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Household response to dynamic pricing of electricity: a survey of 15 experiments

机译:家庭对动态电价的反应:15个实验的调查

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Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a change out of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40% may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, this paper surveys the evidence from the 15 most recent pilots, experiments and full-scale implementations of dynamic pricing of electricity. It finds conclusive evidence that households respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way programmable communicating thermostats and always-on gateway systems that allow multiple end-uses to be controlled remotely. In addition, the design of the studies, the tools used to analyze the data and the geography of the assessment influence demand response. Across the range of experiments studied, time-of-use rates induce a drop in peak demand that ranges between 3 and 6% and critical-peak pricing (CPP) tariffs induce a drop in peak demand that ranges between 13 and 20%. When accompanied with enabling technologies, the latter set of tariffs lead to a reduction in peak demand in the 27-44% range.
机译:自从2000年至2001年美国西部的能源危机以来,人们对提高电力市场的需求响应给予了极大关注。实现这一目标的最佳方法之一是将批发能源成本转嫁给零售客户。这可以通过让零售价格全部或部分动态变化来实现。对于绝大多数客户而言,这需要改变计量基础设施,整个美国的费用可能高达400亿美元。尽管可以通过节省配电系统成本来弥补这一投资的很大一部分,但仍有大约40%的问题仍未解决。这种投资缺口可以通过减少发电成本来弥补,这可以通过需求响应来实现。因此,许多州的州监管机构正在调查客户是否会通过降低需求来应对较高的价格,如果降低的话会降低多少。为了帮助评估,本文调查了15个最新的电力动态定价试点,实验和全面实施的证据。它找到确凿的证据表明,家庭通过降低用量来应对更高的价格。价格响应的幅度取决于几个因素,例如价格上涨的幅度,中央空调的存在以及使能技术的可用性,例如双向可编程通讯恒温器和始终开启的网关系统等,这些技术允许多个终端用户使用。用于远程控制。此外,研究的设计,用于分析数据的工具和评估的地理位置会影响需求响应。在所研究的整个实验范围内,使用时间率导致峰值需求下降3%至6%,而临界峰定价(CPP)关税导致峰值需求下降13%至20%。当与赋能技术一起使用时,后一组关税导致峰值需求减少27-44%。

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