Multi-Utility Energy System Optimization

Dear Colleagues,

A successful transition to an energy system largely based on renewable energy resources cannot be achieved in the electricity sector alone. The necessary flexibility and efficiency call for a combined approach that involves heating, cooling, and mobility as well as gas and water grids. These multi-utility approaches are, however, very complex, include various feedback loops and interdependencies, and operate on different time scales. Recent advances in mathematical optimization and machine learning show great potential in finding the optimal economical or ecological solution in these different domains and for the different actors involved.
Over the last few decades, the usage of optimization in energy science has increased drastically. Finding an optimal solution for complex problems almost automatically, without being limited to a handful of use cases and examples, has influenced decision-making processes and the development of new products and business cases. The optimization of a single energy system, like enabling a smart home to include weather forecasts, is already a standard in the heating sector and also used in the electricity sector. The combined optimization of two or more different energy systems which share common boundary conditions is making progress, as is the optimization of one system towards two or more cost-functions.

The scope of this Special Issue is to apply optimization methods to the problem of a multi-utility energy system. Such a system can cover a whole nation or continent. It can also be a small geographical region, a city or even a single building that contains different utilities. Optimization goals can be as varied as the purpose of the study, from minimal cost or maximal revenue to minimal CO₂ emissions, achieved in planning, management or control.
The scope of optimization models covered in this issue is not limited to classical mathematical modeling and heuristics but can also include the application of artificial intelligence methods like machine learning or multi-agent models.

The purpose of this Special Issue is to cover a broad spectrum of reviews and original research contributions on the topic of a combined simulation and modeling of different utilities. With a wide range of different ideas, approaches and use cases can include gas, electricity, heat, and water networks but also include waste disposal and other utilities which are typical for a local energy provider.
The state of the art and current research is still mostly separated in different publishing societies (e.g., power, heat, building), distributing scientific contributions in various different journals. Our goal is to bring these excellent studies and results from multiple topics together in one Special Issue.

The current Special Issue invites contributions on the topic of multi-utility energy system optimization, of both the energy system on the national and international scale as well as single multi-utility energy systems in the urban and rural environment. Of special interest are submissions including mathematical optimization methods like heuristics, MILP, distributed optimization, bi-level optimization, robust optimization, agent-based optimization, neural networks, deep learning, etc. applied on more than one utility (power, heat, gas, water, waste, etc.) We welcome both original research articles and review articles.

Dr. Tanja M. Kneiske
Guest Editor

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• multi-utility energy systems
• energy system analysis
• grid planning
• grid control
• energy management
• hybrid energy networks
• meta-heuristics
• model predictive control
• multi-agents
• economic optimization
• flexibilities
• storage systems
• robust optimization
• bi-level optimization
• distributed optimization
• heat
• power
• gas
• smart energy
• system integration
• holistic design
• synergies
• neural networks
• deep learning