With the increasing use of renewable energy, the energy flexibility of buildings becomes increasingly important regarding grid support. Therefore, there is a need to describe this flexibility in a concise manner. For the characterization of building energy flexibility, flexibility factors can be used. The comparison of a selection of existing flexibility factors shows that they are not easy to use or understand for designers and users. A simplification is necessary. The aim of this study is to introduce a flexibility classification that is easy to understand and shows in an easy way if a building already uses the lowest energy cost level or if further improvement is possible. The classification expresses the annual energy costs in colored classes: green (class A) for lowest up to red (class D) for highest level. Basically, the flexibility classes can be derived for any metric of interest, in this paper examples are shown for energy costs and CO_2eq emissions. The results given are based on the simulation of load management scenarios with different penalty signals applied for the heat pump operation of a residential building.

Increasing numbers of photovoltaic systems and heat pumps in existing building clusters can lead to an overload of the associated electric grid substations. Based on a multi-agent-based simulation of three building cluster types the impact of building flexibility in regard to the residual substation load is studied. Each building announces its available flexibility, e.g., “heat pump can be switched off/on”. A cluster master coordinator evaluates the incoming offers and decides which offers are accepted in regard to the substation’s capacity utilization. The goal is to honour the substation’s limit by shifting the residual load. This paper presents results from three typical urban building clusters for different penetration scenarios in regard to heat pumps, photovoltaic systems, batteries and electric vehicles. It is shown that in the studied building clusters a high penetration of heat pumps and photovoltaic systems can violate the existing substation’s limits, regardless of the efforts by the master coordinator. Batteries of typical capacities cannot reduce the peak residual load. The load shifting options of the master coordinator are limited.

With the increasing number of photovoltaic systems and heat pumps in buildings existing substations of the electric grid could be overloaded. A multi-agent based simulation of a building cluster studies the impact of building flexibility in regard to the residual substation load. Each building announces its available flexibility, e.g. “heat pump can be switched off/on”. A master coordinator evaluates all incoming offers and decides which offers are accepted. This reduces the residual load at the substation. This paper presents results from a study of the impact at the substation of a smart urban building cluster with different penetration scenarios of heat pumps, photovoltaic systems, batteries and electric vehicles. It is shown that a high penetration of heat pumps and photovoltaic systems violates the substation’s limits for the studied building cluster. Batteries cannot reduce the peak utilization. The master coordinator’s load shifting options are limited.

As a result of climate change, fossil heating systems must be replaced with renewable systems. The question arises whether it makes sense for each building to have its own new heating system or whether a thermal micro-grid is possible. In this paper a model is presented which allows to aggregate buildings into thermal micro-grid clusters. All gas-heated residential buildings of Basel (Switzerland) are marked via geo-data. The heat demand of each building is determined depending on the year of construction and is then converted into the heat load. Each building then is grouped into thermal micro-grids according to a given grid load limit. The thermal micro-grids generated in this way are marked in color, so that the potential of any given city district can be easily and quickly identified. If the grid load limit is increased, the number of possible micro-grids increases, also.