Some Aspects of Sampling Load Curve Data On Distribution Systems

Due to fluctuating characteristics of loads, dynamic reactive power optimization over a certain time period is essential to provide effective strategies to maintain the security and economic operation of distribution systems. In operation, reactive power compensation devices cannot be adjusted too frequently due to their lifetime constraints. Thus, in this paper, an online reactive power optimization strategy based on the segmentation of multiple predicted load curves is proposed to address this issue, aiming to minimize network losses and at the same time to minimize reactive power-compensation device adjustment times. Based on forecasted time series of loads, the strategy first segments each load curve into several sections by means of thresholding a filtered signal, and then optimizes reactive power dispatch based on average load in each section. Through case studies using a modified IEEE 34-bus system and field measurement of loads, the merits of the proposed strategy is verified in terms of both optimization performance and computational efficiency compared with state-of-the-art methods.

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Adequacy of neural networks for wide-scale day-ahead load forecasts on buildings and distribution systems using smart meter data

Energy Informatics ◽

10.1186/s42162-020-00132-6 ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Oleg Valgaev ◽

Friederich Kupzog ◽

Hartmut Schmeck

Keyword(s):

Neural Network ◽

Distribution System ◽

Distribution Systems ◽

Residential Buildings ◽

Network Architectures ◽

Smart Meters ◽

Load Curve ◽

One Step ◽

Wide Scale ◽

Different Characteristics

AbstractPower system operation increasingly relies on numerous day-ahead forecasts of local, disaggregated loads such as single buildings, microgrids and small distribution system areas. Various data-driven models can be effective predicting specific time series one-step-ahead. The aim of this work is to investigate the adequacy of neural network methodology for predicting the entire load curve day-ahead and evaluate its performance for a wide-scale application on local loads. To do so, we adopt networks from other short-term load forecasting problems for the multi-step prediction. We evaluate various feed-forward and recurrent neural network architectures drawing statistically relevant conclusions on a large sample of residential buildings. Our results suggest that neural network methodology might be ill-chosen when we predict numerous loads of different characteristics while manual setup is not possible. This article urges to consider other techniques that aim to substitute standardized load profiles using wide-scale smart meters data.

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Some Aspects of Sampling Load Curve Data on Distribution Systems

IEEE Power Engineering Review ◽

10.1109/mper.1985.5528380 ◽

1985 ◽

Vol PER-5 (11) ◽

pp. 45-46

Author(s):

H. L. Willis ◽

T. D. Vismor ◽

R. W. Powe

Keyword(s):

Distribution Systems ◽

Load Curve

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A Section Load Management Method using Daily Load Curve in Distribution Systems

Journal of the Korean Institute of Illuminating and Electrical Installation Engineers ◽

10.5207/jieie.2012.26.6.047 ◽

2012 ◽

Vol 26 (6) ◽

pp. 47-52

Author(s):

Seong-Il Lim

Keyword(s):

Distribution Systems ◽

Load Management ◽

Load Curve ◽

Management Method ◽

Daily Load

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Bi-Level Load Peak Shifting and Valley Filling Dispatch Model of Distribution Systems With Virtual Power Plants

Frontiers in Energy Research ◽

10.3389/fenrg.2020.596817 ◽

2020 ◽

Vol 8 ◽

Author(s):

Fengzhang Luo ◽

Xin Yang ◽

Wei Wei ◽

Tianyu Zhang ◽

Liangzhong Yao ◽

...

Keyword(s):

Distribution System ◽

Power Plants ◽

Distribution Systems ◽

Distribution Networks ◽

Virtual Power ◽

Load Curve ◽

Optimal Dispatch ◽

Virtual Power Plants ◽

Level Model ◽

Load Peak

Distributed energy resources (DERs) have been widely involved in the optimal dispatch of distribution systems which benefit from the characteristics of reliability, economy, flexibility, and environmental protection. And distribution systems are gradually transforming from passive networks to active distribution networks. However, it is difficult to manage DERs effectively because of their wide distribution, intermittency, and randomness. Virtual power plants (VPPs) can not only coordinate the contradiction between distribution systems and DERs but also consider the profits of DERs, which can realize the optimal dispatch of distribution systems effectively. In this paper, a bi-level dispatch model based on VPPs is proposed for load peak shaving and valley filling in distribution systems. The VPPs consist of distributed generations, energy storage devices, and demand response resources. The objective of the upper-level model is smoothing load curve, and the objective of the lower-level model is maximizing the profits of VPPs. Meanwhile, we consider the quadratic cost function to quantify the deviation between the actual output and the planned output of DGs. The effectiveness of the bi-level dispatch model in load shifting and valley filling is proved by various scenarios. In addition, the flexibility of the model in participating in distribution system dispatch is also verified.

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Reliability Improvement in a Radial Distribution System Using DG

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.768.351 ◽

2013 ◽

Vol 768 ◽

pp. 351-358

Author(s):

Sitan Kumar Singh ◽

D. Sattianadan ◽

M. Sudhakaran

Keyword(s):

Reliability Analysis ◽

Radial Distribution ◽

Distribution System ◽

Distribution Systems ◽

Large Scale ◽

Electric Power Industry ◽

Vital Role ◽

Load Curve ◽

Radial Distribution System ◽

Electrical Distribution Systems

Reliability analysis plays a very vital role in designing and planning of radial distribution systems that operate for minimal interruption of customer loads. The Distributed Generation (DG) in a radial distribution network has been slowly increasing for the last few years due to advancement of technologies and institutional changes in the electric power industry. This paper presents a reliability analysis for large scale, radial (with respect to substation) and reconfigurable electrical distribution systems. This paper evaluates the improvement in reliability over a time varying load curve.

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