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...

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Vydáno v:	IEEE transactions on power systems Ročník 36; číslo 1; s. 97 - 106
Hlavní autoři:	da Costa, Luiz Carlos, Thome, Fernanda Souza, Garcia, Joaquim Dias, Pereira, Mario V. F.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
ISSN:	0885-8950, 1558-0679
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Abstract	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.
AbstractList	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.
Author	Thome, Fernanda Souza da Costa, Luiz Carlos Pereira, Mario V. F. Garcia, Joaquim Dias
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SubjectTerms	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
Title	Reliability-Constrained Power System Expansion Planning: A Stochastic Risk-Averse Optimization Approach
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