报告题目：Forecasting Long-Term Substation Maximum Electricity Demand as a Function of Trends in Customer Count and Energy Throughput: An Application of Extreme Value Theory
报告时间：2018年09月27日 (星期四) 15:30-16:30
报告地点：尚贤楼1楼108报告厅
报告主持人: 曹春正 教授
报告内容简介：
Substation annual maximum electricity demand events are extreme, as customers respond to infrequent and extreme weather. Despite the extreme nature of annual maximum demand, the statistical theory of extreme values has only rarely, if ever, been applied. To support long term planning, utilities typically complete energy consumption and maximum demand forecasts, are often forecast separately through two different process, which can lead to inconsistent trends and messages. To address these shortcomings, a point process approach from extreme value theory is proposed to model substation maximum demand as a function of trends in three common factors (including the customer count, the energy throughput and installed photovoltaic capacity). The point process model can be parameterized as a nonstationary generalized extreme value distribution with location and scale parameters dependent on the trends in these factors. As the generalized extreme value distribution governs the behaviors of block maxima (annual maximum demand), with forecast trends in three common factors, substation maximum demand can be estimated as per quantiles required by planning standards. Therefore, the proposed approach is not only more realistic and flexible to forecast maximum demand, but also ensures consistent outcomes and messaging between the two outputs from energy consumption and maximum demand forecasts.
专家简介：
李云博士，澳大利亚西澳电力商业情报与数据分析高级咨询顾问，高级预报和模型分析研究员。主要负责西澳电力网络的可靠性和供电量的统计建模和预报研究（包括天气极端事件对电力网络的可靠性和供电量的影响），为西澳电力高层决策和规划管理提供内部高级数据分析咨询和建议。2000-2015年任澳大利亚联邦科学与工业研究组织（CSIRO）首席研究员，从事气候统计学的研究，主要研究领域包括天气和气候极端事件的统计建模、统计降尺度模型、气候变化诊断、降水和气温的统计预报等。
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数学与统计学院
2018-09-26