Reliability-Constrained Power System Expansion Planning: A Stochastic Risk-Averse Optimization Approach

This work presents a methodology to incorporate reliability constraints in the optimal power systems expansion planning problem. Besides Loss Of Load Probability (LOLP) and Expected Power Not Supplied (EPNS), traditionally used in power systems, this work proposes the use of the risk measures VaR (V...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on power systems 2021-01, Vol.36 (1), p.97-106
Main Authors: da Costa, Luiz Carlos, Thome, Fernanda Souza, Garcia, Joaquim Dias, Pereira, Mario V. F.
Format: Article
Language:English
Subjects:
Benders decomposition
Constraints
Dynamic programming
Generators
Investment
Load modeling
Mixed Integer Programming
Monte Carlo
Monte Carlo simulation
Optimization
Planning
Power system reliability
Power systems
Reliability
Reliability analysis
Risk
Risk measures
Stochastic Dual Dynamic Programming
Stochastic programming
System expansion planning
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This work presents a methodology to incorporate reliability constraints in the optimal power systems expansion planning problem. Besides Loss Of Load Probability (LOLP) and Expected Power Not Supplied (EPNS), traditionally used in power systems, this work proposes the use of the risk measures VaR (Value-at-Risk) and CVaR (Conditional Value-at-Risk), widely used in financial markets. The explicit consideration of reliability constraints in the planning problem can be an extremely hard task and, to minimize computational effort, this work applies the Benders decomposition technique splitting the expansion planning problem into an investment problem and two subproblems to evaluate the system's operation cost and the reliability index. The operation subproblem is solved by Stochastic Dual Dynamic Programming (SDDP) and the reliability subproblem by Monte Carlo simulation. The proposed methodology is applied to the real problem of optimal expansion planning of the Bolivian power system.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2020.3007974