JOURNAL ARTICLE

Valuing investments in distribution networks with DG under uncertainty

Abstract

After deregulation of the electricity sector, Distributed Generation (DG)has received increasing interest in the power systems development. The identification of efficient and well-timed investments in electric distribution networks that cope with large power market uncertainties is currently an open issue of significant research interest. Strategic flexibility for seizing opportunities and cutting losses contingent upon an unfavorable unfolding of the long-term uncertainties is an attribute of enormous value when assessing irreversible investments in Distribution Systems. In this sense, DG units appear as an effective manner of adding flexibility to the distribution expansion planning. This article proposes an investment valuation approach which properly assesses the option value of deferring investments in distribution feeders whereas gaining flexibility by investing in DG units. The flexibility provided by DG investments -option to abandon and to relocate-is assessed through a Real Option Valuation approach based on the novel Least Square Monte Carlo method (LSM).In order to illustrate the feasibility of the proposed valuation approach, a traditional expansion strategy (distribution feeders) and a flexible investment strategy (distribution feeders and DG) are compared in a study case. The article shows that a proper arrangement of feeders and DG may lead to efficient investments by allowing a progressive adaptation of the distribution grid to the changing scenarios.

Keywords:
Valuation (finance) Distributed generation Flexibility (engineering) Grid Risk analysis (engineering) Power flow Electricity Electric power system Economics Net present value Distribution grid Investment (military) Electricity market Deregulation Environmental economics Computer science Industrial organization Business Microeconomics Renewable energy Engineering Power (physics) Finance Production (economics) Electrical engineering

Metrics

20
Cited By
0.63
FWCI (Field Weighted Citation Impact)
31
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Capital Investment and Risk Analysis
Social Sciences →  Economics, Econometrics and Finance →  Finance
Electric Power System Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Climate Change Policy and Economics
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics

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