Optimal Abandonment Decision for an Energy Portfolio under Uncertainty of Electricity Prices

Scott Grasman; Jianjun Deng; Zhen Liu

Optimal Abandonment Decision for an Energy Portfolio under Uncertainty of Electricity Prices

Scott Grasman, Jianjun Deng, Zhen Liu

Kettering University

Missouri University of Science and Technology

Research output: Contribution to conference › Presentation

Abstract

It’s important for a firm to make effective decisions under uncertainties around it. This paper formulates the optimal abandonment decisions to shut down a power plant in an energy portfolio, with the objective to maximize expected long-term unit profit over a finite time horizon. The electricity price is modeled as Geometric Brownian Motion (GBM) stochastic processes, and auxiliary problems are introduced in order to solve the original problem. The problem is modeled as a mixed optimal stochastic control and optimal stopping problem. Finite Difference Methods are used as numerical method to solve the PDEs in the case study section. Sensitivity studies are conducted to reveal the compact of parameters to the decisions.

Original language	American English
State	Published - 2012
Event	2012 Industrial and Systems Engineering Research Conference - Orlando, Florida Duration: Jan 1 2012 → …

Conference

Conference	2012 Industrial and Systems Engineering Research Conference
Period	1/1/12 → …

Keywords

Energy Portfolio
Optimal Control
Abandonment Decision

Disciplines

Operations Research, Systems Engineering and Industrial Engineering

Cite this

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AB - It’s important for a firm to make effective decisions under uncertainties around it. This paper formulates the optimal abandonment decisions to shut down a power plant in an energy portfolio, with the objective to maximize expected long-term unit profit over a finite time horizon. The electricity price is modeled as Geometric Brownian Motion (GBM) stochastic processes, and auxiliary problems are introduced in order to solve the original problem. The problem is modeled as a mixed optimal stochastic control and optimal stopping problem. Finite Difference Methods are used as numerical method to solve the PDEs in the case study section. Sensitivity studies are conducted to reveal the compact of parameters to the decisions.

KW - Energy Portfolio

KW - Optimal Control

KW - Abandonment Decision

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M3 - Presentation

T2 - 2012 Industrial and Systems Engineering Research Conference

Y2 - 1 January 2012

ER -

Optimal Abandonment Decision for an Energy Portfolio under Uncertainty of Electricity Prices

Abstract

Conference

Keywords

Disciplines

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