Resources and Publications

Three new reports have been released as part of an Alliance to Save Energy (A2SE) research study into the potential for energy efficiency, demand side management and distributed generation in electricity network planning.

The findings of the first systematic national survey of Demand Management (DM) undertaken by electricity network service providers in Australia, the Survey of Energy Network Demand Management in Australia (SENDMA), are presented in the first report.

Summary Report

The Executive Summary summaries the research, key findings and implications for the energy sector in Australia that has been conducted by the Intelligent Grid Cluster (iGrid). The final reports for the seven projects are the culmination of a significant body of research into the economic, environmental and social impacts and benefits of the large-scale deployment of intelligent grid technologies and decentralised energy in Australian. The research provides a foundation for establishing an advanced electricity distribution network in Australia to meet the challenges of reducing carbon emissions and reining in the rising cost of power, while maintaining or improving reliability. Decentralised energy (DE) resources, which bring increased energy efficiency, peak demand management and distributed generation, will play a critical role in the transition to a low carbon economy.

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Project Reports

The reports show the outcomes of modelling the market benefits of large-scale DE deployment in the National Electricity Market. It has identified the network benefits of large-scale DE deployment in Australian electricity networks and how DE can be deployed to alleviate network congestion and defer network investment. The intention is to fully and appropriately value the economic contribution of the intelligent grid and compare it to conventional centralised generation. The research proposed many solutions to overcome the technical challenges of integrating distributed generation into the grid. The research has identified the social issues around the uptake of Decentralised Energy and explored the ways people connect with and understand energy and how this might be influenced by intelligent grid technologies.

Project 1. Control methodologies of distributed generation

Overview

The Project 1 research has focused primarily on the enhancement of stability of medium and low voltage power systems in the presence of Distributed Generation (DG) units. Distribution networks with DG units oscillate with a frequency around 3 Hz under certain operating conditions. DG units enhance damping of oscillatory modes by positively participating in oscillation. While this is a positive result for utilities who want to increase DG penetration, it is important that further investigations be undertaken into power quality and protection issues for higher penetration of DG units in distribution systems. Shunt compensation devices such as capacitor banks, SVCs and STATCOMs are normally installed for voltage stability enhancement. However, the placement of such compensating devices can have an influence on small signal stability. DG units installed with appropriate control mode in a network can be utilised to enhance small signal stability of the network so that distribution utilities don’t have to invest in expensive controllers. This project has developed a number of methodologies to determine the optimal location and size of synchronous and induction generator-based DG units and a new index was formulated for the steady state and post fault voltage recovery. 

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Research Reports

  • Paper Title: Control Methodologies of distributed generation for enhanced network stability and control – End of year report 2010

    Published by: The University of Queensland, St. Lucia, Brisbane

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  • Paper Title: Control methodologies of Distributed Generation for enhanced network stability and control – End of Year Report 30 July 2009

    Published by: The University of Queensland, St. Lucia, Brisbane

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  • Paper Title: Control methodologies of Distributed Generation for enhanced network stability and control – Interim Report 2009

    Published by: The University of Queensland, St. Lucia, Brisbane

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  • Paper Title: Control methodologies of Distributed Generation for enhanced network stability and control – Interim Report 2011

    Published by: The University of Queensland, St. Lucia, Brisbane

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Project 2. Market and economic modelling

Overview

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.

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Research Reports

  • Paper Title: CSIRO Intelligent Grid Cluster End of Year Final Report August 2009

    Published by: University of Queensland

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  • Paper Title: CSIRO Intelligent Grid Cluster End of Year Final Report July 2010 Milestone Report 4 & 5

    Published by: University of Queensland

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  • Paper Title: CSIRO Intelligent Grid Cluster Interim Report on whole project outcomes. Milestone Deliverable 6 December 2010

    Published by: University of Queensland

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  • Paper Title: CSIRO Intelligent Grid Cluster April 2011. Milestones 7 & 8: Combined Report

    Published by: University of Queensland

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  • Paper Title: CSIRO Intelligent Grid Cluster Interim Report 1 January 2009

    Published by: University of Queensland

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Project 3. Optimal siting and dispatch of distributed generators

Overview

Several important issues concerning optimal sitting and dispatch of distributed generators (DGs) are addressed in-depth in this project: 1) technical barriers and solutions associated with voltage and protection; 2) optimised use of DGs for reliability improvement; 3) under-frequency load shedding strategy in the presence of DGs; 4) optimal siting and sizing of DGs in distribution systems; 5) Generation scheduling with DGs; 6) risk control in transmission system planning with DGs; 6) sizing the DGs with life-cycle costing and greenhouse-gas abatement effects. Some key findings are detailed below:

  • DGs have challenges in integrating into existing distribution networks due to the capacity limitations, these can be minimised by strategically integrating resources of DGs.
  • A software program is developed that provides the most beneficial installed capacity for a particular distribution network in increased integration of DGs through cost-based technical analysis.
  • Technical barriers from an increased penetration of DGs are starting to arise in terms of voltage control. An algorithm is developed and simulations have demonstrated that it is effective.
  • The other key technical barrier to the connections of DGs is the impacts on conventional protection schemes. An efficient protection coordination scheme is developed.
  • As the penetration levels of DGs rise there is a growing concern about the reliable detection of high impedance faults. A method is presented with good detection precision of line high-impedance faults in the presence of DGs.
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Research Reports

  • Paper Title: Optimized control constraints and costs for wind, fuel cells, combustion generation

    Published by: Queensland University of Technology and Curtin University

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  • Paper Title: A report on quantification of network benefits from the deployment of Distributed Generation

    Published by: Queensland University of Technology and Curtin University

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  • Paper Title: A benefit comparison of Load Shedding versus use of Distributed Generation

    Published by: Queensland University of Technology and Curtin University

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  • Paper Title: A software development and simulation of generation and cost optimised controller

    Published by: Queensland University of Technology and Curtin University

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  • Paper Title: A report on life cycle costing, greenhouse gas abatement and optimal siting

    Published by: Queensland University of Technology and Curtin University

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Project 4. Institutional barriers, stakeholder engagement, economic modelling

Overview

This report has been developed by the research team at the Institute for Sustainable Futures based at the University of Technology, Sydney. There were four main areas of investigation in this project: Benefits of Decentralised Energy; Institutional barriers to DE and its solutions; the value of DE to networks- DANCE model; the Description and Costs of Decentralised Energy- the D-CODE model. DE has the potential to offer major cost savings and carbon emission reductions while securely and reliably meeting customer energy needs. The major benefits are affordability, sustainability, security and reliability. A key finding of the research is that Decentralised Energy has the potential to defer or reduce in expenditure on the transmission and distribution networks. Around one third of network investment, or $15 billion, is considered potentially avoidable if growth in peak demand was eliminated through measures such as Decentralised Energy including Distributed Generation, Energy Efficiency and peak Load Management.

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Research Reports

  • Paper Title: Mapping Network Opportunities for Decentralised Energy: The Dynamic Avoidable Network Cost Evaluation (DANCE) Model (Working Paper 4.4)

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Model Title: Outputs of the Dynamic Avoidable Network Cost Evaluation (DANCE) model

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Paper Title: Description and Costs and Decentralised Energy D-CODE Model Manual

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Model Title: Evaluating the Costs and Potential of Decentralised Energy

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Paper Title: Description and Costs and Decentralised Energy D-CODE Model Working Paper

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Paper Title: 20 Policy Tools for Developing Distributed Energy (Working Paper 4.2. Version 1.)

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Paper Title: Institutional Barriers to Intelligent Grid (Working Paper 4.1. Version 3)

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Paper Title: Stakeholder Consultation Report (Working Paper 4.5. Version 1)

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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  • Title: Evaluating the Costs and Potential of Decentralised Energy

    Published by: Institute for Sustainable Futures, University of Technology Sydney

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Project 5. Intelligent grid social impact

Overview

The central aim of this project involved assessing the implications of deploying IG-DE solutions against human, social, economic, political, cultural and environmental considerations.  The most significant theme to emerge is the high level of acceptance among energy (residential and SMEs) consumers and the network of energy stakeholders that IG-DE or ‘smart grid’ solutions is a genuine alternative to a centralized grid supply. While economic viability is a crucial impediment, proving that IG-DE can shift from the discourse of theorised benefits to validated investment opportunity is the key. Also a significant is that governments are attributed with the ultimate responsibility for policy direction, regulatory reform, coordination and incentivising all energy stakeholders. The paradox however, is the lack of trust placed in governments’ capacity to implement the IG-DE vision. While government leadership is desired, there is also the recognition of personal responsibility, where all sectors of society including community, business and the energy networks drive the vision through a combination of top down and bottom up processes.

To enable an IG-DE transformation, there is overwhelming support for community energy initiatives, community engagement and facilitation by government leadership, policy direction, regulatory reform and collaboration with the energy industry to ensure an economically viable sector.

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Research Reports

  • Paper Title: Stage 2: Small and Medium Enterprises Survey of Two Regional Communities

    Published by: Curtin University

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  • Paper Title: Chapter 4.3: Results & Analyses of Energy Stakeholder Interviews

    Published by: Curtin University

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  • Paper Title: Chapter 4.4: Results & Analyses of Energy Stakeholder Surveys

    Published by: Curtin University

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  • Paper Title: Section 5.4: Energy Stakeholder Surveys

    Published by: Curtin University

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Project 6. The intelligent grid in a new housing complex

Overview

The University of South Australia (UniSA) worked on Project 6- Intelligent Grid in a New Housing Development. The project aims to investigate the impacts of the introduction of energy efficiency measures and distributed generation on energy use patterns, greenhouse gas emissions, the electrical grid and consumer. The research also investigates the issues of ownership and control of distributed energy resources (i.e. local generation and loads) in residential houses as well as occupants’ attitude towards this new type of energy generation.

The focus of the research is the Lochiel Park Green Village, a master planned community that seeks to demonstrate that urban, medium density housing developments can have sustainable living as their core principle.

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Research Reports

  • Paper Title: The Intelligent Grid in a New Housing Development Period: July – December 2010 (PROGRESS REPORT)

    Published by: University of South Australia

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  • Paper Title: The Intelligent Grid in a New Housing Development Period: January ­ June 2010 (PROGRESS REPORT)

    Published by: University of South Australia

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  • Paper Title: The Intelligent Grid in a New Housing Development Period: March – June 2009. Milestone 3 and 4

    Published by: University of South Australia

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Project 7. Operational control and energy management

Overview

A number of Distributed Generation technologies can be integrated to form an independent electric grid to supply local loads in the absence of the main utility grid. Small electric grid like this are called microgrids. Microgrids are capable of operating connected to the main utility grid (grid-connected mode) or they can operate without the presence of a utility grid (islanded or autonomous mode) without compromising power quality. DGs, especially those based on renewable energy sources such as solar and wind can be effectively integrated into a microgrid to cater for rapid growth in demand.

The final report for Project 7- Operation Control and Energy Management discusses the challenges of microgrid operation such as grid stability, power management and protection. Solutions to overcome these challenges include new control, power management and protection strategies for a safe and reliable micro grid operation.

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Research Reports

  • Paper Title: M3: Control Strategies to ensure efficient, reliable and economic operation of the micro-grid.

    Published by: Queensland University of Technology

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  • Paper Title: M4: Microgrid Operation and Control Executive Summary

    Published by: Queensland University of Technology

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  • Paper Title: Switching Control Strategies for Distributed Generation

    Published by: Queensland University of Technology

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  • Paper Title: Meshed Microgrid Protection

    Published by: Queensland University of Technology

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