Utilizing Demand Response to Improve Network Reliability and Ageing Resilience
Utilizing Demand Response to Improve Network Reliability and Ageing Resilience
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DOI：
10.1109/tpwrs.2018.2883612
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发表时间：
2019-05-01
影响因子：
6.6
通讯作者：
Abogaleela, Mohamed
中科院分区：
文献类型：
--
作者：
Kopsidas, Konstantinos;Abogaleela, Mohamed
提高在不确定情况下的运行灵活性和弹性是现有电网面临的一个永恒的挑战。传统上，应急负载和概率热额定部署在架空线路（ohl）上，为网络运营商提供这种灵活性。目前面临的挑战是量化这些操作实践对OHL导体老化风险的影响，但只有少数研究针对潜在的解决方案进行了调查，以提高灵活性，同时通过采用需求响应来最大限度地降低老化风险。本文提出了一种概率建模方法，该方法利用紧急情况下可用的需求响应，利用双目标优化函数最小化网络OHLs老化并最大化其在不确定情况下的可靠性。因此，所提出的优化为运营商提供了在老化和可靠性成本与需求响应成本之间进行权衡的灵活性。建立了一个预定义的预期等效网络老化指标，将组件老化与可用的网络需求响应联系起来。对24总线IEEE-RTS拟议框架的研究结果表明，网络预期的不供电和中断成本降低了30%以上，同时将整个网络老化减半。因此，需求响应可以对降低关键线路的老化和维护成本产生重大影响。
Increasing operation flexibility and resilience at uncertainties is an everlasting challenge for existing power networks. Emergency loadings and probabilistic thermal ratings are traditionally deployed on overhead lines (OHLs) to provide network operators with such flexibility. The challenge is to quantify the impact of these operating practices on the OHL conductor ageing risks, but only a few investigations exist on potential solutions to enhance flexibility whilst minimizing ageing risks by employing demand response. This paper presents a probabilistic modeling approach that uses a two-objective optimization function to minimize network's OHLs ageing and maximize its reliability at uncertainties by utilizing the available demand response at emergencies. Hence, the proposed optimization provides the operator with the flexibility to tradeoff between ageing and reliability costs against demand response costs. A predefined expected equivalent network ageing index is formulated to relate component ageing with available network demand response. The study of the proposed framework on the 24-bus IEEE-RTS resulted in more than 30% reduction of the network's expected energy not supplied and interruption costs, whilst halving the overall network ageing. Demand response, thus, can have a significant impact on reducing ageing and maintenance costs at critical lines.