General Role: coordination support and energy modelling and optimisation expertise.
Specific technologies in charge of: energy system modelling and optimisation using optihood (optihood — optihood documentation). Model predictive control coupling optihood and pytrnsys (pytrnsys — pytrnsys documentation).
Main goal of the project: In this project, we develop smart planning methods and control strategies for solar neighbourhoods, in order to make optimal use of solar energy, storage solutions, and the interconnection of buildings via electrical and thermal grids. A focus is on the winter heat supply, and alternatives to air/water and geothermal heat pump systems. Exploiting synergies and sector coupling at the neighbourhood scale shall allow to reduce the carbon-intensive winter electricity demand and to provide a high load and production flexibility towards the electricity grid.
Executive Summary: In order to achieve the goal of decarbonization, the Swiss Energy Strategy envisages a significant electrification of the heating sector. The planned electrification of mobility will also have a significant impact on electricity demand, particularly during the winter months, when grid electricity emissions are at their highest. It is therefore imperative to limit the increase in the winter electricity and energy demand of the building sector to a minimum. Besides other measures, like the consistent improvement of building envelope, this requires the implementation of highly efficient heat supply systems and their smart integration into multi-energy systems, thereby exploiting the synergies between the thermal and electrical sectors. Most recently installed heating systems rely on heat pumps that use ambient air or ground as a renewable heat source, each of which have their own shortcomings. This highlights the need for improvements and alternatives to these heating systems. The search for alternative solutions is more challenging in densely built-up neighborhoods than in isolated individual buildings. However, the neighborhood scale offers opportunities to utilize synergies, for example via shared energy transformation and storage units. In relation to these statements, the SolHOOD project aims to achieve the following goals: (1) Develop smart planning methods to achieve high-performance energy supply systems (heat and electricity) for neighborhoods, making optimal use of solar energy resources and using sector coupling synergies; (2) Provide alternatives to standard air and ground source heat pump systems, with low grid electricity demand in winter at the neighborhood scale; and (3) Develop an innovative advanced energy management (AEM) system based on model predictive control (MPC) to optimize the operation of complex energy systems in neighborhoods. These three goals aim to decarbonize Switzerland’s energy supply systems, reduce winter electricity consumption and peak demand, provide greater grid flexibility and make efficient use of roofs and facades for solar energy harvesting.
To achieve these objectives, we further developed an extended a python-based open-source optimization framework “optihood”. The framework was applied to a representative neighborhood in Switzerland to evaluate and compare optimal system designs with a high degree of solar installations. Moreover, the framework was applied to two case studies showing a variety of system design configurations and results, and demonstrating the effectiveness of the developed method on real cases. Additionally, the developed framework was also used to control a district heating system in order to quantify the benefits from using such a smart control against a standard rule-based control. A district design with solar collectors and a central seasonal thermal energy storage was found as both the cost and environmental optimum system design for neighborhoods, when compared to a standard alternative (with ground source heat pump systems). Results show a reduction of about 18 % in total costs, while the emissions were observed to be nearly the same. The cost optimum design with solar thermal collectors employed an air source heat pump, together with solar collectors, in order to provide the winter heat demand. The emissions, in this case, would therefore be largely dependent on the carbon footprint of grid electricity. A sensitivity analysis was therefore performed. Moreover, in terms of the use of a smart control for operating a district heating system, we observed a reduction of about 15 % in the total operation costs. In addition to cost reductions, lower CO2 emissions and better grid flexibility were also observed.
Duration: 2022-2024
Web: https://www.aramis.admin.ch/Grunddaten/?ProjectID=49313
Subcontracted by: Insitute for Solar Technology (SPF)
Funding Agency: Swiss Federal Office Of Energy (SFOE)
