【作者】 刘震；

【导师】 毕星；

【作者基本信息】 天津大学 ， 管理科学与工程， 2014， 硕士

【摘要】 电力是国民经济发展的基础性能源，在整个能源体系中占据着至关重要的地位，与国民经济的各行各业都息息相关，对国民经济的发展具有关键性的支撑作用。电力行业的健康发展能为经济发展提供强大的能源支撑，促进经济发展；反之，经济的持续发展又能推动电力产业的发展。电力的短缺则会对经济的持续健康发展产生严重的制约作用。由于电力不同于其他能源，不能储存并且不存在库存，能够比较真实的反应社会经济的运行状况，因而，经济发展对电力的需求和电力的供应往往成为社会经济发展的风向标。本文采用离散二阶差分方法，对山东2020年电力需求进行预测。根据离散二阶差分方程的预测结果，山东省2020年电力需求达到5906.64亿千瓦时，相对于2012年上涨了55.66%，上升的幅度看似不大，但是由于电力需求的基数较大，增长的绝对数量值为2112.06，相当于2006年山东全省的电力消费量。因此，山东电力需求在未来几年面临一定的压力。随后利用向量自回归模型，对山东电力需求与经济发展的关系进行分析，由脉冲响应函数分析可知，山东省经济发展随着用电的增长，在经过一定快速增长期之后，由于规模效应、边际效应的原因，在电力需求增加的情况下，经济增长的速度有所减缓。山东经济的增长需要电力能源的支持，并且经济发展越快，需要电力能源的支持力度越大。不过在经济发展到一定程度之后，随着新能源的开发与能源利用效率的提高，经济的发展对电能的依赖程度会变小，加之第三产业等低能耗的行业高速发展，因此会出现山东经济发展与电力需求负相关的现象。最后应用VAR模型对离散二阶差分方法的规律性进行检验，由整合数据序列所构建的VAR模型，从时间序列数据的平稳性、两组整合数据的协整关系与VAR模型的各项指标数据可知，离散二阶差分方法预测出的数据在规律性上具有高精准度。由离散二阶差分方法的数值误差率分析可知，离散二阶差分方法所预测出的数据误差率整体较低，体现出较高的精准度。因此，本文采用离散二阶差分方法所预测出的山东电力需求数据具有很高的可信度，对山东未来电力产业的发展提供数据支持与参考。更多还原

【Abstract】 Electric power is the basic power of the development of national economy, playsa crucial role in the whole energy system, and the national economy in all walks oflifeare closely related, the support is a key to the development of the nationaleconomy.The healthy development of the electric power industry can providepowerful energy support for economic development, promote economic development;on the contrary,the sustained economic development can promote the development ofelectric powerindustry. Power shortages have restricted badly to the sustained andhealthy economic development. Because the power is different from other energysources,cannot be stored and there isno inventory, capable of running status of socialeconomy, reaction more realistic and thus, on the economic development of theelectricity supply and electricity demand often become the barometer of the social andeconomic development.In this thesis, Discrete Difference Equation Prediction Model, carries on theforecast to the Shandong2020electricity demand. According to the prediction resultsof discrete two order differential equations, power demand in Shandong Province in2020reached590664000000kwh, compared to2012rose55.66%, increase may seemsmall, butdue to the base education reform of electricity demand growth, the absolutenumberof the value is2112.06, the power consumption is equivalent to the provinceof Shandong in2006. Therefore, Shandong electric power demand pressures in thenext few years.Then use vector autoregressive model, analyzes the relation between theShandong power demand and economic development, by the analysis of impulseresponse function shows, the economic development of Shandong province with theelectricity growth, after a certain period of rapid growth, the marginal effect of scaleeffect, reason, increase in electricity demand, economic growth has slowed. Thenormal electric energy of Shandong’s economic support, and faster economicdevelopment, the need for power energy support greater efforts. But in the economicdevelopment to a certain extent, with the increasing development and energyutilization efficiency of the new energy, economic development will be smaller for electric dependence onenergy, high-speed development in the third industry lowenergy consumption industry, so there will be the development of Shandong economyand power demand negatively related phenomena.Finally, the application of VAR model to discrete the two order differenceregularity were tested by the method of data integration, VAR model constructed fromsequence, each index data stationary time series data, two groups of data integrationof Cointegration and VAR model, discrete two order difference method to predict thedata in the regularity with high precision. By the analysis of the numerical errors ofdiscrete two order difference method, discrete two order difference data error methodto predict the rate is relatively low, reflecting a high degree of precision. Therefore,the Shandong electricity demand data of Discrete Difference Equation PredictionModel to predict with high credibility, to provide data support and reference on thefuture development of Shandong electric power industry.更多还原