Back to results

Virginia Tech

An Expert-based Approach for Demand Curtailment Allocation Subject to Communications and Cyber Security Limitations

Abstract

dc:description.abstract

A smart grid is different from a traditional power system in that it allows incorporation of intelligent features and functions, e.g., meter reading, adaptive demand response, integration of distributed energy sources, substation automation, etc. All these intelligent features and functions are achieved by choosing appropriate communication technologies and network structures for the smart grid appropriately. The objective of this dissertation is to develop an AHP (analytic hierarchy process) - based strategy for demand curtailment allocation that is subject to communications and cyber security limitations. Specifically, it: (1) proposes an electrical demand curtailment allocation strategy to keep the balance between supply and demand in case of the sudden supply shortage; (2) simulates the operation of the proposed demand curtailment allocation strategy considering the impact from communication network limitations and simultaneous operations of multiple smart grid applications sharing the same communication network; and (3) analyzes the performance of the proposed demand curtailment allocation strategy when selected cyber security technologies are implemented. These are explained in more details below. An AHP-based approach to electrical demand curtailment allocation management is proposed, which determines load reduction amounts at various segments of the network to maintain the balance between generation and demand. Appropriate communication technologies and the network topology are used to implement these load reduction amounts down to the end-user. In this proposed strategy, demand curtailment allocation is quantified taking into account the demand response potential and the load curtailment priority of each distribution substation. The proposed strategy helps allocate demand curtailment (MW) among distribution substations or feeders in an electric utility service area based on requirements of the central load dispatch center. To determine how rapidly the proposed demand curtailment strategy can be implemented, the capability of the communication network supporting the demand curtailment implementation needs to be evaluated. To evaluate the capability of different communication technologies, selected communication technologies are compared in terms of their latency, throughput, reliability, power consumption and implementation costs. Since a number of smart grid applications share the same communication network, the performance of this communication network is also evaluated considering simultaneous operation of popular smart grid applications. Lastly, limitations of using several cyber security technologies based on different encryption methods - 3EDS (Triple Data Encryption Standard), AES (Advanced Encryption Standard), Blowfish, etc. - in deploying the proposed demand curtailment allocation strategy are analyzed.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Electrical Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bian, Desong
Chair dc:contributor.committeechair
  • Rahman, Saifur
Committee members dc:contributor.committeemember
  • Silva, Luiz A.
  • Ghandforoush, Parviz
  • Mili, Lamine M.
  • Pipattanasomporn, Manisa

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:9590
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/74930

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Bian, Desong. An Expert-based Approach for Demand Curtailment Allocation Subject to Communications and Cyber Security Limitations. doctoral thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/74930