基于模拟退火粒子群算法的经济调度新方法
A New Approach to the Solution of Economic Dispatch Using Particle Swarm Optimization with Simulated Annealing
摘要：
提出了一种基于粒子群算法的经济调度问题求解方法。它是在专用单元之间分配生产的过程，以便满足强制限制并减少电力需求。更确切地说，软计算方法得到了补充关注，并在许多成功和合理的应用中得到了应用。在这里，已尝试找出最低成本，通过使用粒子群优化算法使用的三个发电机组的数据。在这项工作中，已采取的数据，如损耗系数与最大-最小功率限制和成本函数。粒子群算法和模拟退火算法的功能是为不同的能量需求提供最少的量。当输出与传统的方法相比，粒子群算法似乎给一个改进的结果，增强收敛功能。所有的方法都在MATLAB环境下实现。通过三台机组的算例验证了该方法的有效性和可行性。输出给出了有希望的结果，这意味着预计的计算方法是胜任的经济形成先进的卓越解决方案，解决经济调度问题。
英文摘要：
A new approach to the solution of Economic Dispatch using Particle Swarm Optimization is presented. It is the progression of allocating production amongst the dedicated units such that the restriction forced are fulfilled and the power needs are reduced. More just, the soft computing method has received supplementary concentration and was used in a quantity of successful and sensible applications. Here, an attempt has been made to find out the minimum cost by using Particle Swarm Optimization Algorithm using the data of three generating units. In this work, data has been taken such as the loss coefficients with the max-min power limit and cost function. PSO and Simulated Annealing are functional to put out the least amount for dissimilar energy requirements. When the outputs are compared with the conventional method, PSO seems to give an improved result with enhanced convergence feature. All the methods are executed in MATLAB environment. The effectiveness and feasibility of the proposed method were demonstrated by three generating units case study. Output gives hopeful results, signifying that the projected method of calculation is competent of economically formative advanced eminence solutions addressing economic dispatch problems.
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