Showing 25 pages using this property.
P | |
PowerMatcher + | "The PowerMatcher is a smart grid coordination mechanism. It balances distributed energy resources (DER) and (flexible) loads ... The PowerMatcher core application provides the market mechanism for the determination of the market equilibrium, while the devices work as actors for demand and/or supply" |
PowerSimulations.jl + | Flexible, modular, and scalable package for power system quasi-static analysis with sequential problem specification capabilities. |
PowerSystems.jl + | The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing. |
Pvlib python + | pvlib python is a community supported tool that provides a set of functions and classes for simulating the performance of photovoltaic energy systems. |
PyLESA + | PyLESA is an open source tool capable of modelling local energy systems containing both electrical and thermal technologies. It was developed with the aim of aiding the design of local energy systems. The focus of the tool is on modelling systems with heat pumps and thermal storage alongside time-of-use electricity tariffs and predictive control strategies. It is anticipated that the tool provides a framework for future development including electrical battery studies and participation in grid balancing mechanisms.
This tool was developed as part of a PhD, "Modelling and Design of Local Energy Systems Incorporating Heat Pumps, Thermal Storage, Future Tariffs, and Model Predictive Control " by Andrew Lyden. |
PyPSA + | PyPSA is a free software toolbox for simulating and optimising modern energy systems that include features such as variable wind and solar generation, storage units, sector coupling and mixed alternating and direct current networks. PyPSA is designed to scale well with large networks and long time series. |
Q | |
QuaSi - GenSim + | GenSim - for "generic building simulation" - is a building simulation software using the EnergyPlus® simulation engine to generate high-resolution heating and cooling demand profiles as well as electricity demand profiles for buildings with various types of use. "Generic" in this context refers to a "generally valid" building model. This means that the software is versatile enough to simulate any type of building in a very flexible and simplified way, enabling users to efficiently adapt the software for any building design.
GenSim was specifically devloped for the use during project pre-planning where detailed simulations of buildings are challenging due to typically constrained time budgets and limited availability of information. Traditional simulation tools require extensive input data, making the process time-consuming. GenSim addresses this by providing presets for multiple building typologies and a streamlined approach for quick, simple, yet accurate building simulations. This is particularly valuable in early planning stages when only rough data about the planned buildings is available. If more detailed information (wall structure, detailed geometry, specific use, ...) is available about the building to be examined, this can be used for more precise results.
More information is available in the documentation: https://quasi-software.readthedocs.io/en/latest/gensim_user_manual/ |
QuaSi - ReSiE + | ReSiE is a software tool that simulates energy supply concepts for buildings, focusing on renewable energy, sector coupling and individual operating strategies. It is part of the QuaSi project that includes additional tools and can be used for individual buildings up to district-level or cities. Unlike many other tools based on systems of equations, ReSiE uses rule-based algorithms, system dynamics and an agent-based approach. This approach enables detailed simulations without linearization, capturing energy flow and system state in each time step. The central mathematical model is based on energy balances and the order of the energy calculations that is determined during preprocessing. In addition, ReSiE is suitable to perform black-box optimizations for optimal component sizing. The model can be easily extended by any energy carriers and additional components or storages of variable complexity. More information is available in the documentation: https://quasi-software.readthedocs.io/en/latest/
Note: ReSiE is currently under development! |
QuaSi - SoDeLe + | SoDeLe (loosely translated as "Solar simulation as easy as can be") is an easy-to-use tool for calculating energy profiles of photovoltaic systems. It is based on the well-validated python-pvlib, but offers a user-friendly GUI based on Excel (also a CLI with JSON input). SoDeLe can simulate PV systems with parameters from real PV modules and inverters with different orientations. Alternatively, preset standard modules and a constant DC-AC efficiency can be selected. The database of parameters contains more than 35,000 PV modules from various manufacturers.
The simulation is based on a weather file, which can be either an EWP file (EnergyPlus Weather File) or a .dat file from the German Weather Service (DWD).
With SoDeLe, the energy yield of planned or existing photovoltaic systems can be determined quickly and easily in high temporal resolution without much expert knowledge. The results can be used for dynamic energy system simulations, storage sizing or dynamic cost and greenhouse gas calculations. In addition, different orientations and different PV modules and inverters can be analyzed or the energy yield of existing systems can be checked if real historical weather data is used as input.
The results of SoDeLe were verified for different module-inverter configurations, orientations and locations using comparative simulations with the commercial software PV*SOL and with the annual totals calculated by PVGIS. |
R | |
REopt + | The REopt™ model provides concurrent, multiple technology integration and optimization capabilities to help organizations meet their cost savings and energy performance goals. Formulated as a mixed integer linear program, the REopt model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies; estimates the net present value of implementing those technologies; and provides a dispatch strategy for operating the technology mix at maximum economic efficiency. |
Region4FLEX + | The open source model region4FLEX quantifies, to which extent regional load shifting potentials can fulfill the local flexibility demand of the German high voltage grid (110, 220, 380 kV), e.g. for mitigating curtailment of renewable energies. The model offers an underlying database, which contains load shifting potentials on the administrative district level for Germany. The load shifting potentials are calculated by taking into account the structural parameters of the respective regions, such as employment rates in different industry sectors or the composition of the residential building stock. The local flexibility demand data of the power grid are calculated using the open_eGO energy system model. In region4FLEX, a cost optimisation defines, which of the available load shifting potentials in a region can be used, to meet the local flexibility demand. The resulting operating data, e.g. numbers of load shifting events, are used for a subsequent economic-assessment of the flexibility options from the operator’s perspective.
Model is under development. After release it will be directly downloadable.
MODULE 1: Heat demand and power-to-heat capacities
(Article: https://doi.org/10.1016/j.apenergy.2019.114161 ; Open Access Preprint: https://arxiv.org/abs/1912.03763 ; Open Dataset DOI: https://doi.org/10.5281/zenodo.2650200)
MODULE 2: Regionalised load shifting potentials for 19 technologies from the residential, commercial and industrial sector, as well as sector coupling (dsmlib tool)
(Article: https://doi.org/10.1016/j.adapen.2020.100001, dsmlib tool and dataset: https://zenodo.org/record/3988921)
MODULE 3: Investment and dispatch optimisation of demand response; economic assessment from macro-economic and operator's perspective
(Article: https://doi.org/10.3390/en15228577; Code repository: https://doi.org/10.5281/zenodo.6424639) |
Renpass + | renpass is an open source simulation energy model which has the goal to fulfil the requirements of full transparency and the possibility to image 100% renewable energy systems as well as today's system on a high regional and time resolution.
Currently renpass is being developed further as renpassG!S based on the Open Energy Modelling Framework (oemof). |
S | |
SIREN + | SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works" |
SMS++ + | SMS++ is a software framework for modelling and solving large-scale problems with multiple nested forms of structure. The primary application of SMS++ has been to energy problems and several specific components have been developed. |
SciGRID gas + | The SciGRID_gas project provides an open-source gastransmission data model for Europe with rich geographical and meta information originating from various publicly available sources. It is build by the German Aerospace Center DLR Institute of Networked Energy Systems Oldenburg and funded as a three year project by the German Federal Ministry for Economic Affairs and Energy (BMWi).
The following SciGRID_gas data sets are available:
• INET_Raw: InternetDaten data set; Data originates from an internet research of Wikipedia, gas TSOs
fact sheets, maps, press releases and more.
• INET_filled: INET_raw dataset with all empty values estimated by heuristic processes and filled
into the dataset
• GIE_Raw: Gas Infrastructure Europe data set; Data orginates from Gas Infrastructure Europe
• NO_Raw: Norway data set; Data originates from Gassco AS, The Norwegian Ministry of Petroleum and Energy
(www.norskpetroleum.no)
• LKD_Raw: Long-term Planning and Short-term Optimization data set; Data originates from gas data of LKD_EU
(ISBN: 978-3-86780-554-4) project
• EMAP_Raw: Entsog Capacity Map 2019
• SciGRID_gas IGG: merged data sets of INET_raw, GIE and International Gas Union data set (GSE) data and
heuristic process to fill missing parameter values
• SciGRID_gas IGGI: merged data sets of INET, GIE, GSE and International Gas Union data set (IGU)
• SciGRID_gas IGGIN: merged data sets of INET, GIE, GSE, IGU and NO
• SciGRID_gas IGGINL: merged data sets of INET, GIE, GSE, IGU, NO and LKD
All data sets can we downloaded at https://zenodo.org/search?page=1&size=20&q=SciGRID_gas. |
SciGRID power + | SciGRID is an open source model of the European transmission network. On the 15.06.2015 the first version (release V0.1) of SciGRID was released and the second version (release V0.2) was made available on the 20.11.2015. The third release of SciGRID (release 0.3) was made available on the 1st of August 2016 and includes a European and German dataset. |
SimSEE + | SimSEE is a platform for the Simulation of Systems of Electrical Energy. As such, it allows creating simulators tailored to a generation system, simply by adding the different types of Actors (thermal, wind, solar and hydraulic generators, demand, interconnections, etc.) to a Play-Room (simulation environment). These Actors behave in the Room according to their type.
It is 100% programmed with Object Oriented technology which makes it easy to incorporate new models (types of Actors).
To simulate the optimal operation of an Electric Power System, SimSEE solves a Dynamic Stochastic Programming problem, obtaining as a result an Optimal Operation Policy. Using this Policy, different realizations of the stochastic processes (chronicles or possible histories of the future of the system) are simulated.
Since 2010, SimSEE has become the tool commonly used in Uruguay to simulate the operation of the energy system, mainly due to the good stochastic models developed for the modeling of wind and solar energy.
These models achieve an adequate representation, both in the long term (Investment Planning) and in the short term (System Operation). |
SimSES + | SimSES provides a library of state-the-art energy storage models by combining modularity of multiple topologies as well as the periphery of an ESS. This paper summarizes the structure as well as the capabilites of SimSES. Storage technology models based on current research for lithium-ion batteries, redox flow batteries, as well as hydrogen storage-based electrolysis and fuel cell are presented in detail. In addition, thermal models and their corresponding HVAC systems, housing, and ambient models are depicted. Power electronics are represented with AC/DC and DC/DC converters mapping the main losses of power electronics within a storage system. Additionally, auxiliary components like pumps, compressors, and HVAC are considered. Standard use cases like peak shaving, residential storage, and control reserve power provisions through dispatch of storage are discussed in this work, with the possibility to stack these applications in a multi-use scenario. The analysis is provided by technical and economic evaluations illustrated by KPIs. |
SpineOpt.jl + | SpineOpt is a flexible, open-source, energy system modelling framework for performing operational and planning studies, consisting of a wide spectrum of novel tools and functionalities. The most salient features of SpineOpt include a generic data structure, flexible temporal and spatial structures, a comprehensive representation of uncertainties, and model decomposition capabilities to reduce the computational complexity. These enable the implementation of highly diverse case studies. |
StELMOD + | stELMOD is a stochastic optimization model to analyze the impact of uncertain renewable generation on the dayahead and intraday electricity markets as well as network congestion management. The consecutive clearing of the electricity markets is incorporated by a rolling planning procedure resembling the market process of most European markets. |
Switch + | Switch is a capacity-planning model for power systems with large shares of renewable energy, storage and/or demand response. It optimizes investment decisions for renewable and conventional generation, storage, hydro and other assets, based on how they would be used during a collection of sample days in many future years. The use of multiple investment periods and chronologically sequenced hours enables optimization and assessment of a long-term renewable transition based on a direct consideration of how these resources would be used hour-by-hour. The Switch platform is highly modular, allowing easy selection between prewritten components or addition of custom components as first-class elements in the model. |
System Advisor Model (SAM) + | The System Advisor Model (SAM) is a free techno-economic software model that facilitates decision-making for people in the renewable energy industry. |
T | |
TIMES + | The TIMES model generator combines two different, but complementary, systematic approaches to modelling energy: a technical engineering approach and an economic approach. TIMES is a technology rich, bottom-up model generator, which uses linear-programming to produce a least-cost energy system, optimized according to a number of user constraints, over medium to long-term time horizons. |
TIMES Évora + | The TIMES-Évora is a city specific energy system model, which comprehensively represent Évora municipality energy systems, focusing on energy use in residential and non-residential buildings, transport systems and other energy uses (e.g. public lighting, small-scale industry etc.). It also will represent the city waste chain and water and sewage systems in what concerns its energy consumption. The key objective of the model is the identification of an optimum mix of applicable measures and technologies that will pave the way towards the achievement of the cities’ sustainable targets. |
TIMES-PT + | TIMES_PT is a technology rich, bottom-up model generator, which uses linear-programming to produce a least-cost energy system to satisfy the demand for energy services, optimized according to a number of user constraints (e.g. CO2 emissions cap), over medium to long-term time horizons. TIMES_PT characterizes the entire chain of the Portuguese energy system from 2005 to 2050 (in 5-year steps), including energy imports and production (e.g., oil and bio refineries), transformation (e.g., power and heat production), distribution, exports and end-use consumption, in industry, residential, services, agriculture and transport sectors and their respective sub-sectors.
TIMES_PT has been developed since 2004 and has benefited from the peer-review of numerous national partners from industrial sectors, power production, oil refining and end-use energy sectors. TIMES_PT model informed climate policy in Portugal in the last 10 years and has supported the design of climate mitigation policies.
The development of the TIMES_PT model started within the EU research project NEEDS and the national research project E2POL. Although its implementation was motivated by research goals, during the past decade the model has become a major tool supporting national climate mitigation policies, and to a lesser extent, air pollution policies. The Low Carbon Roadmap 2050 is a flagship policy document currently used as the Portuguese long term view on mitigation goals, while the PNAC— National Plan on Climate Change includes the visions up to 2030 from stakeholders from other policy areas, as transportation and industry. The negotiations for the revisions of the National Emission Ceilings Directive for 2020 and 2030, as well as the National Strategy for Air Quality (2015) were supported by projections generated by TIMES_PT. More recently, TIMES_PT was linked with a national CGE model, which has motivated its use in the Green Tax Reform. |