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The Australian National Electricity Market (NEM) is undergoing rapid change as utility-scale wind, solar and now battery storage technologies enter the market. The impact of these changes on the operation of the NEM is of interest to a potentially wide range of stakeholders including researchers, market participants, consultants and energy NGOs. De...
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... Generation availability for thermal plant is based on the historical availability of thermal plant in the NEM over using the NEMOSIS package and based on data from AEMO's NEMWEB repository (AEMO, 2022c; Gorman et al., 2018). In the absence of long-term historical data on wind and solar availability for modern turbines of the scale and form implemented in the NEM, a back-casting approach is adopted. ...
We consider the classical concern of why there is limited long-term hedging in electricity markets (the missing markets)... but ask the question of whether this challenge will persist in 'low-carbon' markets with lots of wind and solar.
To do this we adopt insights from insurance theory including the work of Carolyn Kousky and Roger Cooke who showed that there is an 'Unholy Trinity' of factors that makes tail risk hard to insure. Using this framework we found that when you consider the tail risk and financing constraints of a system dominated by gas and coal... the cost of defending a long-term hedge becomes extremely high. What then happens when you add a lot of wind, solar and storage?
Our core experimental result was interesting but also surprising - where adding "uncertain forms of generation like wind and solar" to a system could actually improve hedgeability and contracting. In reality all generation is uncertain - but the uncertainty patterns of low-carbon resources are fundamentally different to that of legacy forms of generation - and so the resultant portfolio is one that is more diverse in the tails - which given investor risk-aversion is relevant for hedging over the long term.
... Furthermore, NEMSEER adds significant value to users interested in deeper analysis through its documentation. It contains examples showing how users can analyse demand forecast errors and energy price convergence using pre-dispatch demand and price forecast data (obtained using NEMSEER) and historical actual NEM system and market data (obtained using NEMOSIS) (Gorman et al., 2018). Figure 1 is an output of one such example. ...
... global), they do not reflect dispatch outcomes in the presence of regional constraints. Offer and dispatch data were obtained using NEMOSIS (Gorman et al., 2018). generation -Section 3.1.2), ...
... Many existing flexible conventional resources (OCGT, reciprocating engines and hydro generation) submit dispatch inflexibility profiles to AEMO that contain the resource's time to start up and reach MSL, the MSL itself, the time required at minimum loading and the time taken to shut down (Australian Energy Market Operator, 2021b). The most frequently offered fast start inflexibility profile of a resource in 2020 was obtained using NEMOSIS (Gorman et al., 2018) and used to calculate its start-up rate, minimum up-time, MSL and shutdown rate. The minimum down-time for these resources was chosen to be equal to the minimum up-time. ...
... depending on the start state of the resource after being offline for its minimum downtime) obtained from GHD (2018) or Aurecon Australasia (2020). The shut-down rates for these resources were calculated based on actual shutdowns, or those of similar technology types, observed in AEMO dispatch data that was obtained using NEMOSIS (Gorman et al., 2018). BESS were dispatched by PLEXOS's arbitrage algorithm subject to charging and discharging efficiencies and maximum and minimum state of charge constraints that corresponded to those assumed within AEMO's 2020 Inputs and Assumptions workbook (Australian Energy Market Operator, 2020c). ...
Across several power systems with market frameworks, policy-makers are proposing that balancing flexibility requirements emerging during energy transition be addressed through new reserve product markets. However, these may introduce additional costs, constraints and complexity, and even encroach upon the functions of existing operational practices. Thus, policy-makers need to assess and compare flexibility design options, and quantifying system flexibility capabilities based on current and expected resource mixes can assist in achieving this. In this article, we offer a practical method to quantify the time-varying spectrum of upwards and downwards flexibility capabilities in systems, and subsequently apply it to historical and projected resource mixes in two regions of the Australian National Electricity Market. Our results suggest that with higher penetrations of renewable energy: (1) downwards flexibility margins can be exhausted around noon if wind and solar are unable or unwilling to provide it, (2) upwards flexibility becomes more scarce during morning and evening peak demand events and (3) a greater portion of upwards flexibility is provided by energy-limited resources. Given these trends, we recommend that policy-makers examine how existing operational practices can be augmented to elicit upwards flexibility provision, and that duration specifications and sustained footroom procurement be considered for reserve products.
... To model the grid pricing, we consider the distribution of the wholesale regional prices over the FY2018-19 for each state region of the Australian National Electricity Market (NEM) made available by Australian Energy Market Operator (AEMO) as part of its market information system. The data by AEMO was then filtered using the opensource tool ''NIMOSIS'', which is designed specifically for the Australian National Energy Market (Gorman et al., 2018). The tool is accessible on the Collaboration on Energy and Environmental Markets website. ...
The high variability and intermittency of wind and solar farms raise questions of how to operate electrolyzers reliably, economically, and sustainably using predominantly or exclusively variable renewables. To address these questions, we develop a comprehensive cost framework that extends to include factors such as performance degradation, efficiency, financing rates, and indirect costs to assess the economics of 10 MW scale Alkaline and PEM electrolyzers to generate hydrogen. Our scenario analysis explores a range of operational configurations, considering: (i) current and projected wholesale electricity market data from the Australian National Electricity Market (NEM), (ii) existing solar/wind farm generation curves and (iii) electrolyzer capital costs/performance to determine costs of H2 production in the near (2020-2040) and long-term (2030-2050). Furthermore, we analyze dedicated off-grid integrated electrolyzer plants as an alternate operating scenario, suggesting oversizing renewable nameplate capacity with respect to the electrolyzer to enhance operational capacity factors and achieving more economical electrolyzer operation.
... The statewide load in South Australia and Victoria has been estimated using 4s SCADA data publicly available through AEMO's NEMWeb portal [42], accessed using the NEMOSIS open source tool [43]. This data set contains 4s data for all registered generators and interconnectors in the NEM. ...
... Historical Frequency Control Ancillary Services (FCAS) data was also obtained through AEMO's NEMWeb portal [42], accessed using the NEMOSIS open source tool [43]. The data set obtained contains FCAS enablement for each NEM region over the period November 2017 to November 2018. ...
As distributed photovoltaics (PV) levels increase around the world, it is becoming apparent that the aggregate behavior of many small-scale PV systems during major power system disturbances may pose a significant system security threat if unmanaged. Alternatively, appropriate coordination of these systems might greatly assist in managing such disturbances. A key issue is PV behavior under extreme voltage events. PV connection standards typically specify aspects of inverter voltage behavior. However unresolved questions remain regarding compliance, ambiguity and transition between versions of these standards. In addition, how major voltage disturbances manifest in the low voltage network is complex, and analysis of operational system data could be particularly useful for establishing the behavior of distributed PV in the field. Our study utilizes 30 s operational PV generation data from 376 sites during two major voltage disturbances in Australia. Australia has one of the highest penetrations of distributed PV worldwide, and as such provides a useful case study. Results show that an aggregate ~30–40% reduction in distributed PV generation occurred during these events, but individual inverter behavior varied markedly. To the authors’ knowledge, this is the first time the aggregate response of distributed small-scale PV to voltage disturbances originating in the transmission system has been demonstrated. Four novel techniques for analyzing events are proposed. Results show a potential increase in system security service requirements as distributed PV penetrations grow. Our findings would seem to have major implications for development of composite load models used by power system operators and for contingency management.
... A multifactor sensitivity analysis feature was implemented in VBA to aid users in identifying drivers of uncertainty. Historical NEM wholesale price and renewable energy generation data is also made available in accompanying MS Excel workbooks, pre-formatted for use in MSAT, this data was originally sourced using NEMOSIS, an open-source data tool developed by Gorman et al. (2018). ...
Power Purchase Agreements (PPA) between end-users of electricity and renewable energy generators are of increasing significance in the Australian electricity sector. PPAs, depending on how they are structured, can allow end-users to achieve several objectives, including supporting renewable energy development, meeting corporate emissions reduction targets or mandated renewable energy requirements, accessing lower-cost electricity and managing cost uncertainty over the medium and long term. Previous work indicates that a wide variety of contract structures are being used to implement PPAs in Australia, while at the same time, many aspects of the future of the Australian electricity industry remain uncertain. This paper reports on a freely available MS Excel workbook that helps decision-makers assess a wide variety of potential PPA contract structures, their associated financial uncertainties and risks to future Australian electricity market developments. We have termed this, the Multi-factor Sensitivity Analysis Tool for PPAs (MSAT-PPA or MSAT for short). Contract for Difference PPAs are identified as of particular interest and the tool is demonstrated by exploring drivers of uncertainty for this type of PPA, using a hypothetical example, loosely modelled on the experience of the University of New South Wales (UNSW Sydney) with one such PPA. While contracting arrangements can vary considerably across jurisdictions, this analysis of Australian arrangements has wider relevance for other markets where PPAs are playing a role in driving new renewables deployment.
For restructured electricity industries undergoing energy transition, designing effective and efficient frequency control arrangements is a complex and ongoing task that requires appropriate configuration of controllers, generator technical connection requirements, market arrangements and wider policy settings. In this paper, we provide an overview and assessment of these arrangements in Australia’s National Electricity Market - a useful case study given its long-standing frequency control ancillary services markets, yet recent challenges in maintaining secure frequency control. We assess the performance of these evolving arrangements in delivering improved frequency control outcomes, with particular regard to growing renewable penetrations and evident tensions between mandatory requirements and market-based incentives. Based on this assessment, we draw out four key insights on designing frequency control arrangements as power system capabilities and needs change: (1) Understanding control action interactions, (2) Implementing efficient price formation and cost-allocation mechanisms, (3) Monitoring and assessing service provision to better align participant remuneration with service quality, and (4) Considering both regulatory and market mechanisms and their consequences and interactions. In particular, we discuss the trade-offs between effective and efficient outcomes, and provide arguments for more robust and forward-looking frequency control arrangements during energy transition.
Battery electrified public transit (BEPT), including buses and passenger ferries, is a promising solution to transport-related climate emissions and urban air pollution, but introduces potentially challenging large, coincident demand in the low-voltage distribution network. This paper presents a tool for estimating the energy and charging demand of electrified public transit using public data that is available in over 150 cities/states globally and demonstrates it in two case studies. The tool applies heuristic vehicle scheduling to existing public General Transit Feed Specification data to model the charging profiles and electricity consumption of BEPT for various charging regimes across different geographical scales. For the case study of New South Wales, Australia, the impacts of BEPT are most significant at the low-voltage network, where adding a battery-electric bus depot was found to increase the annual critical peak demand at the local zone substation in Summer by up to 17% while exacerbating demand during the daily evening peak period by 20–30%. Across the entire state of NSW, a full transition to BEPT increases annual electricity consumption by 1.28–1.34% and peak daily demand by 1–3%.
