Residential load variability and diversity at different sampling time and aggregation scales

The increasing use of large-scale intermittent distributed renewable energy resources on the electrical power system introduces uncertainties in both network planning and management. In addition to architectural changes to the power system, the applications of demand side response (DSR) also add a d...

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Main Authors: Elombo, A, Morstyn, T, Apostolopoulou, D, McCulloch, M
Format: Conference item
Published: Institute of Electrical and Electronics Engineers 2017
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author Elombo, A
Morstyn, T
Apostolopoulou, D
McCulloch, M
author_facet Elombo, A
Morstyn, T
Apostolopoulou, D
McCulloch, M
author_sort Elombo, A
collection OXFORD
description The increasing use of large-scale intermittent distributed renewable energy resources on the electrical power system introduces uncertainties in both network planning and management. In addition to architectural changes to the power system, the applications of demand side response (DSR) also add a dimension of complexity - thereby converting the traditionally passive customers into active prosumers (customers that both produce and consume electricity). It has therefore become important to conduct detailed studies on system load profiles to uncover the nature of the system load. These studies could help distribution network operators (DNOs) to adopt relevant strategies that can accommodate new resources such as distributed generation and energy storage on the evolving distribution network and ensure updated design and management approaches. This paper investigates the relationship between both the system load diversity and variability when different customers are aggregated at different scales. Additionally, the implication of sampling time scales is investigated to capture its effect on load diversity and variability. The study looks at the diversity and variability that is observable from the viewpoint of higher power levels, when interconnecting different sized groupings of customers, at different sampling resolutions. The paper thus concludes that the per-customer capacity requirement of the network decreases as the size of customer groupings increases. The load variability also decreases as the aggregation level increases. For active network management, faster time scales are required at lower aggregation scales due to high load variability.
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spelling oxford-uuid:3345dc74-b2fa-4e50-8406-343e8153c2c72022-03-26T13:19:20ZResidential load variability and diversity at different sampling time and aggregation scalesConference itemhttp://purl.org/coar/resource_type/c_5794uuid:3345dc74-b2fa-4e50-8406-343e8153c2c7Symplectic Elements at OxfordInstitute of Electrical and Electronics Engineers2017Elombo, AMorstyn, TApostolopoulou, DMcCulloch, MThe increasing use of large-scale intermittent distributed renewable energy resources on the electrical power system introduces uncertainties in both network planning and management. In addition to architectural changes to the power system, the applications of demand side response (DSR) also add a dimension of complexity - thereby converting the traditionally passive customers into active prosumers (customers that both produce and consume electricity). It has therefore become important to conduct detailed studies on system load profiles to uncover the nature of the system load. These studies could help distribution network operators (DNOs) to adopt relevant strategies that can accommodate new resources such as distributed generation and energy storage on the evolving distribution network and ensure updated design and management approaches. This paper investigates the relationship between both the system load diversity and variability when different customers are aggregated at different scales. Additionally, the implication of sampling time scales is investigated to capture its effect on load diversity and variability. The study looks at the diversity and variability that is observable from the viewpoint of higher power levels, when interconnecting different sized groupings of customers, at different sampling resolutions. The paper thus concludes that the per-customer capacity requirement of the network decreases as the size of customer groupings increases. The load variability also decreases as the aggregation level increases. For active network management, faster time scales are required at lower aggregation scales due to high load variability.
spellingShingle Elombo, A
Morstyn, T
Apostolopoulou, D
McCulloch, M
Residential load variability and diversity at different sampling time and aggregation scales
title Residential load variability and diversity at different sampling time and aggregation scales
title_full Residential load variability and diversity at different sampling time and aggregation scales
title_fullStr Residential load variability and diversity at different sampling time and aggregation scales
title_full_unstemmed Residential load variability and diversity at different sampling time and aggregation scales
title_short Residential load variability and diversity at different sampling time and aggregation scales
title_sort residential load variability and diversity at different sampling time and aggregation scales
work_keys_str_mv AT elomboa residentialloadvariabilityanddiversityatdifferentsamplingtimeandaggregationscales
AT morstynt residentialloadvariabilityanddiversityatdifferentsamplingtimeandaggregationscales
AT apostolopouloud residentialloadvariabilityanddiversityatdifferentsamplingtimeandaggregationscales
AT mccullochm residentialloadvariabilityanddiversityatdifferentsamplingtimeandaggregationscales