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mdpi.com
article
https://www.mdpi.com/1996-1073/14/5/1425
No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal. # Open Source Modelling and Simulation of the Nordic Hydro Power System†. In this paper, we present the results from the development and the simulation of a hydro power model for Sweden and Norway, using SpineOpt software and openly available data. We employ (i) hydrological and market data from the Nordic region and (ii) the abstract representation of the multi-vector modelling and simulation engine SpineOpt, to compile an open-source model of a large portion of the hydro power plants of the Nordic region, for conducting realistic hydro power generation studies.
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en.wikipedia.org
article
https://en.wikipedia.org/wiki/Open_energy_system_models
# Open energy system models. | icon | This article **incorporates text from a large language model, which is prohibited in Wikipedia articles**. **Open energy-system models** are energy-system models that are open source. Energy-system models are often applied to questions involving energy and climate policy. Energy regulators and system operators in Europe and North America began to adopt open energy-system models for planning purposes in the early‑2020s. Open models and open data are increasingly being used by government agencies to guide the develop of net‑zero public policy as well. The open energy modeling projects listed here fall exclusively within the bottom-up paradigm, in which a model is a relatively literal representation of the underlying system. The use of open energy-system models and open energy data represents one attempt to improve the transparency, comprehensibility, and reproducibility of energy system models, particularly those used to aid public policy development. As of 2017, the European Commission now supports several open source energy system modeling projects to aid the transition to a low-carbon energy system for Europe.
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osti.gov
official
https://www.osti.gov/biblio/code-66918
https://doi.org/10.11578/dc.20211112.1` 🗎 Copy to clipboard `Mitra, Bhaskar, Gallego-Calderon, JuanF., Elliott, ShilohN, Mosier, ThomasM, & Bastidas Pacheco, CamiloJose (2021). https://doi.org/10.11578/dc.20211112.1` 🗎 Copy to clipboard `Mitra, Bhaskar, Gallego-Calderon, JuanF., Elliott, ShilohN, et al., "Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series," (2021), https://doi.org/10.11578/dc.20211112.1` 🗎 Copy to clipboard `@misc{osti_code-66918, author = {Mitra, Bhaskar and Gallego-Calderon, JuanF. and Elliott, ShilohN and Mosier, ThomasM and Bastidas Pacheco, CamiloJose}, title = {Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series}, annote = {Hydropower is one of the most mature forms of renewable energy generation. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.}, doi = {10.11578/dc.20211112.1}, url = {https://www.osti.gov/biblio/code-66918}, place = {United States}, year = {2021}, month = {10}}` 🗎 Copy to clipboard. `Mitra, Bhaskar, Gallego-Calderon, JuanF., Elliott, ShilohN, et al., "Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series," (2021), https://doi.org/10.11578/dc.20211112.1`.
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nlr.gov
official
https://www.nlr.gov/research/software
# Software. For the most current listing of NLR-developed open-source software, see U.S. Department of Energy Office of Scientific and Technical Information's DOE CODE database. | https://github.com/NREL/SDOM | SDOM: Storage Deployment Optimization Model | SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined energy target. The building XML model is the text input file to the preprocessor that contains a minimal set of high-level parameters to describe the building type, geometry, loads, and systems. The preprocessor constructs the resulting EnergyPlus building model by automatically generating and connecting all of the required EnergyPlus objects based on a set of built-in modeling assumptions.
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github.com
article
https://github.com/energy-modelling-toolkit/hydro-power-database
## Repository files navigation. map of hydro-power plants. The development of this dataset started as an output of the Energy work package of the Water-Energy-Food-Ecosystems (WEFE) Nexus project at the European Commission's Joint Research Centre (JRC). This dataset has been created for power system modelling purposes and it is based on publicly available sources. This dataset tries to collect some basic information on all the European hydro-power plants. This dataset is released under CC-BY-4.0 license. This dataset is an open project and it is not an official product of the European Commission. If you have any question or comment the best way would be to add a post in the Issues to keep track of open and closed issues/questions. If you want to contribute please send me an email or submit a Pull Request on this repository. The dataset contains 4264 hydro-power plants. The list of the used sources is here:.
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anl.gov
official
https://www.anl.gov/hydropower/projects-modeling-tools
Advanced Pumped Storage Hydropower. Detailed models of advanced pumped storage hydropower (PSH) plants to analyze the role and value of PSH in the power system.
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pypsa.org
article
https://pypsa.org
# Welcome to the PyPSA Community! PyPSA stands for Python for Power System Analysis. # Optimize the network. ## PyPSA Framework. ### An open-source Python framework for optimising modern power systems with conventional generators, renewable energy, storage, and multi-sector coupling - designed for researchers and planners. ## Framework and Tools. Python for Power System Analysis - the core framework for simulating and optimising modern power systems. ### Open Energy System Models built with PyPSA. A flexible Python-based open optimisation model to study energy system futures around the world. A Sector-Coupled Open Optimisation Model of the European Energy System. An Open-Source Energy System Optimization Model for the United States. ### PyPSA: Python for power system analysis. ### On the history and future of 100% renewable energy systems research. PyPSA is a framework for optimising and simulating modern power and energy systems. PyPSA has an active community of users and developers on Discord and elsewhere who can help you with questions and issues.
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eng-tips.com
article
https://www.eng-tips.com/threads/best-or-free-potable-water-system-modeling-s…
You can find information about the proposed (but apparently stalled) open source project to enhance EPANET here: https://github.com/USEPA/