题的求解。为提高算法求解效率，结合模型特点采用提前终止暂态稳定仿真的加速策略。并利用Matlab并行工具箱对算法进行主从并行化改造，显著提高了算法运行效率。最后利用新英格兰10机系统仿真测试，证明了方法有效可行。 |
| 关键词: 电力系统 最优潮流 暂态稳定 模糊集理论 协同进化粒子群算法 并行计算 |
| DOI：10.7667/PSPC160754 |
| 投稿时间：2016-05-25修订日期：2016-08-25 |
| 基金项目: |
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| Optimal power flow algorithm with transient stability constraints in power system |
| LU Jinling,ZHANG Jin |
| (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China) |
| Abstract: |
| By applying fuzzy set theory to optimal power flow with transient stability constraints and considering the practical features of power system, the traditional transient stability constrained optimal power flow model is modified, the rotor angles constraint, voltage constraint and the objective function are fuzzily processed, and the TSCOPF fuzzy model is established by max-min methods. Besides, a collaborative evolutionary particle swarm optimization algorithm which is suitable for large-scale nonlinear optimization problem is established to solve the transient stability constrained optimal power flow. In order to enhance the efficiency of the optimization algorithm, considering the model’s characteristics, a transient stability simulation early terminated strategy and a master-slave parallel technology are applied to the algorithm, and the algorithm is parallel processed using MATLAB toolbox. The test results on the New England 10-machine system demonstrate the proposed method is effective and feasible. |
| Key words: power system optimal power flow transient stability fuzzy set theory cooperative coevolutionary PSO algorithm parallel computing |
