NDLI: Load modelling in distributed generation planning

Content Provider	IEEE Xplore Digital Library
Author	Qian, K. Zhou, C. Allan, M. Yuan, Y.
Copyright Year	2009
Description	Author affiliation: School of Engineering and Computing, Glasgow Caledonian University, Glasgow G4 0BA, U.K. (Qian, K.; Zhou, C.; Allan, M.) \|\| School of Electrical Engineering, Hohai University, Nanjing 210098, China (Yuan, Y.)
Abstract	Increasing the penetration level of Distributed Generation (DG) into the distribution system is a new challenge for traditional electric power systems. Although it is generally recognised that DG has the potential of reducing energy losses in power systems, inappropriate modelling can lead to a misleading predictions for power loss reduction in DG planning. This paper presents an investigation into the impact of load models on the calculation of energy loss. Following a brief introduction the paper proposes detailed modelling of load in DG planning. Load is divided into three categories: residential, industrial and commercial rather than characterised as the traditional constant PQ. A comparative study of real and reactive power losses for various load models and load levels is carried out using the methodology proposed in this paper. In addition, a long term forecasting model is developed to forecast the future customer demand for residential, commercial and industrial sectors in 2020 for the UK, allowing consideration of various factors and aspects, such as, historical load demand, weather data, economic growth and demographic information. A sample power system is adopted to analyse the system performance under various DG scenarios and at various load levels. Simulation results indicate that load models can significantly affect the load losses calculation in DG planning.
Starting Page	1
Ending Page	6
File Size	348538
Page Count	6
File Format	PDF
ISBN	9781424449347
DOI	10.1109/SUPERGEN.2009.5348231
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Weather forecasting Demand forecasting Load model Power system planning Predictive models Power system modeling Energy loss Load forecasting Distributed control Economic forecasting Electrical power loss Distributed generation Load modeling
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Spatial load forecasting model for electrical distribution planning

Short-Term Load Demand Modeling and Forecasting: A Review

An Accurate Model for Short-Term Load Forecasting

Residential load forecast in China

A new ARIMA model for hourly load forecasting

Composite modeling for adaptive short-term load forecasting

A hierarchical neural model in short-term load forecasting

A hierarchical neural model in short-term load forecasting

A study on wind energy generation forecasting using connectionist models

Load modelling in distributed generation planning

Similar Documents

Spatial load forecasting model for electrical distribution planning

Short-Term Load Demand Modeling and Forecasting: A Review

An Accurate Model for Short-Term Load Forecasting

Residential load forecast in China

A new ARIMA model for hourly load forecasting

Composite modeling for adaptive short-term load forecasting

A hierarchical neural model in short-term load forecasting

A hierarchical neural model in short-term load forecasting

A study on wind energy generation forecasting using connectionist models

Load modelling in distributed generation planning