Regional-scale electric power system planning under uncertainty—A multistage interval-stochastic integer linear programming approach

In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed for supporting electric power system (EPS) planning under uncertainty that is based on a multistage interval-stochastic integer linear programming method. The developed MIS-REM can deal with uncertaint...

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Bibliographic Details
Published in:Energy policy Vol. 38; no. 1; pp. 475 - 490
Main Authors: Li, Y.F., Huang, G.H., Li, Y.P., Xu, Y., Chen, W.T.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 2010
Elsevier
Elsevier Science Ltd
Series:Energy Policy
Subjects:
Applied sciences
Case studies
Economic data
Economic development
Economic structure
Economics
Electric energy
Electric power
Electric power generation
Electric power system
Electric power system Inexact optimization Multistage
Electricity
Electricity distribution
Electricity generation
Energy
Energy consumption
Energy development
Energy economics
Energy planning
Energy policy
Energy resources
Energy sources
Environmental requirements
Exact sciences and technology
General, economic and professional studies
Inexact optimization
Integer programming
Justification
Linear programming
Methodology. Modelling
Multistage
Optimization
Penalties
Planning
Power plants
Power supply
Regional analysis
Regions
Renewable energy
Renewable resources
Stochastic models
Stochastic processes
Studies
Transactions
Uncertainty
Inexact optimization
Electric power system
Multistage
Uncertainty
Electric energy transportation
Methodology
Regional scope
Transmission capacity
Linear programming
Stochastic programming
Integer programming
Production capacity
Planning
Electric power production
Interval
ISSN:0301-4215, 1873-6777
Online Access:Get full text
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Description
Summary:In this study, a multistage interval-stochastic regional-scale energy model (MIS-REM) is developed for supporting electric power system (EPS) planning under uncertainty that is based on a multistage interval-stochastic integer linear programming method. The developed MIS-REM can deal with uncertainties expressed as both probability distributions and interval values existing in energy system planning problems. Moreover, it can reflect dynamic decisions for electricity generation schemes and capacity expansions through transactions at discrete points of a multiple representative scenario set over a multistage context. It can also analyze various energy-policy scenarios that are associated with economic penalties when the regulated targets are violated. A case study is provided for demonstrating the applicability of the developed model, where renewable and non-renewable energy resources, economic concerns, and environmental requirements are integrated into a systematic optimization process. The results obtained are helpful for supporting (a) adjustment or justification of allocation patterns of regional energy resources and services, (b) formulation of local policies regarding energy consumption, economic development, and energy structure, and (c) analysis of interactions among economic cost, environmental requirement, and energy-supply security.
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ISSN:0301-4215
1873-6777
DOI:10.1016/j.enpol.2009.09.038