| 引用本文: | 于青,刘刚,刘自发,刘幸.基于量子微分进化算法的分布式电源多目标优化规划[J].电力系统保护与控制,2013,41(14):66-72.[点击复制] |
| YU Qing,LIU Gang,LIU Zi-fa,LIU Xing.Multi-objective optimal planning of distributed generation based on quantum differential evolution algorithm[J].Power System Protection and Control,2013,41(14):66-72[点击复制] |
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| 摘要: |
| 为了克服再生能源的间歇性、随机性导致的分布式电源优化结果不够准确，提出了一种基于概率特性的电源-负荷综合模型，将分布式电源的随机出力问题转化成确定性问题。考虑分布式电源对配网的影响，建立了包含建设运行费用、网络损耗、可靠性费用和环境因素的多目标优化模型。提出采用量子微分进化算法对分布式电源接入配网进行优化配置，该算法采用量子的概率表达特性和叠加态特性，潜在地提高了算法的寻优效率，同时采用变异和交叉操作，保持了良好的种群多样性。通过对算例的分析，表明所提出的模型和算法合理、可行。 |
| 关键词: 分布式电源 概率模型 环境因素 多目标优化 量子微分进化算法 |
| DOI：10.7667/j.issn.1674-3415.2013.14.011 |
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| 基金项目: |
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| Multi-objective optimal planning of distributed generation based on quantum differential evolution algorithm |
| YU Qing1,LIU Gang2,LIU Zi-fa2,LIU Xing3 |
| () |
| Abstract: |
| The intermittent of DG makes it difficult to predict power output, consequently the optimized result will be inaccurate. This paper proposes a probabilistic generation-load model to convert the problem of random output into an issue of certainty. Meanwhile, considering the effect of DG on distribution network, this paper establishes a multi-objective model, which considers the construction and operation fees, network loss, reliability and environmental factor. A quantum differential evolution optimization (QDE) algorithm is put forward to determine the optimal site and capacity of DG in the network. The algorithm takes advantage of its probability expression and superposition state, which potentially improves the searching ability. Besides, crossing and variation operation of QDE helps maintain population diversity. The analysis of results proves reasonableness and feasibility of the proposed model and algorithm. |
| Key words: distributed generation probabilistic model environmental factor multi-objective optimization QDE |
