[HTML][HTML] Design of low-carbon multi-energy systems in the SecMOD framework by combining MILP optimization and life-cycle assessment
Decarbonizing complex industrial energy systems is an important step to mitigate climate
change. Designing the transition of such sector-coupled industrial energy systems to low …
change. Designing the transition of such sector-coupled industrial energy systems to low …
[HTML][HTML] Smart energy management: Process structure-based hybrid neural networks for optimal scheduling and economic predictive control in integrated systems
Integrated energy systems (IESs) are complex prosumers consisting of diverse operating
units spanning multiple domains. The tight integration of these units results in varied …
units spanning multiple domains. The tight integration of these units results in varied …
Application of data-driven methods for energy system modelling demonstrated on an adaptive cooling supply system
The efficient and sustainable operation of building energy systems is playing an increasingly
important role in most industrialized countries. At the same time, building energy systems …
important role in most industrialized countries. At the same time, building energy systems …
A method to bridge energy and process system optimization: Identifying the feasible operating space for a methanation process in power-to-gas energy systems
The growing adoption of renewable energy is driving the integration of new, complex
process technologies into energy systems, presenting operational optimization challenges …
process technologies into energy systems, presenting operational optimization challenges …
Automog 3d: Automated data-driven model generation of multi-energy systems using hinging hyperplanes
The optimal operation of multi-energy systems requires optimization models that are
accurate and computationally efficient. In practice, models are mostly generated manually …
accurate and computationally efficient. In practice, models are mostly generated manually …
[HTML][HTML] Component modeling and updating method of integrated energy systems based on knowledge distillation
Amid the backdrop of carbon neutrality, traditional energy production is transitioning towards
integrated energy systems (IES), where model-based scheduling is key in scenarios with …
integrated energy systems (IES), where model-based scheduling is key in scenarios with …
Zone-wise surrogate modelling (ZSM) of univariate systems
SV Srinivas, IA Karimi - Computers & Chemical Engineering, 2023 - Elsevier
Many complex systems display distinctly different behaviors across regions, zones, or sub-
domains. A single surrogate may not suffice in modelling such systems. A better approach …
domains. A single surrogate may not suffice in modelling such systems. A better approach …
Dynamic ram** for demand response of processes and energy systems based on exact linearization
The increasing share of volatile renewable electricity production motivates demand
response. Substantial potential for demand response is offered by flexible processes and …
response. Substantial potential for demand response is offered by flexible processes and …
Comparison of machine learning algorithm for Santander dataset
YA Wijaya, N Suarna, R Hamonangan… - IOP Conference Series …, 2021 - iopscience.iop.org
The dataset for Santander banks is released on kaggle. com to decide whether the customer
makes a transaction or not. The classes in this dataset are 2 with 200,000 entries in records …
makes a transaction or not. The classes in this dataset are 2 with 200,000 entries in records …
[BOOK][B] Optimization methods for integrating energy and production systems
Die wichtigste Maßnahme zur Verminderung des Klimawandels ist die Reduzierung der
Treibhausgasemissionen. Eine Schlüsselrolle hierbei spielt die energieintensive Industrie …
Treibhausgasemissionen. Eine Schlüsselrolle hierbei spielt die energieintensive Industrie …