Stochastic optimisation-based valuation of smart grid options under firm DG contracts
File(s)symplectic_copy.pdf (1.04 MB)
Accepted version
Author(s)
Giannelos, S
Konstantelos, I
Strbac, G
Type
Conference Paper
Abstract
Under the current EU legislation, Distribution Network
Operators (DNOs) are expected to provide firm connections to new
DG, whose penetration is set to increase worldwide creating the
need for significant investments to enhance network capacity.
However, the uncertainty around the magnitude, location and
timing of future DG capacity renders planners unable to accurately
determine in advance where network violations may occur. Hence,
conventional network reinforcements run the risk of asset
stranding, leading to increased integration costs. A novel stochastic
planning model is proposed that includes generalized formulations
for investment in conventional and smart grid assets such as
Demand-Side Response (DSR), Coordinated Voltage Control (CVC)
and Soft Open Point (SOP) allowing the quantification of their
option value. We also show that deterministic planning approaches
may underestimate or completely ignore smart technologies.
Operators (DNOs) are expected to provide firm connections to new
DG, whose penetration is set to increase worldwide creating the
need for significant investments to enhance network capacity.
However, the uncertainty around the magnitude, location and
timing of future DG capacity renders planners unable to accurately
determine in advance where network violations may occur. Hence,
conventional network reinforcements run the risk of asset
stranding, leading to increased integration costs. A novel stochastic
planning model is proposed that includes generalized formulations
for investment in conventional and smart grid assets such as
Demand-Side Response (DSR), Coordinated Voltage Control (CVC)
and Soft Open Point (SOP) allowing the quantification of their
option value. We also show that deterministic planning approaches
may underestimate or completely ignore smart technologies.
Date Issued
2016-04-08
Date Acceptance
2016-02-01
Citation
2016
Publisher
IEEE
Copyright Statement
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (E
Grant Number
EP/I031650/1
Source
2016 IEEE International Energy Conference (ENERGYCON)
Publication Status
Published
Start Date
2016-04-04
Finish Date
2016-04-08
Coverage Spatial
Leuven, Belgium