학술논문

Building Foresight in Long-Term Infrastructure Planning Using End-Effect Mitigation Models
Document Type
Periodical
Source
IEEE Systems Journal Systems Journal, IEEE. 11(4):2040-2051 Dec, 2017
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Planning
Investment
Computational modeling
Biological system modeling
Optimization
Mathematical model
Carbon policy
computational time
dual equilibrium
end effects
foresight
infrastructure planning
Language
ISSN
1932-8184
1937-9234
2373-7816
Abstract
This paper applies the end-effect mitigation models to build foresight into long-term infrastructure planning problems. This paper describes the phenomenon of end effects; presents four different models that address it, namely extended simulation, salvage value, and primal and dual equilibria; and applies them to long-term energy system planning problems with finite resources for investments. The planning model is a simultaneous multiperiod linear optimization model that plans for energy system infrastructures at the national scale. Two instances of this model are considered: 1) a small-scale five-node model; and 2) a medium-to-large-scale 13-node model. These instances are used to assess and quantify: 1) the end effects of using investment solutions; and 1) the efficacy of each mitigation methods in terms of accuracy and computational time. The illustrations demonstrate that, without attributing the long-term infrastructure planning with some level of foresight about the future cost and performance of the technologies, the resulting portfolio will have end effects in terms of: 1) investment bias toward low-cost resources at the end years; and 2) adopting low-cost quick fixes (such as excess cofiring) to meet near-term emission targets, both of which may render the model to lose sight of long-term targets and economics.