A two layer differential evolution algorithm for economic emission dispatch with random wind power
A two layer differential evolution algorithm for economic emission dispatch with random wind power
复制标题
随机风电经济排放调度的两层差分进化算法
DOI：
10.3233/jifs-212735
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发表时间：
2021-12
影响因子：
2
通讯作者：
Ning Liu
中科院分区：
文献类型：
--
作者：
Chenye Qiu;Ning Liu
针对随机风电经济排放调度问题，提出了一种基于多突变策略（TLDE）的双层差分进化算法。近年来，风能等可再生能源越来越多地参与到电力系统中，以解决化石能源短缺和环境污染问题。因此，本文研究了随机风力发电可得性下的电力需求问题。由于风速的不确定性，采用威布尔概率分布函数对随机风力进行建模。为了提高搜索能力，TLDE根据适应度排序将种群分为两层，并对两层中的个体进行区别对待，以充分考察其自身的潜力。这两层可以相互协作，利用信息共享策略进一步提高搜索性能。同时引入了自适应重启方案，避免了系统陷入停滞。采用2台改装后的风力发电机对40台机组系统进行了性能测试。实验结果表明，TLDE方法可以在随机风力发电的EED问题中实现精确的调度策略。
This paper proposes a novel two layer differential evolutionary algorithm with multi-mutation strategy (TLDE) for solving the economic emission dispatch (EED) problem involving random wind power. In recent years, renewable energy such as wind power is more and more participated in the power systems to address the problems of fossil energy shortage and environmental pollution. Hence, the EED problem with the availability of random wind power is investigated in this paper. Due to the uncertain nature of wind speed, the Weibull probability distribution function is used to model the random wind power. In order to improve the search ability, TLDE divides the population into two layers according to the fitness ranking, and individuals in the two layers are treated differently to fully investigate their own potential. The two layers can cooperate with each other to further enhance the search performance by utilizing an information sharing strategy. Also, an adaptive restart scheme is introduced to avoid falling into stagnation. The performance of the proposed TLDE is testified on the 40 units system with 2 modified wind turbines. The experimental results demonstrate that the TLDE method can achieve precise dispatch strategy in EED problem with random wind power.
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