Full stochastic scheduling for low-carbon electricity systems
File(s)CFP_TASE_Teng_Strbac_Final_V1.docx (278.73 KB)
Accepted version
Author(s)
Teng, F
Strbac. G
Type
Journal Article
Abstract
High penetration of renewable generation will increase the requirement for both operating reserve and frequency response, due to its variability, uncertainty and limited inertia capability. Although the importance of optimal scheduling of operating reserve has been widely studied, the scheduling of frequency response has not yet been fully investigated. In this context, this paper proposes a computationally-efficient mixed integer linear programming formulation for a full stochastic scheduling model that simultaneously optimizes energy production, operating reserve, frequency response and under-frequency load shedding. By using value of lost load as the single security measure, the model optimally balances the cost associated with the provision of various ancillary services against the benefit of reduced cost of load curtailment. The proposed model is applied in a 2030 GB system to demonstrate its effectiveness. Impact of installed capacity of wind generation and setting of value of lost load are also analysed. Note to Practitioners— One of the obstacles for large scale deployment of wind generation is the challenges it imposes on the efficient operation of the electricity system. This paper presents a full stochastic scheduling model. The long-term uncertainty driven by wind forecasting errors and short-term uncertainty driven by generation outages are modelled by using scenario tree and capacity outage probability table, respectively. The model leads to significant operation cost saving within reasonable computational time. The proposed model could be applied in real large-scale power systems to support the cost-effective integration of wind generation.
Date Issued
2017-01-25
Date Acceptance
2016-11-08
Citation
IEEE Transactions on Automation Science and Engineering, 2017, 14 (2), pp.451-470
ISSN
1558-3783
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Start Page
451
End Page
470
Journal / Book Title
IEEE Transactions on Automation Science and Engineering
Volume
14
Issue
2
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/N005996/1
Subjects
Science & Technology
Technology
Automation & Control Systems
Power system dynamics
stochastic programming
unit commitment (UC)
wind energy
CONSTRAINED UNIT COMMITMENT
FREQUENCY CONTROL
POWER-SYSTEMS
WIND POWER
DISPATCH
LOAD
UNCERTAINTY
FORMULATION
SECURITY
MODEL
0906 Electrical And Electronic Engineering
0910 Manufacturing Engineering
0913 Mechanical Engineering
Industrial Engineering & Automation
Publication Status
Published