Optimization of complex integrated energy systems refers to the process of systematically improving the performance and efficiency of a -renewable- energy setup that involves multiple interconnected components. This optimization may involve finding the best configuration, operation strategy, geometry design, or resource allocation to maximize energy output, minimize costs, or achieve other specified objectives including environmental issues. Such a multidisciplinary process often requires advanced mathematical modeling, simulation, and optimization techniques to handle the complexity and interdependencies within the system, where the goal is to enhance the overall sustainability and effectiveness of energy generation, storage, transport, and utilization. This can also combine perspectives from mathematics, operational research, data analysis, energy economics, and mechanical and electrical engineering in an interdisciplinary way. This approach recognizes that energy systems are complex and interconnected, requiring expertise from various fields to address challenges and achieve optimal solutions.
Based on that, optimizing high-dimensional, expensive, and black-box (HEB) integrated power systems and renewable energy sources (RES) typically involves using advanced optimization algorithms, surrogate models, and domain-specific knowledge. For this purpose, designers should consider sophisticated techniques like population-based algorithms and leverage parallel computing for efficiency. Developing surrogate models can help approximate the black-box system which is our design space, making optimization more tractable. In this way, collaboration between energy experts and mathematicians can be helpful to incorporate domain knowledge and constraints into the multi-objective optimization process. Effective implementation and application of (in-house developed) modern optimization techniques and/or algorithms will be an important part of this research topic. At the same time, seamless integration of different tools and methods will be unavoidable to reach the goal of such studies.
This Research Topic on optimization of HEB problems for the energy domain will provide a platform for researchers to publish their latest work in this area, to share new insights and developments, and to discuss open challenges and future directions. It could be also of interest to researchers, scientists, and students working in the field of algorithm development and optimization, who are seeking to expand their scientific achievements in this important area of applied research. The papers are expected to make a significant contribution to the state-of-the-art optimization research within these particular real-world problems in the energy sector. Original research, viewpoints, and review papers are among the acceptable forms of papers that can be submitted to this special Research Topic.
As long as there are any kinds of curse of dimensionality in the energy system under study, the topics covered by these papers are (but not limited to):
• Advanced global optimization methods and techniques
• Metamodel-based energy system optimization
• Machine learning and surrogate models
• AI-driven modeling and optimization for energy-related black-box problems
• System-level and component-level optimization
• Techno-economic analysis for hybrid energy system
• High-dimensional and expensive problems in the energy sector
• Multiobjective optimization models
• PESTEL-oriented interdisciplinary optimization
• Variational and control problems
• Optimization and sustainability in the energy domain
• Optimization for reliability and resilience in complex energy systems
• Optimization for best configuration, operation strategy, geometry design, life-cycle, or resource allocation in energy systems.
Keywords:
Integrated energy system, Renewable energy sources, Multi-objective optimization, Advanced optimization techniques, Global optimization, Metamodels, Surrogate modeling, Expensive black-box problems, Curse of dimensionality, Algorithm development
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Optimization of complex integrated energy systems refers to the process of systematically improving the performance and efficiency of a -renewable- energy setup that involves multiple interconnected components. This optimization may involve finding the best configuration, operation strategy, geometry design, or resource allocation to maximize energy output, minimize costs, or achieve other specified objectives including environmental issues. Such a multidisciplinary process often requires advanced mathematical modeling, simulation, and optimization techniques to handle the complexity and interdependencies within the system, where the goal is to enhance the overall sustainability and effectiveness of energy generation, storage, transport, and utilization. This can also combine perspectives from mathematics, operational research, data analysis, energy economics, and mechanical and electrical engineering in an interdisciplinary way. This approach recognizes that energy systems are complex and interconnected, requiring expertise from various fields to address challenges and achieve optimal solutions.
Based on that, optimizing high-dimensional, expensive, and black-box (HEB) integrated power systems and renewable energy sources (RES) typically involves using advanced optimization algorithms, surrogate models, and domain-specific knowledge. For this purpose, designers should consider sophisticated techniques like population-based algorithms and leverage parallel computing for efficiency. Developing surrogate models can help approximate the black-box system which is our design space, making optimization more tractable. In this way, collaboration between energy experts and mathematicians can be helpful to incorporate domain knowledge and constraints into the multi-objective optimization process. Effective implementation and application of (in-house developed) modern optimization techniques and/or algorithms will be an important part of this research topic. At the same time, seamless integration of different tools and methods will be unavoidable to reach the goal of such studies.
This Research Topic on optimization of HEB problems for the energy domain will provide a platform for researchers to publish their latest work in this area, to share new insights and developments, and to discuss open challenges and future directions. It could be also of interest to researchers, scientists, and students working in the field of algorithm development and optimization, who are seeking to expand their scientific achievements in this important area of applied research. The papers are expected to make a significant contribution to the state-of-the-art optimization research within these particular real-world problems in the energy sector. Original research, viewpoints, and review papers are among the acceptable forms of papers that can be submitted to this special Research Topic.
As long as there are any kinds of curse of dimensionality in the energy system under study, the topics covered by these papers are (but not limited to):
• Advanced global optimization methods and techniques
• Metamodel-based energy system optimization
• Machine learning and surrogate models
• AI-driven modeling and optimization for energy-related black-box problems
• System-level and component-level optimization
• Techno-economic analysis for hybrid energy system
• High-dimensional and expensive problems in the energy sector
• Multiobjective optimization models
• PESTEL-oriented interdisciplinary optimization
• Variational and control problems
• Optimization and sustainability in the energy domain
• Optimization for reliability and resilience in complex energy systems
• Optimization for best configuration, operation strategy, geometry design, life-cycle, or resource allocation in energy systems.
Keywords:
Integrated energy system, Renewable energy sources, Multi-objective optimization, Advanced optimization techniques, Global optimization, Metamodels, Surrogate modeling, Expensive black-box problems, Curse of dimensionality, Algorithm development
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.