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Article . 2017 . Peer-reviewed
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Evaluation of regulatory impacts on investments of distributed generation and upstream network under uncertainty: a new stochastic bi-level model

Authors: Farshid Misaghi; Taghi Barforoushi;

Evaluation of regulatory impacts on investments of distributed generation and upstream network under uncertainty: a new stochastic bi-level model

Abstract

A new framework is proposed to study impacts of regulatory incentive policies on distributed generation (DG) investment, as well as upgrading of upstream transmission substations and sub-transmission lines. Investment incentives are fuel cost, firm contracts, capacity payments and investment subsidy. Conventional and wind generation technologies are considered as expansion candidates for investor which participate in wholesale and contractual markets. High Temperature Low Sag (HTLS) conductors are used as expansion candidates for lines. The problem is modelled as a stochastic bi-level optimization problem, where the upper-level consists of investor’s decisions maximizing its own profit, while both market clearing and decision on upgrading of substations and lines aimed at minimizing the total cost are considered in the lower-level. Due to non-convexity of lower level problem, an algorithm based on enumeration and mathematical optimization is used where for each expansion strategies of substations and lines, the bi-level problem is converted to a stochastic mathematical programming with equilibrium constraints and then converted to a mixed-integer linear program. The effectiveness of the proposed model is tested through on an actual 22-bus [The west of MAZANDARAN Regional Electric Company (MREC) sub-transmission network as an area of Iran interconnected power system.] network.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Average
gold