NDLI: Probabilistic available transfer capability assessment in power systems with wind power integration

Content Provider	IET Digital Library
Author	Sun, Xin Tian, Zhongbei Rao, Yufei Li, Zhaohui Tricoli, Pietro
Abstract	Extending current deterministic tools to incorporate significant stochastic wind power is becoming an important as well as challenging task for present-day power system decision-making. This study proposes a novel probabilistic assessment method to assess the available transfer capability (ATC). Usually, repeated ATC evaluations with an exhaustive set of samples are needed to obtain converged results by the Monte Carlo simulation. To alleviate the computation burden, a statistically-equivalent surrogate model for the ATC solution is constructed based on the canonical low-rank approximation (LRA). By implementing LRA for the base case and a set of enumerated contingencies, the uncertainties of wind power generation and load, as well as transmission equipment outages, are addressed efficiently. With the proposed method, the probabilistic ATC is characterised, and the most influential uncertain factors are identified, which helps to determine a suitable ATC level. The effectiveness of the proposed method is validated via case studies with a modified IEEE 118-bus system.
Starting Page	1912
Ending Page	1920
Page Count	9
ISSN	17521416
Volume Number	14
e-ISSN	17521424
Issue Number	Issue 11, Aug (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2019.1383
Journal	IET Renewable Power Generation
Publisher Date	2020-05-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ATC Solution Computation Burden Converged Result Current Deterministic Tools Exhaustive Set Incorporate Significant Stochastic Wind Power Load Flow Low-rank Approximation LRA Modified IEEE 118-bus System Monte Carlo Method Monte Carlo Simulation Optimisation Technique Power System Power System Economics Power System Managemen Power System Operation Power System Planning And Layout Power System Reliability Power System Security Power Transmission Planning Power Transmission Reliability Present-day Power System Decision-making Probabilistic Assessment Method Probabilistic ATC Probabilistic Available Transfer Capability Assessment Probability Reliability Repeated ATC Evaluations Statistically-equivalent Surrogate Model Statistics Stochastic Linearised SCUC Suitable ATC Level Wind Power Generation Wind Power Integration Wind Power Plant
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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

Probabilistic assessment of available transfer capability considering spatial correlation in wind power integrated system

Probabilistic Assessment of Available Transfer Capability Based on Monte Carlo Method With Sequential Simulation

Determination of available transfer capability with implication of cascading collapse uncertainty

Research on low carbon electricity under the probabilistic reliability evaluation

Data clustering based probabilistic optimal power flow in power systems

Probabilistic-Based Available Transfer Capability Assessment Considering Existing and Future Wind Generation Resources

Available transfer capability analysis method of AC–DC power system based on security region

Determination of optimal total transfer capability using a probabilistic approach

Flexible transmission expansion planning associated with large-scale wind farms integration considering demand response

Probabilistic available transfer capability assessment in power systems with wind power integration

Similar Documents

Probabilistic assessment of available transfer capability considering spatial correlation in wind power integrated system

Probabilistic Assessment of Available Transfer Capability Based on Monte Carlo Method With Sequential Simulation

Determination of available transfer capability with implication of cascading collapse uncertainty

Research on low carbon electricity under the probabilistic reliability evaluation

Data clustering based probabilistic optimal power flow in power systems

Probabilistic-Based Available Transfer Capability Assessment Considering Existing and Future Wind Generation Resources

Available transfer capability analysis method of AC–DC power system based on security region

Determination of optimal total transfer capability using a probabilistic approach

Flexible transmission expansion planning associated with large-scale wind farms integration considering demand response

Probabilistic available transfer capability assessment in power systems with wind power integration