小水电站群智能调度系统的研究与实现

发布时间：2018-04-11 13:47

本文选题：小水电群 + 调度系统　；参考：《浙江工业大学》2014年硕士论文

【摘要】：小水电是经济发展、环境保护与生态建设的重要手段。将小水电群进行联合优化调度,可以整体提升区域内小水电的经济效益和生态效益,促进小水电的可持续发展。目前小水电的调度情况大多采用人工经验的方式,该调度方式完全凭借电站工作人员的经验进行决策,调度结果具有不稳定性和不确定性,不同调度人员的调度结果往往存在根本性的差异,无法明确是否为最优调度策略。水电调度模型多样性使得调度系统无法全面考虑,后期系统模型升级繁琐。基于以上几点,本文的主要工作如下：(1)分析小水电调度中存在的具体问题和现有的实际调度方案,建立了适合长期调度和短期调度的多个目标模型,并选取了多个优化求解算法。(2)实现小水电群调度模型可插拔设计,采用接口抽取方法与关注点分离思想,将多个调度模型以XML描述文件或JSON字符串的格式进行切割分片,在调度决策中以可插拔的形式制定调度计划,具备了良好的可操作性和扩展性。(3)针对项目试点区域江西省泸水河流域进行调度目标建模工作。采用粒子群算法和改进粒子群算法对所建立的模型进行优化求解。仿真实验证明模型具有实用价值,通过优化调度可以提高泸水河流域内的整体发电效益,并且选取的改进粒子群算法具有较强的全局搜索能力和较快的收敛速度。(4)开发基于B/S架构的小水电站群调度系统,实现了集径流预测、中长期优化调度相结合、生态安全调控等各种要求。
[Abstract]:Small hydropower is an important means of economic development, environmental protection and ecological construction.The joint optimal dispatching of small hydropower groups can enhance the economic and ecological benefits of small hydropower in the whole region and promote the sustainable development of small hydropower.At present, most of the dispatching conditions of small hydropower are based on artificial experience, and the dispatching method is based entirely on the experience of the staff of the power station to make decisions, and the scheduling results are unstable and uncertain.The scheduling results of different schedulers are often fundamentally different, and it is not clear whether the optimal scheduling policy is or not.Because of the diversity of hydropower dispatching model, the scheduling system can not be considered comprehensively, and the upgrade of the system model is tedious.Based on the above points, the main work of this paper is as follows: 1) analyzing the specific problems existing in the small hydropower dispatching and the existing actual scheduling schemes, and establishing several target models suitable for long-term and short-term scheduling.Several optimization algorithms are selected to realize the pluggable design of small hydropower group scheduling model. The interface extraction method and the idea of separating concern are used to cut multiple scheduling models in the format of XML description file or JSON string.The scheduling plan is formulated in the form of pluggable, which has good maneuverability and expansibility. (3) the target modeling for the Lushui River basin in Jiangxi Province is carried out in the pilot area of the project.Particle Swarm Optimization (PSO) and improved PSO (improved PSO) are used to solve the model.The simulation results show that the model has practical value, and the overall power generation efficiency in Lushui River Basin can be improved by optimal dispatching.And the improved particle swarm optimization algorithm has strong global search ability and faster convergence speed. It develops a small hydropower station group dispatching system based on B / S architecture, which realizes runoff prediction and mid-long term optimal operation.Ecological security control and other requirements.
【学位授予单位】：浙江工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TV737

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