scholarly journals Calliope: a multi-scale energy systems modelling framework

2018 ◽  
Vol 3 (29) ◽  
pp. 825 ◽  
Author(s):  
Stefan Pfenninger ◽  
Bryn Pickering
Keyword(s):  
Energy Systems ◽  
Multi Scale ◽  
Modelling Framework ◽  
Systems Modelling

scholarly journals Backbone—An Adaptable Energy Systems Modelling Framework

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3388 ◽  
Author(s):  
Niina Helistö ◽  
Juha Kiviluoma ◽  
Jussi Ikäheimo ◽  
Topi Rasku ◽  
Erkka Rinne ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Unit Commitment ◽  
Energy Systems ◽  
Mixed Integer ◽  
Investment Planning ◽  
Planning And Scheduling ◽  
Modelling Framework ◽  
Wide Range ◽  
Systems Modelling

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

scholarly journals Advancing the representation of reservoir hydropower in energy systems modelling: The case of Zambesi River Basin

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0259876
Author(s):  
Nicolò Stevanato ◽  
Matteo V. Rocco ◽  
Matteo Giuliani ◽  
Andrea Castelletti ◽  
Emanuela Colombo
Keyword(s):  
River Basin ◽  
Water Resource ◽  
Thermal Power ◽  
Energy Systems ◽  
Advanced Characterization ◽  
Electricity Production ◽  
Modelling Framework ◽  
Hydropower Potential ◽  
Systems Modelling ◽  
Improved Model

In state-of-the-art energy systems modelling, reservoir hydropower is represented as any other thermal power plant: energy production is constrained by the plant’s installed capacity and a capacity factor calibrated on the energy produced in previous years. Natural water resource variability across different temporal scales and the subsequent filtering effect of water storage mass balances are not accounted for, leading to biased optimal power dispatch strategies. In this work, we aim at introducing a novelty in the field by advancing the representation of reservoir hydropower generation in energy systems modelling by explicitly including the most relevant hydrological constraints, such as time-dependent water availability, hydraulic head, evaporation losses, and cascade releases. This advanced characterization is implemented in an open-source energy modelling framework. The improved model is then demonstrated on the Zambezi River Basin in the South Africa Power Pool. The basin has an estimated hydropower potential of 20,000 megawatts (MW) of which about 5,000 MW has been already developed. Results show a better alignment of electricity production with observed data, with a reduction of estimated hydropower production up to 35% with respect to the baseline Calliope implementation. These improvements are useful to support hydropower management and planning capacity expansion in countries richly endowed with water resource or that are already strongly relying on hydropower for electricity production.

scholarly journals Generalised control-oriented modelling framework for multi-energy systems

2019 ◽  
Vol 235 ◽  
pp. 320-331 ◽  
Author(s):  
Sebastian Long ◽  
Ognjen Marjanovic ◽  
Alessandra Parisio
Keyword(s):  
Energy Systems ◽  
Modelling Framework

scholarly journals IMPLEMENTING AIR-POLLUTION AND HEALTH-DAMAGE COSTS IN URBAN MULTI-ENERGY SYSTEMS MODELLING

2018 ◽  
Author(s):  
MARCO RAVINA ◽  
EDOARDO PATTI ◽  
LORENZO BOTTACCIOLI ◽  
DEBORAH PANEPINTO ◽  
ANDREA ACQUAVIVA ◽  
...  
Keyword(s):  
Air Pollution ◽  
Energy Systems ◽  
Damage Costs ◽  
Health Damage ◽  
Systems Modelling

Holistic Ship Energy Systems Modelling for Efficient Ship Design and Operation

2015 ◽  
Author(s):  
F Tillig ◽  
◽  
J W Ringsberg ◽  
W Mao ◽  
B Ramne ◽  
...  
Keyword(s):  
Energy Systems ◽  
Ship Design ◽  
Systems Modelling

Multi-Scale, Multi-Dimensional Modelling of Future Energy Systems

2015 ◽  
pp. 113-135 ◽  
Author(s):  
Catalina Spataru ◽  
Andreas Koch ◽  
Pierrick Bouffaron
Keyword(s):  
Material Science ◽  
Control Strategies ◽  
Energy Systems ◽  
Simulation Models ◽  
Energy System ◽  
System Modelling ◽  
Multi Scale ◽  
Future Challenges ◽  
Urban Energy ◽  
Power System Engineering

This chapter provides a discussion of current multi-scale energy systems expressed by a multitude of data and simulation models, and how these modelling approaches can be (re)designed or combined to improve the representation of such system. It aims to address the knowledge gap in energy system modelling in order to better understand its existing and future challenges. The frontiers between operational algorithms embedded in hardware and modelling control strategies are becoming fuzzier: therefore the paradigm of modelling intelligent urban energy systems for the future has to be constantly evolving. The chapter concludes on the need to build a holistic, multi-dimensional and multi-scale framework in order to address tomorrow's urban energy challenges. Advances in multi-scale methods applied to material science, chemistry, fluid dynamics, and biology have not been transferred to the full extend to power system engineering. New tools are therefore necessary to describe dynamics of coupled energy systems with optimal control.

Sign in / Sign up

Export Citation Format

Share Document