We consider power system expansion planning under uncertainty. In our approach, integer programming and stochastic programming provide a basic framework. We develop a multistage stochastic programming model in which some of the variables are restricted to integer values. By utilizing the special property of the problem, called block separable recourse, the problem is transformed into a two-stage stochastic program with recourse. The electric power capacity expansion problem is reformulated as the problem with first stage integer variables and continuous second stage variables. The L-shaped algorithm to solve the problem is proposed
Multistage stochastic integer programming (MSIP) is a framework for sequential decision making under...
This paper presents a stochastic scenario-based approach to finding an efficient plan for the electr...
We propose a three-stage stochastic integer programming model to tackle the design of smart energy d...
The paper investigates national/regional power generation expansion planning for medium/long-term an...
We present a stochastic model for capacity-expansion planning of electricity dis-tribution networks ...
In this article, we study the long-term power generation investment expansion planning problem under...
We develop a two-stage stochastic integer programming model for the simultaneous optimization of pow...
This paper addresses a multi-period investment model for capacity expansion in an uncertain environm...
textThis dissertation proposes a new transmission planning method for electric power systems with la...
We develop a two-stage stochastic integer programming model for the simultaneous optimization of pow...
Tesis para optar al grado de Magíster en Ciencias de la Ingeniería, Mención Matemáticas AplicadasMem...
Electric energy constitutes one of the most crucial elements to almost every aspect of life of peopl...
We present a mathematical model for maximizing the benefit of a price-taker power producer who has t...
A power generation system comprising thermal and pumped-storage hydro plants is considered. Two kind...
In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed f...
Multistage stochastic integer programming (MSIP) is a framework for sequential decision making under...
This paper presents a stochastic scenario-based approach to finding an efficient plan for the electr...
We propose a three-stage stochastic integer programming model to tackle the design of smart energy d...
The paper investigates national/regional power generation expansion planning for medium/long-term an...
We present a stochastic model for capacity-expansion planning of electricity dis-tribution networks ...
In this article, we study the long-term power generation investment expansion planning problem under...
We develop a two-stage stochastic integer programming model for the simultaneous optimization of pow...
This paper addresses a multi-period investment model for capacity expansion in an uncertain environm...
textThis dissertation proposes a new transmission planning method for electric power systems with la...
We develop a two-stage stochastic integer programming model for the simultaneous optimization of pow...
Tesis para optar al grado de Magíster en Ciencias de la Ingeniería, Mención Matemáticas AplicadasMem...
Electric energy constitutes one of the most crucial elements to almost every aspect of life of peopl...
We present a mathematical model for maximizing the benefit of a price-taker power producer who has t...
A power generation system comprising thermal and pumped-storage hydro plants is considered. Two kind...
In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed f...
Multistage stochastic integer programming (MSIP) is a framework for sequential decision making under...
This paper presents a stochastic scenario-based approach to finding an efficient plan for the electr...
We propose a three-stage stochastic integer programming model to tackle the design of smart energy d...