The change from a centralized to a decentralized energy supply creates new challenges in the planning of such energy supply concepts. Specialized planning tools that can cope with the complex requirements and multi-layered boundary conditions of local energy use are therefore needed. Existing methods need to be further developed and optimized to suit the complex stakeholder structures encountered in innovative district projects, as well as for research purposes. This paper presents selected aspects and challenges in the development of an application-oriented planning tool. Using a North German district as a case study, the usability of a Building Information Model as an aggregated data platform is tested in the context of a residential energy district planning process. In addition, the modeling of heating grids using a combination of Geographic Information System and open source thermodynamic tools is presented. Economic valuation methods are examined to determine the extent to which the value of flexibility and access to local flexibility markets can be taken into account. Finally, an approach for evaluating the ecological aspects of the district energy supply is presented, based on the dynamic assessment of imported and exported energy quantities.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented, and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is to present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

Since the Paris Agreement in 2016, the goals of limiting climate change and moving toward climate resilience stand. With a share of about 80% of global CO₂ emissions, the energy sector is an essential driver for these goals. A shift to low-carbon energy production and a decentralized system for more efficient energy transmission distribution is necessary. In this paper, we present our work on Modelling of Power Exchanges, Algorithms for Local Energy Market (LEM), Competitiveness of Combined Heat and Power Plant (CHP) and Energy Feedback Devices. The study was conducted considering technical, economic, social and regulatory framework. For easy integration into energy simulations or a district energy management system (DEMS), a model for power exchanges was created that allows flexible input or deterministic price patterns. The algorithm handles the clearing of an LEM by a district aggregator using limit orders with the goal of increasing the share of locally consumed electricity using economic incentives. An investigation was conducted into the operation of flexible CHPs in low-carbon power systems to balance the volatility of renewable energy. An Energy Signal Light (ESL) was developed as an energy feedback device, which is integrated into the DEMS in a living lab and allows individual configuration. In summary, the results presented should be compared with those of other research approaches in the future and require qualitative and quantitative evaluation.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

In the course of the energy transition, distributed, hybrid energy systems, such as the combination of photovoltaic (PV) and battery storages, is increasingly being used for economic and ecological reasons. However, renewable electricity generation is highly volatile, and storage capacity is usually limited. Nowadays, a new storage component is emerging: the power-to-gas-to-power (PtGtP) technology, which is able to store electricity in the form of hydrogen even over longer periods of time. Although this technology is technically well understood and developed, there are hardly any evaluations and feasibility studies of its widespread integration into current distributed energy systems under realistic legal and economic market conditions. In order to be able to give such an assessment, we develop a methodology and model that optimises the sizing and operation of a PtGtP system as part of a hybrid energy system under current German market conditions. The evaluation is based on a multi-criteria approach optimising for both costs and CO₂ emissions. For this purpose, a brute-force-based optimal design approach is used to determine optimal system sizes, combined with the energy system simulation tool oemof.solph. In order to gain further insights into this technology and its future prospects, a sensitivity analysis is carried out. The methodology is used to examine the case study of a German dairy and shows that PtGtP is not yet profitable but promising.