In-Person event
Optimized Design and Operation of Seasonal Storages
March 13-14, 2024
In-Person event
Optimized Design and Operation of Seasonal Storages
March 13-14, 2024
In-Person event
Optimized Design and Operation of Seasonal Storages
March 13-14, 2024
Summary
Dr. Stefan Kirschbaum delivered a comprehensive presentation on the optimized design and operation of seasonal storages in energy systems. He introduced "Top Energy," a product developed by GFaI, enabling energy system modeling and optimization through flow sheets. The presentation addressed challenges in mathematical optimization for energy system planning, emphasizing factors like energy prices, weather conditions, and regulatory constraints.
To gain deeper insights and access exclusive content, we encourage you to fill out the form and unlock more valuable information.
Challenge
The complexity of energy system design and operation poses challenges in mathematical optimization, particularly with long-term time coupling constraints encountered in seasonal storages. Existing models often struggle to accurately represent real-world energy systems due to variability in end-user behavior and limited detailed information.
Solution
Dr. Kirschbaum presented a multi-stage approach to address these challenges, involving downsampling time series, relaxing binary constraints, and iteratively refining the model based on results. A rolling horizon approach was also discussed to optimize energy system operation over extended periods, aiming to enhance computational efficiency and model accuracy.
Results
The presentation demonstrated the effectiveness of the multi-stage approach in optimizing energy system design and operation. By refining the model iteratively and incorporating feedback, significant improvements in computational efficiency and solution accuracy were achieved. Comparative analysis with existing methods showed superior results in terms of solution quality and computational time.
Dr. Kirschbaum concluded by highlighting promising developments in mathematical optimization for energy system planning. The methodologies presented offer practical solutions to complex challenges such as long-term time coupling constraints and end-user behavior variability. Future research aims to further refine these approaches and integrate them into commercial software solutions like Top Energy, advancing sustainability and efficiency in energy systems.
Summary
Dr. Stefan Kirschbaum delivered a comprehensive presentation on the optimized design and operation of seasonal storages in energy systems. He introduced "Top Energy," a product developed by GFaI, enabling energy system modeling and optimization through flow sheets. The presentation addressed challenges in mathematical optimization for energy system planning, emphasizing factors like energy prices, weather conditions, and regulatory constraints.
To gain deeper insights and access exclusive content, we encourage you to fill out the form and unlock more valuable information.
Challenge
The complexity of energy system design and operation poses challenges in mathematical optimization, particularly with long-term time coupling constraints encountered in seasonal storages. Existing models often struggle to accurately represent real-world energy systems due to variability in end-user behavior and limited detailed information.
Solution
Dr. Kirschbaum presented a multi-stage approach to address these challenges, involving downsampling time series, relaxing binary constraints, and iteratively refining the model based on results. A rolling horizon approach was also discussed to optimize energy system operation over extended periods, aiming to enhance computational efficiency and model accuracy.
Results
The presentation demonstrated the effectiveness of the multi-stage approach in optimizing energy system design and operation. By refining the model iteratively and incorporating feedback, significant improvements in computational efficiency and solution accuracy were achieved. Comparative analysis with existing methods showed superior results in terms of solution quality and computational time.
Dr. Kirschbaum concluded by highlighting promising developments in mathematical optimization for energy system planning. The methodologies presented offer practical solutions to complex challenges such as long-term time coupling constraints and end-user behavior variability. Future research aims to further refine these approaches and integrate them into commercial software solutions like Top Energy, advancing sustainability and efficiency in energy systems.
Summary
Dr. Stefan Kirschbaum delivered a comprehensive presentation on the optimized design and operation of seasonal storages in energy systems. He introduced "Top Energy," a product developed by GFaI, enabling energy system modeling and optimization through flow sheets. The presentation addressed challenges in mathematical optimization for energy system planning, emphasizing factors like energy prices, weather conditions, and regulatory constraints.
To gain deeper insights and access exclusive content, we encourage you to fill out the form and unlock more valuable information.
Challenge
The complexity of energy system design and operation poses challenges in mathematical optimization, particularly with long-term time coupling constraints encountered in seasonal storages. Existing models often struggle to accurately represent real-world energy systems due to variability in end-user behavior and limited detailed information.
Solution
Dr. Kirschbaum presented a multi-stage approach to address these challenges, involving downsampling time series, relaxing binary constraints, and iteratively refining the model based on results. A rolling horizon approach was also discussed to optimize energy system operation over extended periods, aiming to enhance computational efficiency and model accuracy.
Results
The presentation demonstrated the effectiveness of the multi-stage approach in optimizing energy system design and operation. By refining the model iteratively and incorporating feedback, significant improvements in computational efficiency and solution accuracy were achieved. Comparative analysis with existing methods showed superior results in terms of solution quality and computational time.
Dr. Kirschbaum concluded by highlighting promising developments in mathematical optimization for energy system planning. The methodologies presented offer practical solutions to complex challenges such as long-term time coupling constraints and end-user behavior variability. Future research aims to further refine these approaches and integrate them into commercial software solutions like Top Energy, advancing sustainability and efficiency in energy systems.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Pawit Singcornrum
Account Executive, Renewals-Japan
Pawit is originally from Thailand and holds a Bachelor degree in Business and Administration from Thailand and an Associate degree in Computer Science from Japan. He is an IT professional with over seven years of experience in account management and renewals across the Asia-Pacific region, including Japan, Thailand, Taiwan, and Hong Kong, combining technical expertise with a strong cross-cultural perspective.
Trilingual in Thai, English, and Japanese and specializing in building strong client relationships and driving successful renewal strategies across diverse markets with proven track record of managing accounts, supporting business growth, and delivering consistent value to customers.
In his free time, Pawit enjoys exploring emerging technologies such as AI models and AI agents, as well as developing creative skills like video editing.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Account Executive, Renewals-Japan
Pawit Singcornrum
Pawit is originally from Thailand and holds a Bachelor degree in Business and Administration from Thailand and an Associate degree in Computer Science from Japan. He is an IT professional with over seven years of experience in account management and renewals across the Asia-Pacific region, including Japan, Thailand, Taiwan, and Hong Kong, combining technical expertise with a strong cross-cultural perspective.
Trilingual in Thai, English, and Japanese and specializing in building strong client relationships and driving successful renewal strategies across diverse markets with proven track record of managing accounts, supporting business growth, and delivering consistent value to customers.
In his free time, Pawit enjoys exploring emerging technologies such as AI models and AI agents, as well as developing creative skills like video editing.
Mathematical Optimization QA Engineer
David Torres Sanchez
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
Mathematical Optimization QA Engineer
David Torres Sanchez
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
Mathematical Optimization QA Engineer
David Torres Sanchez
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
Mathematical Optimization QA Engineer
David Torres Sanchez
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
Speakers
Meet Your Expert Speaker
Learn from the best in the industry, bringing years of experience and groundbreaking insights to the forefront of AI personalization.
Pawit Singcornrum
Account Executive, Renewals-Japan
Pawit is originally from Thailand and holds a Bachelor degree in Business and Administration from Thailand and an Associate degree in Computer Science from Japan. He is an IT professional with over seven years of experience in account management and renewals across the Asia-Pacific region, including Japan, Thailand, Taiwan, and Hong Kong, combining technical expertise with a strong cross-cultural perspective.
Trilingual in Thai, English, and Japanese and specializing in building strong client relationships and driving successful renewal strategies across diverse markets with proven track record of managing accounts, supporting business growth, and delivering consistent value to customers.
In his free time, Pawit enjoys exploring emerging technologies such as AI models and AI agents, as well as developing creative skills like video editing.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
David Torres Sanchez
Mathematical Optimization QA Engineer
David received his PhD in Operations Research from Lancaster University (UK) in 2019. The topic was aircraft maintenance scheduling and recovery. Since then, David has held research positions at SINTEF Digital (Norway) and Lancaster University, where he has worked on a varied range of combinatorial optimization problems from vehicle routing to multicommodity flow problems.
In his spare time he enjoys bouldering, riding his mountain bike, and maintaining and contributing to several open-source projects.
