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[IEEE 2019 International Topical Meeting on Microwave Photonics (MWP) - Ottawa, ON, Canada (2019.10.7-2019.10.10)] 2019 International Topical Meeting on Microwave Photonics (MWP) - Proposal of Photonic Analog-to-digital Conversion Using Weighted Multiwavelength Pulses and Balanced Photodetector

DOI:10.1109/mwp.2019.8892045 出版年份:2019 更新时间:2025-09-23 15:21:01
摘要: Nowadays, enhanced knowledge of the nature of the electricity demand is achieved through the progressively increasing deployment of smart meters and advanced data analysis techniques. One of the major challenges is to exploit this knowledge to support the introduction of strategies to modify the demand according to relevant objectives to be achieved, like users’ participation in demand response programmes. A key point for facing this challenge is to characterize the demand flexibility. In spite of many discussions about the concept of flexibility, the few mathematical definitions of flexibility available do not address the variation in time of the overall demand aggregation. This paper starts from the analysis of time-variable patterns of aggregate residential customers, ending up with suitable definitions of expected flexibility for aggregate demand. These definitions are based on assessing positive and negative pattern variations and are identified from the analysis of the collective behavior of the aggregate users. A set of results is shown for different numbers of aggregate customers, by considering different values of the averaging time step for load pattern representation.
作者: Intisar Ali Sajjad,Gianfranco Chicco,Roberto Napoli
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To define and quantify flexibility in the context of aggregate residential electricity demand, focusing on the variation in time of the overall demand aggregation.

The paper introduces novel demand flexibility indicators (FIAD and PFL) for residential demand aggregations, based on binomial probability models of demand variations. These indicators help quantify the flexibility achievable from aggregate loads in different time periods, aiding in the selection of suitable time slots for demand response programs. The study demonstrates the effects of aggregation level and time step duration on flexibility indicators, providing insights into the collective behavior of residential customers.

The study focuses on residential demand aggregations and does not address real-time control of specific appliances. The approach does not require knowledge of individual user details, which limits the granularity of control but addresses privacy concerns.

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