【作者】 徐敏杰；

【导师】 胡兆光； 吴俊勇；

【作者基本信息】 北京交通大学 ， 电力系统及其自动化， 2008， 博士

【摘要】 现代社会,电力的安全供应是经济发展的必要条件。系统分析影响电力需求的各种因素,把握未来电力需求,建立健全电力供需预警机制指导电源、电网的规划与建设,保证电力工业的健康发展具有重大的理论和现实意义。电力供需分析预测与预警受到社会经济等各个方面的影响,属于复杂系统问题,本文首先对研究复杂系统问题的方法论—智能工程理论进行了总结和拓展,然后遵循定性分析—定量分析—预测—预警的思路,对我国电力供需分析预测与预警相关问题进行了研究。主要研究内容如下:理论方面总结和拓展了智能工程方法体系和智能空间中广义模型的种类,给出了智能工程理论的2个推理问题和相关数学描述,定义了数学模型、知识模型、结构模型和Agent模型,发展了α-优越解的定义,给出了β-优越目标、β-目标优越解SL(β)、(α,β)-满意解SL(α,β)和目标可达性的定义,并证明了相关定理,为应用智能工程求解巨型复杂问题提供了理论依据。定性分析了20个影响电力需求变化的因素,运用知识模型和结构模型分析了各个因素之间的递阶层次关系,分析得到影响电力需求的深层原因、浅层原因和表层原因,其中深层原因是宏观经济发展。在定性分析的基础上,做了两个方面的定量分析,一是基于计量经济学模型和社会传播模型提出居民电力消费的混合社会模型,基于Agent模型设计了居民电力消费仿真平台RECMAS来模拟居民电力消费的需求供应关系,仿真分析了电价、居民收入及社会公共教育对居民电力消费的影响。二是基于一般均衡思想,运用Agent模型建立了宏观政策对电力消费影响的政策模拟系统ECMAS。通过微观个体的行为动作模拟仿真社会经济运行,分析了宏观经济政策、居民消费变化、政府支出变化对电力消费的影响,为相关政策对电力需求的模拟分析提供了崭新的手段。基于中长期电力需求预测必须适应未来经济发展的思想,运用系统动力学原理建立了全社会用电量中长期预测模型,运用Agent模型建立了基于Agent的智能预测系统,对我国全社会用电量进行了预测。构建了电力供需预警指标体系,划分了预警级别。基于智能工程理论进行了电力供需预警研究,设计了模糊神经网络智能工程算子,在定量预测的基础上,对我国未来几年的电力供需情况进行预警,提出了保证未来几年电力有效供给增长的装机路径。更多还原

【Abstract】 Because power demand-supply is influenced by a large amount of factors, the forecasting and early-warning of power demand-supply are complex system problems.Hence,it is of significance for theory and practice research on the problem. This dissertation focuses on the research on theory for solving the complex system problem,methodology of policy simulation,forecasting methodology of power demand and early-warning of power demand-supply.The main contents are as follows.Intelligent engineering is theory and methodology for solving complex system problem.In this dissertation,generalized model including knowledge model, mathematical model,structural model and intelligent agent model is established.Theα-optimized solution is redefined,andβ-optimized object,β-optimized object solution,(α,β)-satisfied solution and object reachability are proposed.Some theorems are proved.Electricity demand is influenced by many complex factors.In this dissertation,the factors are analyzed by using knowledge model and structural model,and the hierarchical relationships of the factors are established based on interpretative structural modeling(ISM).Surface,shallow and deep reasons of influencing electricity demand are found out.For analyzing effect of pricing and macroeconomic policy,RECMAS and ECMAS simulation platform are designed based on Complex Adaptive System.By using RECMAS,six policy scenarios are analyzed,the results show that public campaign programming and suitable pricing policies can guide people to build up the awareness of saving and improve the using-electricity efficiency.By using ECMAS,the effect of resident consumption and government expenditure on electricity demand is analyzed.Forecasting power demand is the basis of early-warning of power demand-supply. First,system dynamics model is established and intelligent forecasting system based on agent is designed for forecasting mid-and-long power demand.Second,early-warning indexes are given,and early-warning method of power demand-supply is proposed based on intelligent engineering methodology.As a result,intelligent path of power capacity is recommended from 2008 to 2010 in China.更多还原