Market and Economic Modelling of the Intelligent Grid: 1st Interim Report 2009

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.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

Network-Aware Electric Vehicle Coordination for Vehicle-to-Anything Value Stacking Considering Uncertainties

The increased adoption of electric vehicles (EVs) has led to the development of vehicle-to-anything (V2X) technologies, including vehicle-to-home (V2H), vehicle-to-grid (V2G), and energy trading of EVs in the local grid. The EV coordination can provide value to the grid and generate benefits for EVs. However, network constraints and uncertainties in renewable energy and demand pose significant challenges to EV coordination and restrict the realization of these benefits. This paper develops a rolling-horizon optimization problem for V2X value stacking to fully unlock the value of EV coordination, considering power network constraints (such as voltage limits) and uncertainties in the energy system. By coordinating EVs to perform V2H, V2G, and energy trading, our approach exploits the most valuable services in real-time. We also analyze the expected extra costs caused by the prediction errors to evaluate the impact of uncertainties on V2X value stacking. We validate our value-stacking model using real data from Australia's National Electricity Market (NEM), ISO New England (ISO-NE), and New York ISO (NY-ISO) in the US. The results show that V2X value stacking achieves significant benefits to EVs through energy cost reduction. The uncertainty in the load has a higher impact on the value-stacking performance than PV generation, indicating the importance of load prediction.Comment: The 59th annual IEEE Industrial and Commercial Power System Technical Conference (I&CPS 2023

Modelling the Electricity and Natural Gas Sectors for the Future Grid: Developing Co-Optimisation Platforms for Market Redesign

This report provides detail on the modelling and scenario frameworks for the economic analysis of the Future Grid. These frameworks and modelling platforms have been constructed to support the Future Grid Cluster in examining policy and market issues which will affect the electricity and natural gas markets in Australia. Initially we provide an overview of the co-optimisation and expansion of transmission networks and electricity generation for the future grid. In this section we outline not only the key mechanisms and analyses required, but also how we have and will continue to collaborate with the other projects within the Future Grid Cluster. In section 3 we provide an extensive analysis of the electricity market modelling platform PLEXOS. This section will outline, not only the mechanistic components of modelling electricity markets, but also some of the assumptions which are required to examine issues such as generation investment under uncertainty. The following section is a discussion of the natural gas modelling platform ATESHGAH. This model has been in construction for several years prior to the commencement of the Future Grid Cluster and represents a significant shift in gas market modelling methodology for Australia, compared to previous approaches. This model is capable of examining multiple issues associated with policy, market, economic, and physical aspects of gas production, transmission, sale and liquefied natural gas (LNG) export simultaneously. We have used this model to examine how Australia’s eastern gas market could be affected by the commencement of LNG exports from Curtis Island in 2015/16. In the remaining section, we present the scenario modelling framework as an overview and present some initial results for Scenario 1: Set and Forget. These results represent the first set of simulations and should thus be viewed as an initial attempt to undertake the large search space that the four scenarios evaluated in the Future Grid Forum encompass

Project 3: Economic and Investment Models For Future Grids Deliverable 2: The Scenarios

This chapter sets out the design of a scenario framework for the CSIRO Future Grid Cluster’s Project 3. It sets out how the various influences, or driving forces, are separated into four categorised. These being: Policy, States of the World, Sensitivities, and Linkages. The first two, policy, and states of the world, are then further broken down into two sub-categories: supply side influences, and demand side influences. Additionally, we take into account the reports from the CSIRO’s Future Grid Forum (CFGF), describing the comprehensive supply chain end-to-end study that used four major scenarios that are related to the scenario framework described her to be used in this cluster. The Forum also conducted sensitivities around these four scenarios. In section 1.3 of this document we describe the relationship between the CFGF scenarios and our scenario framework

Economic and investment models for future grids: Final Report Project 3

This final Future Grid Cluster Project 3 report provides the deployment of key modelling results and the identification of strategic priorities for stakeholders. The purpose of the University of Queensland’s project has been to create “Economic and Investment Models for the Future Grid” and the primary objectives are as follows: Provide broad understanding of how the electricity sector will need to change in a carbon constrained world. This transition to a lower emissions intensive technology base will require significant structural and regulatory reform to the energy markets; Development of quantitative methods to analyse how price levels and volatility on the wholesale electricity market are affected by changes to the transmission network structure and technology deployment; Implement modelling platforms which can inform stakeholders in the energy market of how changing network structure and electricity generation technology effects electricity prices; Develop market simulation platforms for natural gas to gain a better understanding of how changing the fuel and technology mixes will affect the power delivery process; Develop a scenario planning tool set for future electricity market modelling. This deliverable 6 reports the final analysis and results for the Future Grid project for the University of Queensland (UQ). It is also intended to highlight the progress made on the following topics: Modelling the National Electricity Market under fuel price uncertainty and the shift from coal to gas as the primary fuel source in the generation fleet.The tools developed to model the east coast gas market are discussed in the previous deliverable report [1]. The planning and scenario development is discussed in brief below (section 2) and in [2-4]; Modelling the rise Renewable Energy with a proactive consumer base (“Prosumer”) and the effects on the electricity market. The details of proactive consumers affect electricity markets and the development of modelling techniques to accommodate this new consumer class are detailed more fully in [5, 2, 6, 4, 7]. This report summarises the work carried out by the Project 3 team and a separate report details the work of Future Grid Cluster and its interconnections and progress by other projects. The work carried out by this team is also summarized by several working papers available on the Energy Economics and Management Group website . Details of how this and other projects within the cluster have co-contributed to addressing the transition to a carbon constrained future is detailed in its final summary document

Modelling the Electricity and Natural Gas Sectors for the Future Grid: Developing Co-Optimisation Platforms for Market Redesign

This report provides detail on the modelling and scenario frameworks for the economic analysis of the Future Grid. These frameworks and modelling platforms have been constructed to support the Future Grid Cluster in examining policy and market issues which will affect the electricity and natural gas markets in Australia. Initially we provide an overview of the co-optimisation and expansion of transmission networks and electricity generation for the future grid. In this section we outline not only the key mechanisms and analyses required, but also how we have and will continue to collaborate with the other projects within the Future Grid Cluster. In section 3 we provide an extensive analysis of the electricity market modelling platform PLEXOS. This section will outline, not only the mechanistic components of modelling electricity markets, but also some of the assumptions which are required to examine issues such as generation investment under uncertainty. The following section is a discussion of the natural gas modelling platform ATESHGAH. This model has been in construction for several years prior to the commencement of the Future Grid Cluster and represents a significant shift in gas market modelling methodology for Australia, compared to previous approaches. This model is capable of examining multiple issues associated with policy, market, economic, and physical aspects of gas production, transmission, sale and liquefied natural gas (LNG) export simultaneously. We have used this model to examine how Australia’s eastern gas market could be affected by the commencement of LNG exports from Curtis Island in 2015/16. In the remaining section, we present the scenario modelling framework as an overview and present some initial results for Scenario 1: Set and Forget. These results represent the first set of simulations and should thus be viewed as an initial attempt to undertake the large search space that the four scenarios evaluated in the Future Grid Forum encompass