From 2ce3d926a1ab98231fba5ca2d3dc4b8ceb6432e4 Mon Sep 17 00:00:00 2001 From: nick-gorman <40549624+nick-gorman@users.noreply.github.com> Date: Fri, 13 Jan 2023 15:10:25 +1100 Subject: [PATCH] delete paper files --- paper.bib | 250 ------------------------------------------------------ paper.md | 131 ---------------------------- plot.png | Bin 305005 -> 0 bytes 3 files changed, 381 deletions(-) delete mode 100644 paper.bib delete mode 100644 paper.md delete mode 100644 plot.png diff --git a/paper.bib b/paper.bib deleted file mode 100644 index 059a7bf..0000000 --- a/paper.bib +++ /dev/null @@ -1,250 +0,0 @@ -@software{reback2020pandas, - author = {{The pandas development team}}, - title = {{pandas-dev/pandas: Pandas}}, - month = feb, - year = 2020, - publisher = {Zenodo}, - version = {latest}, - doi = {10.5281/zenodo.3509134}, - url = {https://doi.org/10.5281/zenodo.3509134} -} - -@InProceedings{ mckinney-proc-scipy-2010, - author = { {W}es {M}c{K}inney }, - title = { {D}ata {S}tructures for {S}tatistical {C}omputing in {P}ython }, - booktitle = { {P}roceedings of the 9th {P}ython in {S}cience {C}onference }, - pages = { 56 - 61 }, - year = { 2010 }, - editor = { {S}t\'efan van der {W}alt and {J}arrod {M}illman }, - doi = { 10.25080/Majora-92bf1922-00a } -} - -@Article{ harris2020array, - title = {{Array programming with NumPy}}, - author = {Charles R. Harris and K. Jarrod Millman and St{\'{e}}fan J. - van der Walt and Ralf Gommers and Pauli Virtanen and David - Cournapeau and Eric Wieser and Julian Taylor and Sebastian - Berg and Nathaniel J. Smith and Robert Kern and Matti Picus - and Stephan Hoyer and Marten H. van Kerkwijk and Matthew - Brett and Allan Haldane and Jaime Fern{\'{a}}ndez del - R{\'{i}}o and Mark Wiebe and Pearu Peterson and Pierre - G{\'{e}}rard-Marchant and Kevin Sheppard and Tyler Reddy and - Warren Weckesser and Hameer Abbasi and Christoph Gohlke and - Travis E. Oliphant}, - year = {2020}, - month = sep, - journal = {Nature}, - volume = {585}, - number = {7825}, - pages = {357--362}, - doi = {10.1038/s41586-020-2649-2}, - publisher = {Springer Science and Business Media {LLC}}, - url = {https://doi.org/10.1038/s41586-020-2649-2} -} - -@misc{coin-orpython-mip, - title = {{coin-or/python-mip}}, - author = {H. G. Santos and T. A. M. Toffolo}, - year = {2021}, - publisher = {GitHub}, - journal = {GitHub repository}, - url = {https://github.com/coin-or/python-mip} -} - -@misc{psf, - title = {{Requests}}, - author = {{Python Software Foundation}}, - year = {2021}, - publisher = {GitHub}, - journal = {GitHub repository}, - url = {https://github.com/psf/requests} -} - -@misc{xmltodict, - title = {{xmltodict}}, - author = {M. Blech}, - year = {2021}, - publisher = {GitHub}, - journal = {GitHub repository}, - url = {https://github.com/martinblech/xmltodict} -} - -@misc{nempro, - title = {{NEMPRO}}, - author = {Gorman, Nicholas}, - year = {2021}, - publisher = {GitHub}, - journal = {GitHub repository}, - url = {https://github.com/UNSW-CEEM/NEMPRO} -} - -@misc{nemde, - title = {{NEM Dispatch Engine (NEMDE)}}, - author = {{Australian Energy Market Operator}}, - year = {2021}, - publisher = {Australian Energy Market Operator}, - url = {https://aemo.com.au/en/energy-systems/market-it-systems/electricity-system-guides/nemde-queue-service} -} - -@article{ringkjob2018review, - title={{A review of modelling tools for energy and electricity systems with large shares of variable renewables}}, - author={Ringkj{\o}b, Hans-Kristian and Haugan, Peter M and Solbrekke, Ida Marie}, - journal={Renewable and Sustainable Energy Reviews}, - volume={96}, - pages={440--459}, - year={2018}, - publisher={Elsevier}, - doi={10.1016/j.rser.2018.08.002} -} - -@article{chang2021trends, - title={{Trends in tools and approaches for modelling the energy transition}}, - author={Chang, Miguel and Thellufsen, Jakob Zink and Zakeri, Behnam and Pickering, Bryn and Pfenninger, Stefan and Lund, Henrik and {\O}stergaard, Poul Alberg}, - journal={Applied Energy}, - volume={290}, - pages={116731}, - year={2021}, - publisher={Elsevier}, - doi={10.1016/j.apenergy.2021.116731}, -} - -@article{fattahi2020systemic, - title={{A systemic approach to analyze integrated energy system modeling tools: A review of national models}}, - author={Fattahi, Amirhossein and Sijm, Jos and Faaij, Andr{\'e}}, - journal={Renewable and Sustainable Energy Reviews}, - volume={133}, - pages={110195}, - year={2020}, - publisher={Elsevier}, - doi={10.1016/j.rser.2020.110195}, -} - -@inproceedings{grozev2005nemsim, - title={{NEMSIM: Agent-based simulator for Australia's national electricity market}}, - author={Grozev, George and Batten, David and Anderson, Miles and Lewis, Geoff and Mo, John and Katzfey, Jack}, - booktitle={SimTecT 2005 Conference Proceedings}, - year={2005}, - organization={Citeseer} -} - -@misc{energy_exemplar_plexos_2021, - title = {{PLEXOS}® {Simulation} {Software}}, - url = {https://energyexemplar.com/products/plexos-simulation-software/}, - author = {{Energy Exemplar}}, - year = {2021}, -} - -@article{xenophon2018open, - title={{Open grid model of Australia’s National Electricity Market allowing backtesting against historic data}}, - author={Xenophon, Aleksis and Hill, David}, - journal={Scientific data}, - volume={5}, - number={1}, - pages={1--21}, - year={2018}, - publisher={Nature Publishing Group}, - doi={10.1038/sdata.2018.203} -} - -@article{mcconnell2013retrospective, - title={{Retrospective modeling of the merit-order effect on wholesale electricity prices from distributed photovoltaic generation in the Australian National Electricity Market}}, - author={McConnell, Dylan and Hearps, Patrick and Eales, Dominic and Sandiford, Mike and Dunn, Rebecca and Wright, Matthew and Bateman, Lachlan}, - journal={Energy Policy}, - volume={58}, - pages={17--27}, - year={2013}, - publisher={Elsevier}, - doi={10.1016/j.enpol.2013.01.052} -} - -@article{ventosa, - title={{Electricity market modeling trends}}, - author={Ventosa, Mariano and Baillo, Alvaro and Ramos, Andres and Rivier, Michel}, - journal={Energy Policy}, - volume={33}, - pages={897--913}, - year={2005}, - publisher={Elsevier} -} - -@misc{ANEMWorkingReport, - title = {{Energy Economics and Management Group Working Paper 2-2015}}, - author = {P. Wild and W. P. Bell and J. Foster and M. Hewson}, - year = {2016}, - publisher = {School of Economics The University of Queensland}, - url = {https://economics.uq.edu.au/research/research-centres-and-groups/energy-economics-and management-group/} -} - -@misc{IES, - title = {{Prophet Electricity Market Model}}, - author = {{Intelligent Energy Systems}}, - year = {2021}, - publisher = {Intelligent Energy Systems}, - url = {http://products.iesys.com/Prophet/Index} -} - -@misc{mountain, - title = {{Ensuring reliable electricity supply in Victoria to 2028: suggested policy -changes}}, - author = {B. R. Mountain and S. Percy}, - year = {2019}, - publisher = {Victoria Energy Policy Centre, Victoria University, Melbourne, Australia}, - url = {https://www.vepc.org.au/reports-and-working-papers} -} - -@misc{wood, - title = {{Go for net zero}}, - author = {T. Wood and J. Ha}, - year = {2021}, - publisher = {Grattan Institute}, - url = {https://grattan.edu.au/wp-content/uploads/2021/04/Go-for-net-zero-Grattan-Report.pdf} -} - -@misc{faststart, - title = {{FAST-START INFLEXIBILITY PROFILE PROCESS DESCRIPTION}}, - author = {{Australian Energy Market Operator}}, - year = {2014}, - publisher = {{Australian Energy Market Operator}}, - url = {https://www.aemo.com.au/-/media/Files/PDF/Fast_Start_Unit_Inflexibility_Profile_Model_October_2014.pdf} -} - -@misc{fcasmodel, - title = {{FCAS Model in NEMDE}}, - author = {{Australian Energy Market Operator}}, - year = {2017}, - publisher = {{Australian Energy Market Operator}}, - url = {https://aemo.com.au/-/media/Files/Electricity/NEM/Security_and_Reliability/Dispatch/Policy_and_Process/2017/FCAS-Model-in-NEMDE.pdf} -} - -@misc{lossfactors, - title = {{Regions and Marginal Loss Factors: FY 2021-22}}, - author = {{Australian Energy Market Operator}}, - year = {2021}, - publisher = {{Australian Energy Market Operator}}, - url = {https://aemo.com.au/-/media/files/electricity/nem/security_and_reliability/loss_factors_and_regional_boundaries/2021-22/marginal-loss-factors-for-the-2021-22-financial-year.pdf?la=en} -} - -@misc{constraintviolation, - title = {{SCHEDULE OF CONSTRAINT VIOLATION PENALTY FACTORS}}, - author = {{Australian Energy Market Operator}}, - year = {2017}, - publisher = {{Australian Energy Market Operator}}, - url = {https://www.aemo.com.au/-/media/files/electricity/nem/security_and_reliability/congestion-information/2016/schedule-of-constraint-violation-penalty-factors.pdf} -} - -@misc{treatmentlossfactors, - title = {{TREATMENT OF LOSS FACTORS IN THE NATIONAL ELECTRICITY MARKET}}, - author = {{Australian Energy Market Operator}}, - year = {2012}, - publisher = {{Australian Energy Market Operator}}, - url = {https://aemo.com.au/-/media/files/electricity/nem/security_and_reliability/loss_factors_and_regional_boundaries/2016/treatment_of_loss_factors_in_the_nem.pdf?la=en} - -} - -@misc{nemfactsheet, - title = {{FACT SHEET: The National Electricity Market}}, - author = {{Australian Energy Market Operator}}, - year = {2020}, - publisher = {{Australian Energy Market Operator}}, - url = {https://aemo.com.au/-/media/files/electricity/nem/national-electricity-market-fact-sheet.pdf} -} \ No newline at end of file diff --git a/paper.md b/paper.md deleted file mode 100644 index 9c01b09..0000000 --- a/paper.md +++ /dev/null @@ -1,131 +0,0 @@ ---- -title: 'Nempy: A Python package for modelling the Australian National Electricity Market dispatch procedure' - -tags: - - Python - - electricity markets - - economic dispatch - - Australian National Electricity Market - - NEM - - dispatch -authors: - - name: Nicholas Gorman - affiliation: "1, 3" - - name: Anna Bruce - affiliation: "1, 3" - - name: Iain MacGill - affiliation: "2, 3" -affiliations: - - name: School of Photovoltaics and Renewable Energy Engineering, University of New South Wales, Australia - index: 1 - - name: School of Electrical Engineering and Telecommunications, University of New South Wales, Australia - index: 2 - - name: Collaboration on Energy and Environmental Markets (CEEM), University of New South Wales, Australia - index: 3 -date: 16 August 2021 -bibliography: paper.bib ---- - -# Summary - -Nempy is a python package for modelling the dispatch procedure of the Australian National Electricity Market (NEM). -Electricity markets are a way of coordinating the supply of electricity by private firms. The NEM is a gross pool spot -market that operates on 5 min dispatch basis [@nemfactsheet]. Described simply, this means all generators wishing to sell electricity -must bid into the market every 5 minutes, market clearing proceeds by calculating the cheapest combination of generator -operating levels to meet forecast demand at the end of the 5 minute dispatch interval. The price of electricity is set as the -marginal cost of generation, which, under a simple market formulation, would be the cost of the next generation bid to be -dispatched if demand for electricity were to increase. Real-world formulations require significant additional adjustment -in order to manage the technical complexity of securely and reliably operating an electricity grid. For example, in the -case of the NEM additional markets for ancillary services have been introduced. One set of ancillary markets that have -been integrated into the market dispatch procedure are the Frequency Control Ancillary Services (FCAS) markets. In these -markets generators compete to provide the ability to rapidly change generation levels in order to control the grid frequency. -Nempy is flexible in that it allows for the formulation of very simple market models, for the formulation of market models -of near real-world complexity, and at the various levels of intermediate complexity. Simple models can be constructed -using just generator bids and electricity demand, so called bid stack models. More complete models can be constructed by -using the inbuilt features to create multiple market regions, ramp rate limits, loss factors, FCAS markets, FCAS trapezium -constraints, dynamic interconnector loss models, generic constraints and fast start dispatch inflexibility profiles. -Outputs include market clearing prices, generator and scheduled load dispatch targets, FCAS enablement levels, unit FCAS -availability levels, interconnector flows, interconnector losses and region net inflows. Nempy is written in Python 3, -and uses a relatively small number of first-order dependencies; pandas [@reback2020pandas; @mckinney-proc-scipy-2010], -Numpy [@harris2020array], MIP-Python [@coin-orpython-mip], xmltodict [@xmltodict], and Requests [@psf]. - -# Statement of need - -In modern industrialised economies, the electricity sector plays a key role in societal welfare and progress, yet -commonly is also associated with major environmental harms, particularly where primary energy is sourced mainly through -the burning of fossil fuels. As such, all of us are stakeholders in the continued successful operation of the -electricity industry, while it transitions to cleaner energy sources, and beyond. Computer models are often used to -study the operation, interactions and potential future direction of the electricity sector, review papers highlight the -large body of work in this space [@ringkjob2018review; @chang2021trends; @fattahi2020systemic]. Such tools are, -invariably, simplifications of the underlying processes of electricity industry operation and investment for reasons -including the underlying complexity of the processes and the difficulty of gathering representative data. Commonly they -tackle only a subset of the decision making that must operate from milliseconds (for example, under frequency relay -trips) through to decades (investment in large generation units with long lead times). A particularly challenging and -key task is that of operational dispatch – setting generator outputs and controllable network elements to meet expected -demand over the next five to thirty minutes, and minimising costs while ensuring secure and reliable operation. To the -best of the author's knowledge `Nempy` is the only open-source software that provides a detailed model of the NEM's -dispatch procedure. Other more generalised models of the NEM [@grozev2005nemsim; @mcconnell2013retrospective; -@ANEMWorkingReport; @mountain; @wood] or commercial tools such as PLEXOS [@energy_exemplar_plexos_2021] and Prophet -[@IES] are used to model NEM dispatch, at various levels of complexity, but are not open-source. More recent work by -Xenophon and Hill provides open-source code and data for modelling the NEM, but the dispatch functionality does not -include many of the NEM wholesale market features [@xenophon2018open]. - -Nempy has been designed as a flexible model of the NEM's dispatch procedure and to be re-usable in a number of -contexts. The software is aimed at analysts and modellers studying the NEM, either in industry or academia. It can be -used as is, or as a building block in a larger modelling tool. Some potential use cases are outlined below: - -1. As a tool for studying the dispatch process itself. Models of any energy system or electricity market are necessarily -simplifications, however, to improve model performance it is often desirable to add additional detail. Nempy can be used -to study the impact of different simplifications on modelling outcomes, and thus provide guidance on how model -performance could be improved by adding additional detail. Figure 1 shows a simple example of such an analysis. The price -results from the New South Wales region for 1000 randomly selected intervals in the 2019 calendar year are shown. When -Nempy is configured with a full set of market features price results closely match actual prices. When the FCAS -markets and generic constraints (network and security) are removed from the model, results differ significantly. Resorting -the results of the simpler market model, we can see that both models produce a similar number of medianly priced -intervals. However, the highest and lowest priced intervals of the simpler model are significantly lower. The average -historical price is 81.4 $/MWh, the average price of the full featured model is 81.3 $/MWh, and the average price of the -simpler model is 75.0 $/MWh. The close match between the results of the full featured model and actual prices allows -for the attribution of the deviation of the simpler model explicitly to the simplifications that have been made. - -![Dispatch price results from the New South Wales region for 1000 randomly selected intervals in the 2019 calendar year. - The actual prices, prior to scaling or capping, are also shown for comparison. Results from two Nempy models are - shown, one with a full set of dispatch features, and one without FCAS markets or generic constraints (network and - security constraints). Actual prices, results from the full featured model, and the simpler model are shown in - descending order for actual prices, results from the simpler model are also shown resorted.\label{fig:example}](plot.png) - -2. As a building block in agent based market models. Agent based models can be used to study electricity market -operation, and are particularly useful in modelling both the competitive nature of electricity markets and their complex -operational constraints [@ventosa]. In such models, agents must interact with a modelled environment, and a key part of that -environment is the market dispatch process. Thus, Nempy could be useful as a building block to create agent based models -of the NEM, and play a role in answering various questions about market operational outcomes. Such questions could -include: - - * How does changing the demand for electricity affect market outcomes? - * How does the entry of new generating technologies affect market outcomes? - * How do patterns of generator ownership affect market outcomes? - - Of course, another necessary component of agent based models are the behavioural models of the agents, a prototype - behavioural model of NEM participants is being developed as part of the NEMPRO project [@nempro]. - -3. To answer counter factual questions about historical dispatch outcomes. For example: - - * What would have been the impact on market dispatch if a particular network constraint had not been present? - * How would have dispatch outcomes differed if a unit had offered a different bid into the market? - - The answers to such questions have direct, and potentially large, financial implications for market participants. - AEMO offers access to a production version of the market dispatch engine to allow participants to answer such questions - [@nemde]. However, access is restricted to registered participants and is provided at a cost of $15,000 per year. - Additionally, users of this service are not provided with a copy of the dispatch engine, but access it by submitting - input files to AEMO. This prevents the use of this service to answer questions about how changes to the dispatch - process, rather than the inputs, would affect dispatch outcomes. In contrast, access to Nempy is not restricted, it is - free to use, and is open to modification. - -4. As a reference implementation of the NEM's dispatch procedure. While the Australian Energy Market Operator (AEMO) -has published several documents that describe aspects of the dispatch process [@fcasmodel; @faststart; @lossfactors; -@constraintviolation; @treatmentlossfactors], our experience developing Nempy has indicated that key -implementation details are often missing from the publicly available documentation. Through a process of testing various -implementation options, where the documentation was not explicit, Nempy has been refined in an attempt to better reflect -the actual dispatch procedure. As a result, Nempy is a useful additional reference for analysts and modellers -looking to understand the NEM's dispatch procedure. - -# References \ No newline at end of file diff --git a/plot.png b/plot.png deleted file mode 100644 index 58510d4c4cb3d2dc33c5b08a39727bacf890cee0..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 305005 zcmdqJg?I5Q!lqq=#;#Rl2)|RzXDp8A=+YTVQAgP)fRIXiz$a z&Y{jT`~AN6Z1;Emg2Q!TjKgo9SkJxg`(EqugQ~JD(G7|l5D0__CMTs1f!x@GK(1(A zy9!>R6B^C|zg>5f({+JBIO*}<7d$h?+#!&^ATX(Cnx128limiJZokjB4g%ii1Uy6h z&gB2D*uAapNA23l!Na1Upkz~CK{!%OxXWQP-i_>@kB@Mu zG@)`V*#5>8X*J8kA4jL$;s#g0kedewdWq16d$I5=CiV)Z^d2R;nD=;#(q8}r`v2Qk zfKZlP2SSsjJ!fx(&Z;Ow)Sgo~+o-xhGn#TDtmE>(rfVDj(8dw-ZMHhq z?}=eXMxEYZW@X9$eOu^IG5x^VLz|g$l|sxLMx_X(WGI1mwt((_6ucAW;fSlY%TWB+ zcvIEBmxdv29de4+U=tA*4|{HD}*paX$>ZcM5Z6lNFy^+QVW>^5?H`~(Xy zohDU>w1Pn0@)v^pVFCL7a|W^(TME^f{`CWWIdZzPc}c5tJ{;Hg(6ro`h$FjbF^t0h 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