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Residential Electricity Demand: Peaks, Sequences of Activities and Markov chains (REDPeAk)

住宅电力需求：峰值、活动序列和马尔可夫链 (REDPeAk)

基本信息

批准号：
EP/P000630/1
负责人：
Jacopo Torriti
金额：
$ 78.46万
依托单位：
University of Reading
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FP000630%2F1
关键词：
Residential Electricity Demand Peaks Sequences

项目摘要

Peak electricity demand is becoming an increasingly significant problem for UK networks as it causes imbalances between demand and supply with negative impacts on system costs and the environment. The residential sector is responsible for about one third of overall electricity demand (DECC, 2013). During peak demand, electricity prices in wholesale markets could fluctuate from less than 0.04 Euros/kWh to as much as 0.35 Euros/kWh (Torriti, 2015). In the future the peak problem is expected to worsen due to the integration of intermittent renewables in the supply mix as well as high penetration of electric vehicles and electric heat pumps. Understanding what constitutes peaks and identifying areas of effective load shifting intervention becomes vital to the balancing of demand and supply of electricity. Whilst there is information about the aggregate level of consumption of electricity, little is known about residential peak demand and what levels of flexibility might be available. REDPeak will fill this gap.The overall aim of REDPeak is to analyse the variation in sequences of activities taking place at times of peak electricity demand with a view to identify clusters of users which might provide flexibility for peak shifting intervention. The project will analyse 10-minute resolution time use activity data from the UK Office for National Statistics Time Use Survey with a view to derive information about occupancy and synchronisation of activities. Markov chains will be used to model load profiles in combination with appliance-specific parameter data. Since Markov chains have proven effective at generating electricity load profiles except for peak times, REDPeak will develop Hybrid Monte Carlo modelling to account for demand moving in larger steps during peak periods. Sequence analysis will be used to mine activities at periods of peak electricity demand. REDPeak will cluster respondents according to sequences of activities and analyse to what extent appliance-specific control variables explain activities at specific times of the day. Three datasets will be used for direct validation between metered data and time use data. Findings on sequence analysis will feed into algorithms for automated demand management or Demand Side Response.

高峰电力需求正成为英国电网日益严重的问题，因为它会导致需求和供应之间的不平衡，对系统成本和环境产生负面影响。住宅部门约占总电力需求的三分之一（能源和气候变化部，2013年）。在需求高峰期，批发市场的电价可能从低于0.04欧元/千瓦时波动至高达0.35欧元/千瓦时（Torriti，2015年）。未来，由于间歇性可再生能源在供应结构中的整合以及电动汽车和电动热泵的高度渗透，预计峰值问题将恶化。了解什么是高峰，并确定有效的负荷转移干预领域变得至关重要的电力供需平衡。虽然有关于总用电量的资料，但对住宅用电高峰期的需求和灵活程度知之甚少。REDPeak将填补这一空白，其总体目标是分析在电力需求高峰期发生的活动顺序的变化，以期确定用户群，从而为调峰干预提供灵活性。该项目将分析来自英国国家统计局时间使用调查的10分钟分辨率时间使用活动数据，以获得有关活动占用率和同步性的信息。马尔可夫链将用于结合电器特定参数数据对负载曲线进行建模。由于马尔可夫链已被证明在生成除高峰时间外的电力负荷曲线方面是有效的，因此REDPeak将开发混合蒙特卡罗模型，以解释高峰期间需求以更大幅度移动的情况。在电力需求高峰期，将使用序列分析进行开采活动。REDPeak将根据活动顺序对受访者进行聚类，并分析特定于电器的控制变量在多大程度上解释了一天中特定时间的活动。三个数据集将用于计量数据和时间使用数据之间的直接验证。序列分析的结果将输入自动需求管理或需求侧响应的算法。