基于仿生优化算法的含可再生能源机组负荷调度研究

项目名称： 基于仿生优化算法的含可再生能源机组负荷调度研究

项目编号： No.61273040

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 牛群

作者单位： 上海大学

项目金额： 69万元

中文摘要： 机组负荷调度，是电力系统中一类具有非线性、强约束、时变特性的复杂优化问题。传统煤耗发电会造成空气污染、全球变暖等问题。风能、太阳能这类可再生能源，不会资源枯竭，也不会对环境有危害，因此在提高火电利用率的基础上，高效利用可再生能源，对提高企业经济效益和促进国家的长远发展，具有重要意义。该项目对机组的各种系统动态约束、机组特性约束及系统安全运行状况约束进行研究，以最小化发电燃料总耗量、污染排放量和系统安全稳定程度为目标，建立多目标动态负荷调度模型；对风电的不确定性进行研究，考虑旋转备用约束，提出含风电、太阳能可再生能源多目标动态负荷调度模型；研究细菌觅食算法、人工蜂群算法与和声搜索算法以及相应的多目标算法，并对算法进行改进，提出参数自适应机制，并设计与数学方法或智能算法的结合，将改进的仿生算法应用于含可再生能源多目标动态负荷调度，实现对其高性能优化求解，从而达到为企业降低成本，节能减排的目的。

中文关键词： 机组负荷调度；机组组合问题；可再生能源；仿生优化算法；节能减排

英文摘要： Economic load dispatch (ELD) is one of the power system optimization problems with characteristics of nonlinear, strong constraints and time-varying. Traditional coal power generation may cause air pollution and global warming while other renewable energy sources such as wind and solar power would not cause such problems. Therefore, it is significant for the economic benefit of enterprises and the long-term development of our country to efficiently utilize the renewable energy sources on the basis of raising the utilization rate of thermal power. This project will investigate the dynamic constraints, unit characteristics constraints and system security condition constraint and then establish the multi-objective dynamic load scheduling model with the minimization of total cost of electricity generation fuel and pollution emissions, as well as ensuring the safety and stability of the power system. This project also will investigate the uncertainty of wind power and the spinning reserve constraint, so as to propose the multi-objective dynamic load scheduling model with wind power and solar power. The project will carry out the research on bacteria foraging algorithm, artificial bee colony algorithm, harmony search algorithm and the corresponding multi-objective algorithms. This project will improve the algorithms a

英文关键词： economic load dispatch；unit commitment；sustainable energy；bio-inspired optimization algorithm；energy-saving and emission-reduction