智能电网中多种发电模式联合调度模型及效益评价研究

发布时间：2018-03-03 07:33

本文选题：智能电网　切入点：电力预测　出处：《华北电力大学》2014年博士论文　论文类型：学位论文

【摘要】：随着智能电网的发展和节能减排要求的提高,清洁能源发电比重正不断提高。风力发电和太阳能发电具有发电随机性强、可调节能力弱,地域性强、集中度高等特点,提高我国电网对清洁能源接入的适应性,寻求技术经济效益最优的解决策略,加强智能电网建设被认为是解决风电和光电上网问题的关键。本文提出的智能电网中多种发电模式联合调度模型及效益评价研究,通过分析清洁能源发电的必要性、智能电网的要求、大规模清洁能源发电并网的优势和问题,提出清洁能源和传统能源等多种发电模式联合调度的方式,对于我国节能减排目标的实现、电网安全稳定运行、电网和发电企业经济效益的提高具有积极的作用。在大量数据资料分析整理的基础上,系统分析我国电源结构与电网的发展现状及面临的问题,研究智能电网的提出对电源和电网的影响,同时对本文主要研究的几种发电模式,如火力发电、风力发电、太阳能光伏发电等,进行技术经济对比分析,为电力预测、联合调度及效益评价做铺垫；针对风力发电和太阳能光伏发电不稳定性的特点,分别提出了服务于联合调度的基于GABP神经网络的预测模型进行风电输出功率的预测,服务于联合调度基于拟境知识挖掘的自适应神经网络预测模型进行光伏发电输出功率的预测,最后提出了服务于联合调度基于FHNN相似日聚类的组合预测模型进行智能电网电力负荷预测研究；根据我国节能减排的要求,结合风火电联合运营的特点,建立了智能电网中风火电联合运营节能减排调度模型,提出了基于KKT和量子遗传算法的多目标决策智能算法进行模型的求解；根据风力发电和太阳能光伏发电的特点,探讨风光互补混合供电系统模式,建立了风光互补智能调度模型,提出了改进的混沌免疫遗传算法进行模型的求解；综合分析火力发电、风力发电和太阳能光伏发电的特点,建立了一套火、风、光联合运营的电力调度模型,提出了改进的量子粒子群优化算法进行调度模型的求解；综合考虑智能电网中混合电力系统联合调度的特点,从社会效益、环境效益、经济效益、安全性等几个方面进行综合分析,建立了效益评价指标体系,提出了基于Vague集和D-S证据理论的效益评价模型,进行智能电网中多种发电模式联合调度效益评价；针对以上提出的预测模型、调度模型和效益评价模型,分别进行了实证分析和验证。多种发电模式联合调度符合我国智能电网的发展方向,有利于达到节能减排的效果,通过系统深入的分析,针对目前我国多种发电模式联合调度管理中存在的问题,提出了相应的管理方案和建议。本文的电力预测模型、调度模型和效益评价模型,对我国智能电网的发展、多种发电模式联合调度管理具有理论与实践指导借鉴意义。
[Abstract]:With the development of smart grid and the improvement of energy saving and emission reduction requirements, the proportion of clean energy generation is increasing. Wind power generation and solar power generation have the characteristics of strong randomness of power generation, weak adjustable ability, strong regional and high concentration. To improve the adaptability of China's power grid to clean energy access, to seek the best technical and economic solution strategy, and to strengthen the construction of smart grid is considered to be the key to solve the problem of wind power and optoelectronic access. Based on the analysis of the necessity of clean energy generation, the requirements of smart grid, the advantages and problems of large-scale clean energy generation and grid connection, the combined dispatching model and benefit evaluation of multiple generation modes in smart grid are proposed in this paper. This paper puts forward the combined dispatching mode of various power generation modes such as clean energy and traditional energy, which plays a positive role in the realization of energy saving and emission reduction goal, the safe and stable operation of power grid, and the improvement of economic benefits of power grid and power generation enterprises. Based on the analysis and arrangement of a large amount of data, the development status and problems of power supply structure and power grid in China are systematically analyzed, and the influence of smart grid on power supply and power grid is studied. At the same time, several power generation modes studied in this paper, such as thermal power generation, wind power generation, solar photovoltaic power generation, etc., are compared and analyzed technologically and economically, which can pave the way for electric power prediction, joint dispatch and benefit evaluation. According to the characteristics of instability of wind power generation and solar photovoltaic power generation, a prediction model based on GABP neural network for joint dispatch is proposed to predict the output power of wind power. It is used to predict the output power of photovoltaic power generation based on adaptive neural network prediction model based on quasi-environment knowledge mining. Finally, a combined forecasting model based on FHNN similar daily clustering for joint dispatch is proposed to forecast the power load of smart grid. According to the requirements of energy saving and emission reduction in China, combined with the characteristics of wind and thermal power combined operation, The energy saving and emission reduction scheduling model of apoplectic thermal power joint operation in smart grid is established, and the multi-objective decision-making intelligent algorithm based on KKT and quantum genetic algorithm is proposed to solve the model, which is based on the characteristics of wind power generation and solar photovoltaic power generation. In this paper, the model of hybrid power supply system with wind and wind is discussed, and the intelligent dispatching model of wind power is established, and the improved chaos immune genetic algorithm is proposed to solve the model, and the characteristics of thermal power generation, wind power generation and solar photovoltaic power generation are analyzed synthetically. In this paper, a set of fire, wind and light power dispatching models are established, and an improved quantum particle swarm optimization (QPSO) algorithm is proposed to solve the scheduling model. The environmental benefit, economic benefit and safety are analyzed synthetically, the benefit evaluation index system is established, and the benefit evaluation model based on Vague set and D-S evidence theory is put forward. In view of the forecasting model, dispatching model and benefit evaluation model proposed above, the evaluation of joint dispatch benefit of multiple generation modes in smart grid is carried out. The combined dispatching of multiple power generation modes is in line with the development direction of smart grid in China, which is conducive to achieving the effect of energy saving and emission reduction. Aiming at the problems existing in the joint dispatch management of various power generation modes in our country, the corresponding management schemes and suggestions are put forward. The power forecasting model, dispatching model and benefit evaluation model of this paper have theoretical and practical guidance significance for the development of smart grid in China and the joint dispatching management of multiple generation modes.
【学位授予单位】：华北电力大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：F426.61;TM73

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