Energy Flexible nZEBs
The increasing share of fluctuating renewable energy generation in the electricity grids requires technical measures, new market designs and models to balance generation and demand for electricity on the demand and supply side. As buildings are major energy consumers in the energy system and electricity for heating, domestic hot water and cooling, as well as on-site electricity generation from renewables are increasing, the integration of building energy systems/ buildings in the energy system is gaining importance. Renewable electricity is generated on-site, stored in batteries, which could also be used for balancing the local distribution networks, heat-pumps and electrical vehicles are new electrical consumers in buildings with relatively high connected power,…there are many new and already established technologies, which have to be integrated into the system and be operated in a way stabilizing the electricity grids.
There are several different options, flexibility goals and KPIs discussed in the field of energy efficiency and flexibility. Furthermore, there are different options and needed technologies to provide flexibility. In the CRAVEzero report ‘Energy flexible building managing models’, these are described in detail. Furthermore, technologies and different methods were applied in some of the CRAVEzero case study buildings. The options are compared using three different approaches/ KPIs, namely:
- Self-sufficiency/ autarky rate based on Results of the tool PVopti
- Analysis of the Grid Support Coefficient GSC developed at Fraunhofer ISE
- Analysis of the Smart Readiness of the buildings based on the current status of the definition of the Smart Readiness Indicator, which might be introduced on the European level in the future.
Similarities, as well as contradictions of the approaches, are highlighted. The aim of the work is the development and description of models and methodologies for (i) continuous commission of buildings and (ii) building-grid interaction with a focus on the on-site use of renewable energies. Thereby, two major challenges of the future are addressed, which are (i) the reduction of the energy use in buildings and avoidance of malfunctions in the building energy system and (ii) the integration of fluctuating renewable energies in the electricity grid by adjustments in the building operation.
The process of continuous commissioning is described based on a detailed literature review as well as on results from projects focusing on fault detection in large and complex building energy systems.
For the integration of renewable energies in the electricity grid by an adjusted building operation, the definitions and findings from the IEA EBC Annex 67 “Energy Flexible Buildings” are the basis. Possibilities for an improved building-grid interaction are described qualitatively and assessed quantitatively using different approaches/ tools and a comparison of the respective results. The quantitative analysis uses the PHPP-models of case studies as a starting point. With the tool PVopti , the self-consumption and autarky level of the base case and several other technology sets are assessed, and for each case hourly electricity profiles are generated. The hourly profiles are used in a second step to analyze the grid supportiveness of the building/ technology set using a methodology and indicator (Grid Support Coefficient GSC) developed at Fraunhofer ISE. Also, the case study buildings assessed in detail are rated using a simplified method for rating the Smart Readiness of Building (Smart Readiness Indicator SRI) based on the proposed Simplified online quick–scan described in (Reynders, 2019).
The differences between the approaches and the respective results are compared, analyzed and critically discussed. The aim is to identify different implications for the building technology sets from the different approaches resulting from the different focuses (self-consumption, grid-supportiveness,…).
Buildings interact with surrounding energy systems by importing and exporting energy (Salom et al., 2014). Usually, the focus is the interaction with the electricity grid. With the increasing usage and integration of fluctuating renewable energy technologies like wind and photovoltaic in buildings and electricity grids, the interaction between all participants (energy consumers and producers, as well as prosumers, is gaining importance. In order to support the integration of fluctuating renewables the import and export of buildings should be oriented on the current state of the superordinate power grid by increasing the flexibility of the energy supply and demand of the buildings. In (Weiß et al., 2019a) flexibility is described as the maximum time a power draw can be postponed or additionally consumed at a specific moment during the day.
In (Voss et al., 2010), the importance of building-grid interaction to realize net-zero-energy buildings (NZEBs) is emphasized. The interaction/ energy exchange with a grid infrastructure helps to overcome limitations of on-site seasonal energy storage. Grid interaction is defined in (Voss et al., 2010, p. 2) as “the temporal match of the energy transferred to a grid with the needs of a grid”. In the following important terms and approaches to manage and optimize the interaction between energy grids and buildings as well as strategies to increase the intelligence of energy systems and buildings are described. Furthermore, approaches to quantify the ability and level to operate buildings in a way, which is helping to stabilize and manage the grids and thereby integrate an increasing share of fluctuating renewables are introduced.
Demand Side Management (DSM) can be used to manage the load curve of buildings, such as shift demand in time (load-shifting), reduce the peak in the energy demand (peak-clipping/load shaving) or temporally increase the load when the incentives are high, or the electricity prices are low (valley-filling) – see Figure 43. The relevance and possibilities for the different DSM approaches in several European countries.
DSM is defined from a utility perspective as “the planning and implementation of those electric utility activities designed to influence customer uses of electricity in ways that will produce desired changes in the utility’s load shape” (Gellings, 1985), and can be divided into two categories like energy efficiency (EE) and demand response (DR) (Palensky and Dietrich, 2011). The benefit of DR strongly depends on the available energy flexibility and successful implementation of DR programs. Hence, most state-of-the-art literature is focusing on demonstrating to what extent this can reduce energy cost, shift peak power, increase the use of local renewable electricity production, or achieve stability in the power grids by utilizing the flexibility of buildings.
In this context, the term “grid-supportive” operation of buildings is introduced and discussed in science, e.g. in (Klein, 2017). The goal of analyzing and quantifying the grid supportiveness is to understand how and to what extent buildings can contribute to “efficient integration of a high share of intermittent renewable energy into the energy system” (Klein, 2017, p. 17). The focus is on the support of the overall upstream energy system, not only local/ regional grids. “Grid-supportiveness” is defined by (Klein, 2017) as an operation of variable electrical loads in a way that they consume power predominantly in periods with low relative electricity demand in the system. Thereby, not only power load needs are considered, but also the availability of fluctuating renewable energies. On the other hand, a grid-supportive generator produces mainly when the relative electricity demand in the whole energy system is high (Klein, 2017). The contrary behaviour is termed grid-adverse. For measuring/ quantifying the grid-supportiveness, (Klein, 2017) developed the absolute Grid Support Coefficient GSCabs and the relative GSCrel.
One of the key barriers jeopardizing the market uptake of smart technologies is the lack of clarity about the energy benefits. There are few studies about the impacts of implementing smart home devices in buildings, and there is a lack of independently verified empirical data on savings impacts (Urban et al., 2016), evaluated with a shared approach. The EPDB Recast 844/2018 (The European Parliament and the Council of the European Union, 2018) introduced the Smart Readiness Indicator (SRI), in order to raise the awareness amongst building owners and occupants of the value behind smart devices and services, giving confidence to the occupants about the actual savings of those new enhanced-functionalities. It, therefore, measures the readiness of the building “to adapt the operation of buildings to the needs of the occupants and the grid and to improve the energy efficiency and overall performance of buildings“ (The European Parliament and the Council of the European Union, 2018).
From the view of a building, the logic behind this EPBD amendment is: It is intelligent only with minimum equipment of smart technologies and services. What might be missing, displaced or even able to generate resistance:
- These technologies and services do not guarantee that the building is intelligent in the context of the surrounding energy networks (electricity, heat and gas) or that it helps to lower the CO2 emissions of the overall energy system. In the context of a neighborhood or the surrounding network, however, the energy flexibility and “smartness” of buildings are essential resources for reducing CO2 emissions at this level, in line with the IEA EBC Annex 67.
- Measured or achieved “smartness” could cause additional costs, which preclude the required affordability of housing. And there are fears that “grid-supportiveness” – if it is applied – would by no means be adequately remunerated by the utilities.
A consortium led by the Flemish Institute for Technological Research NV (“VITO”) has been awarded the contract for the implementation respectively the concept of the SRI. If their proposal is accepted by the European Commission through parliament and council, the implementation respectively the ascertainment will be up to the individual states. The preparation of a possible national specification of the SRI as well as the possible integration in the process of energy performance calculation can still be influenced since the preparation process is on-going.
AEE INTEC is involved in the development of the calculation methodology, which is based on a technology and services rating system, weighting different services by their functionality level affecting predefined impact criteria (Reynders, 2019; Verbeke et al., 2018). Such effects are pre-calculated for the smart devices and services available on the market, but they are not associated either to physical nor to performance quantities. This should be noted and kept in background knowledge when new SRI developments are integrated into the work in CRAVEzero to assess the technologies’ and building services’ smartness found within CRAVEzero demonstration projects to learn from.
The case studies “Brussels” and “Moretti More” were analyzed concerning different KPIs, namely self-consumption, autarky GSC with respect to EEX prices, GSC for residual load and the smart readiness of the buildings. For all KPIs except the smart readiness several variants were assessed to identify the driving (technical) factors. However, a positive factor for increasing e.g. the self-consumption is not necessarily positive for the GSC and vice versa. The main positive and negative factors identified for the case study “Parkcarré” are summarised in Table 10 and for “Moretti More” in Table 11.
The main drivers for a high self-consumption are the installation of electricity storage and the size of the PV-system in relation to electricity consumers. Thereby, the presence of large electricity consumers especially in summer (cooling units, heat pump) is a crucial factor as well. Generally one can say the smaller the PV-system compared to the electricity demand, the higher the self-consumption as (almost) all electricity is used on-site throughout the year. The challenge in buildings without high electrical demands in summer (high PV generation) is the usage of the generated electricity in the summer months. For a high autarky rate as well as good GSC values however large PV systems are positive.
For good GSC values, the installation of battery storages, as well as the use of electricity using heating systems, is positive, especially when a PV system installed. In climate regions with mainly heating demands a large PV system in combination with heat-pumps is increasing the GSC concerning EEX prices.
The absence of large electricity consumers, especially the absence of heat pumps with thermal storages, is a crucial part for the self-consumption and GSC as this is (i) affecting the possibility to use PV electricity generated on-site and (ii) affecting the load-shifting possibilities, which are necessary to operate a building grid-supportive. Bivalent heat-pumps thereby even offer higher shifting/ switching potentials and are also positive for the autarky rate.
Especially concerning the self-consumption and autarky, the followed strategy strongly affects the technical installation needed; to increase the self-consumption by trend small PV systems are positive, for a high autarky large systems are necessary. Furthermore, it is crucial that the PV system is sized accurately to the demands of a respective building and sufficient storage possibilities are available.
As the analysis of the smart readiness is based on a more qualitative approach positive and negative factors for the SRI are not included in the summarising tables below. The dimensioning of renewable energy technologies on-site is not influencing the SRI result, but the presence of these technologies. However, what is more important is the availability of storages and the controllability / usability of these storages based on external (grid) demands. Thereby, the installation of batteries, which is positively influencing all other KPIs, has also a positive effect on smart readiness. For a high SRI-score the controllability and control strategies supporting the stability and management of higher level grids are positive. Implementing these strategies in buildings is also supporting the increase of the self-consumption, autarky as well as the GSC. The quantitative effects were not assessed in this study as detailed building models and optimizations would be needed for the analysis, which was not part of the project. It can be concluded however that considering the high level services described in the SRI services catalog is positively affecting all other quantitative KPIs assessed in the frame of this study.
Table: Comparison of factors positively and negatively affecting the assessed KPIs in the case study “Parkcarré”
| Self-consumption | Autarky | GSC_EEX | GSC_Residual | |
| Positive | Battery storageAccurate dimensioning of PV in relation to el. demand (by trend smaller PV)Installation of heat-pump | Large PV-systemLarge battery storageNo big el. consumer like heat-pump during winter (bivalent heat pumps achieve better results) | Medium – large PV system in combination with heat pump and battery storage | Heat pump + Large PV systemIf no heat pump and Battery installed, smaller PV-system positive |
| Negative | No big el. consumers in summerNo battery storageToo large PV system | No Battery storageSmall PV systemHeating system only using electricity à bivalent heat-pumps better | Non-electric heat generation / district heat à only low shifting potentialNo Battery storage | Non-electric heat generation / district heat à only low shifting potential No Battery storage |
Table: Comparison of factors positively and negatively affecting the assessed KPIs in the case study “Moretti More”
| Self-consumption | Autarky | GSC_EEX | GSC_Residual | |
| Positive | Battery storageAccurate dimensioning of PV in relation to el. demand especially in summer | Bivalent heat pumpLarge PV systemBattery storage | Installation of battery + large PV | BatteryOptimisation of operation |
| Negative | Large PV-systemNo battery storage | No battery storageSmall PV system | Large PV without battery | Installation of PV |
The chapter aimed to develop and description models and methodologies for a continuous commission of buildings and building-grid interaction with a focus on the on-site use of renewable energies. The chapter thereby addresses two major challenges of the future:
• Reduction of energy use in buildings and avoidance of mal-functions in building energy systems
• Integration of fluctuating renewable energies in electricity grids by adjustments in the building operation
The process of continuous commission is described based on a detailed literature review as well as on results from projects focusing on fault detection in large and complex building energy systems. The importance for a reliable and robust operation of a building is highlighted and suggestions for the integration of continuous commission in the building life cycle are provided.
For the integration of renewable energies in the electricity grid by an adjusted building operation, definitions and findings from the IEA EBC Annex 67 “Energy Flexible Buildings” are the basis. Possibilities for an improved building-grid interaction are described qualitatively and assessed quantitatively. Therefore, PHPP-models of case studies and the tool PVopti are used to assess the self-consumption and autarky level of several technology sets are assessed. The results show that an adequate sizing of on-site renewable energy technologies in combination with electrical and thermal storage is essential. A difference between the goal of increasing the self-consumption and increasing the autarky is the size of the on-site renewable generation. While for a high autarky rate a high generation capacity is needed to provide the needed electricity also in times with low specific on-site generation this approach reduces the self-consumption in times with high specific on-site generation. In the case study “Parkcarré” self-consumption rates between 19 % and 100 % and autarky rates of 14 % to 77 % are achieved. The variants with a high autarky always have a relatively low self-consumption compared with similar technology sets and vice versa. Variants with a large PV system and battery but no heat pump have a high autarky rate (a large part of the electricity demand during winter can be provided by on-site PV generation). On the other hand variants with a small PV system and a heat pump have high self-consumption but a very low autarky. Similar results are obtained in the case study “Moretti More”. However, due to a more constant electricity demand throughout the year due to the electrical cooling units installed, the importance of a battery for both, the self-consumption and autarky, is lower than for the case study “Parkcarré”, in which the electricity demand fluctuates more throughout the year. The right dimensioning of the PV system is of major importance in this case.
With the tool PVopti, also hourly profiles for the electricity purchase from the grid were generated, which are used to analyze the grid-supportiveness concerning two external grid signals:
• EEX-prices
• Residual load
Almost all analyzed technology sets are grid-adverse and no set is really grid-supportive. However, the technologies installed and combined offer the possibility to operate the buildings grid-supportive. In order to increase the grid-supportiveness (GSC) the control strategies of single technologies as well as the whole building energy system have to be adjusted. Especially the use of storages and the operational times of large electricity consumers like heat pumps and cooling units are crucial. To quantify the effects of different control strategies, detailed simulations and optimisations are required, which were not part of this study.
In addition to the quantitative assessment, the smart readiness of two case study buildings is rated using a simplified method based on the proposed simplified online quick–scan for the SRI. Here, only the base case (as built / as planned) is rated. Both buildings achieve an SRI below 50 %. Especially concerning on-site energy savings and comfort, both buildings show a good performance, which can be explained with the focus on energy demand reductions and high comfort in buildings in the past years. The flexibility and smartness of building operation is just starting to gain importance and the current energy markets are still not offering promising business cases for a smart and flexible operation. However, the topic will gain importance in the future and many technologies currently installed in buildings already offer an increased flexibility with some adjustments in control strategies (thermal storages, heat pumps).
Besides the technical implementation, the market design including sufficient incentives to provide flexibility in / of the building for the operation and management of higher-level electricity grids has to be adjusted. Currently, only large switchable and shiftable loads can participate in the electricity market. However, the required power for participation is much higher than the power most buildings can provide. Different approaches to close the gap are currently assessed in different projects. Possibilities are e.g. pooling of many small loads to reach the required load size, lowering the required size or new ways of trading amongst participants in the energy markets.
Summing up, the addressed KPI strongly influences the technologies needed. Especially the autarky rate has very different needs compared to the other KPIs. Furthermore, most technologies needed for a flexible building operation are already available. However, some are still comparably expensive and therefore not widespread. The main challenge is the operation and management of buildings in a way that renewable energy can be integrated into the energy system on different levels (on-site, regional, national, European). Therefore, on the one hand control strategies in buildings have to be adjusted and optimized, on the other hand adequate grid signals have to be available for building management and control systems.