Maximising the benefit of distributed wind generation through intertemporal active network management

Simon Gill

Research output: ThesisDoctoral Thesis

Abstract

The objective of the thesis is to answer the questions: How can energy storage and flexible demand be scheduled in a second-generation Active Network Management scheme representing the next stage of Smart Grid deployment in the UK? And how should they be operated to gain most benefit from distributed wind generation? To answer these questions the thesis develops and uses tools to study the optimisation of such schemes. The tools include a Dynamic Optimal Power Flow algorithm which combines a full AC-network model with the first fully flexible model of energy storage in this context and with a detailed model for demand flexibility. The model also includes the first implementation of principles-of-access in an optimal power flow, as well as the first detailed study of the role of energy storage and flexible demand in managing thermal limits and reducing curtailment of distributed wind generation. The thesis also develops the theory of Dynamic Locational Marginal Pricing based on the economic information contained in an optimal solution to a Dynamic Optimal Power Flow. Finally, the thesis goes on to apply Dynamic Optimal Power Flow to a real case study representing a deployed UK Smart Grid. The thesis reaches a number of conclusions regarding operation of energy storage and flexible demand focusing on the role of losses (both electrical and storage), and the impact on the monetary flows. In addition it quantifies the ability of flexible demand and energy storage to reduce the cost of operating a system, and how that cost reduction impact on consumer payments.
LanguageEnglish
QualificationPhD
Awarding Institution
  • University Of Strathclyde
Supervisors/Advisors
  • Ault, Graham, Supervisor
  • Kockar, Ivana, Supervisor
Publisher
Publication statusPublished - 2014

Fingerprint

Active networks
Network management
Energy storage
Cost reduction
Costs
Economics

Keywords

  • wind generation
  • optimal power flow
  • energy storage
  • energy system

Cite this

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title = "Maximising the benefit of distributed wind generation through intertemporal active network management",
abstract = "The objective of the thesis is to answer the questions: How can energy storage and flexible demand be scheduled in a second-generation Active Network Management scheme representing the next stage of Smart Grid deployment in the UK? And how should they be operated to gain most benefit from distributed wind generation? To answer these questions the thesis develops and uses tools to study the optimisation of such schemes. The tools include a Dynamic Optimal Power Flow algorithm which combines a full AC-network model with the first fully flexible model of energy storage in this context and with a detailed model for demand flexibility. The model also includes the first implementation of principles-of-access in an optimal power flow, as well as the first detailed study of the role of energy storage and flexible demand in managing thermal limits and reducing curtailment of distributed wind generation. The thesis also develops the theory of Dynamic Locational Marginal Pricing based on the economic information contained in an optimal solution to a Dynamic Optimal Power Flow. Finally, the thesis goes on to apply Dynamic Optimal Power Flow to a real case study representing a deployed UK Smart Grid. The thesis reaches a number of conclusions regarding operation of energy storage and flexible demand focusing on the role of losses (both electrical and storage), and the impact on the monetary flows. In addition it quantifies the ability of flexible demand and energy storage to reduce the cost of operating a system, and how that cost reduction impact on consumer payments.",
keywords = "wind generation, optimal power flow, energy storage, energy system",
author = "Simon Gill",
year = "2014",
language = "English",
publisher = "University of Strathclyde",
school = "University Of Strathclyde",

}

Maximising the benefit of distributed wind generation through intertemporal active network management. / Gill, Simon.

University of Strathclyde, 2014. 340 p.

Research output: ThesisDoctoral Thesis

TY - THES

T1 - Maximising the benefit of distributed wind generation through intertemporal active network management

AU - Gill, Simon

PY - 2014

Y1 - 2014

N2 - The objective of the thesis is to answer the questions: How can energy storage and flexible demand be scheduled in a second-generation Active Network Management scheme representing the next stage of Smart Grid deployment in the UK? And how should they be operated to gain most benefit from distributed wind generation? To answer these questions the thesis develops and uses tools to study the optimisation of such schemes. The tools include a Dynamic Optimal Power Flow algorithm which combines a full AC-network model with the first fully flexible model of energy storage in this context and with a detailed model for demand flexibility. The model also includes the first implementation of principles-of-access in an optimal power flow, as well as the first detailed study of the role of energy storage and flexible demand in managing thermal limits and reducing curtailment of distributed wind generation. The thesis also develops the theory of Dynamic Locational Marginal Pricing based on the economic information contained in an optimal solution to a Dynamic Optimal Power Flow. Finally, the thesis goes on to apply Dynamic Optimal Power Flow to a real case study representing a deployed UK Smart Grid. The thesis reaches a number of conclusions regarding operation of energy storage and flexible demand focusing on the role of losses (both electrical and storage), and the impact on the monetary flows. In addition it quantifies the ability of flexible demand and energy storage to reduce the cost of operating a system, and how that cost reduction impact on consumer payments.

AB - The objective of the thesis is to answer the questions: How can energy storage and flexible demand be scheduled in a second-generation Active Network Management scheme representing the next stage of Smart Grid deployment in the UK? And how should they be operated to gain most benefit from distributed wind generation? To answer these questions the thesis develops and uses tools to study the optimisation of such schemes. The tools include a Dynamic Optimal Power Flow algorithm which combines a full AC-network model with the first fully flexible model of energy storage in this context and with a detailed model for demand flexibility. The model also includes the first implementation of principles-of-access in an optimal power flow, as well as the first detailed study of the role of energy storage and flexible demand in managing thermal limits and reducing curtailment of distributed wind generation. The thesis also develops the theory of Dynamic Locational Marginal Pricing based on the economic information contained in an optimal solution to a Dynamic Optimal Power Flow. Finally, the thesis goes on to apply Dynamic Optimal Power Flow to a real case study representing a deployed UK Smart Grid. The thesis reaches a number of conclusions regarding operation of energy storage and flexible demand focusing on the role of losses (both electrical and storage), and the impact on the monetary flows. In addition it quantifies the ability of flexible demand and energy storage to reduce the cost of operating a system, and how that cost reduction impact on consumer payments.

KW - wind generation

KW - optimal power flow

KW - energy storage

KW - energy system

M3 - Doctoral Thesis

PB - University of Strathclyde

ER -