Increase of in-house consumption by building clusters and active storages (Eigenlast Cluster)
Smart Grids are the current term used to describe the change of paradigm currently taking place in the electric energy grid. Energy industry and science are heavily working with con-cepts of smart meters, tap changers in local transformers and communication networks. In addition, there is a shift from central energy production towards distributed local production that increasingly comes from fluctuating energy sources. To support this transition to go smoothly, it is advised to plan for this as early as possible. For example, during planning of decentralized energy generation plants and designation of building land it can already be cared for an optimal usage of the energy locally.
Contents and Objectives
In this context, the project EigenlastCluster was looking into the identification and evaluation of suitable clusters of consumers that increase the on-site consumption of energy. The basic approach is that different consumers such as households, commerce, industry and commu-nal buildings have differing load profiles. The combination / common accounting of those can have a positive impact on the on-site consumption of fluctuating PV generation. In addition, within this project the additional effect of Demand side Management measures as well as the usage of short term lithium batteries and seasonal hydrogen batteries were investigated. In analogy to the electric grid, suitable consumers (clusters) are identified also for the thermal grid to increase usage of the heating plant through suitable, flexible loads. The effects of forming clusters for both the electric and thermal grid are finally evaluated economically. The object under investigation is exemplarily the town of Großschönau.
In order to identify suitable clusters and allow an economic assessment, first consumption profiles and PV generation profiles need to be prepared. The consumption profiles consist partly of monitoring data as well as synthetically generated profiles. The PV generation was modeled based on solar irradiation and ambient temperature as well as the systems’ charac-teristics such as module efficiency, temperature characteristics and orientation. A cluster is the sum of three different load profiles assigned to one PV system. The suitability of a cluster is assessed by how little excess energy is fed into the electric grid over the duration of a year. Finally the resulting clusters were supplemented by Demand Side Management measures and various combinations of short term and long term electrical storages.
In order to identify suitable clusters for the heat plant and assess their potential the following method was applied: The monitoring data of the heat plant is processed, enriched (ie. with indicators of heating days), verified and analyzed in order to identify the five coldest days. In case there is still potential visible in the daily output, this potential can be utilized through flexible loads (similar to the clustering and DSM measures of electrical loads). The result is a new cluster that contains buildings with flexible heating loads. The assumption is, that those buildings have low thermal losses throughout the day and a high thermal inertia, so that they can cover their daily needs in times where the heating plant has capacity left. The monitoring data had to be projected into a stronger winter as the winter with monitoring data between 2013 and 2014 was a mild one and as a result not representative. The projection was done by identifying the base load in summer of 85,8kW and scaling the heat output through the outside temperature dependent part between 12°C and -17°C. -17°C was the as-yet meas-ured coldest day in Großschönau, at which the heating plant was known to operate at its maximum capacity. The identified potential together with a simplified modelling of the passive houses allow an estimation of the additional heating demand and ultimately an economic assessment.
The project shows, that creating suitable clusters of different electric load profiles is econom-ically attractive. Clustering increases the economic benefit through increasing the on-site consumption. On-site consumption is increased by an average 40% by adding two additional consumers to smaller PV installations (< 10 kW). The positive resulting economic effect is around 0,10 €/kWh for households and around 0,07 €/kWh if calculated benefits are referred to additional on-site consumption.
Regarding chemical storages (9.6 kWh, Li-Ion technology) without combining it with H2-storage solutions an additional 23% of on-site consumption can be achieved for clusters with high shares of household load profiles. However, H2-Storage solutions reduce economic performance significantly, as they are engineered as seasonal storages and therefore high capital cost are given. In general load profile clustering reduces economic benefits of storage solutions significantly or even eliminates them as almost no additional on-site consumption can be achieved.
Demand Side Management (DSM) solutions are hardly economic (even large scale options) as additional on-site consumptions rates calculated to 0.45%. Again this is due to load clus-tering effects. Thus, a combination of clustering as well as storage and DSM solutions can not be recommended from an economic perspective.
The thermal heat plant has remaining potential for a flexible load at coldest days between 22:00 and 7:00 o‘clock which corresponds to a theoretical extra heating demand of 2654 kWh per day which corresponds to about 47 passive houses. The positive economic effect of this is a reduction of about 3,5% of operational cost for existing customers. The total present value of such measure must not exceed 23000 €. However, the remaining life time of the relatively old power plant is to be considered. Also the additional demand would need to be chosen less in reality in order to not strain the heat plant excessively and to ensure safety margins.
Prospects / Suggestions for future research
This project is the basis for further projects and activities in Großschönau to gain additional knowledge and has already influenced new funding proposals and lead to publications. A further validation of the results within existing buildings of Großschönau would be interesting. Potential PV clusters that are interested in realizing a demonstration could be equipped with temporally highly detailed measurement devices and be looked into with in more detail (look-ing into cable lengths, additional meters, accounting systems, etc. and also incorporating results from project GEBEN). Such demonstration would reveal additional aspects of user acceptance (prejudice, transparency), insurance issues, and aspects of financing and coor-dination (accounting, responsibilities and roles).
On the level of the municipality it would be interesting to investigate the effect of increasing the share of PV further and create a roadmap, since increasing the share of PV changes the setting in which clustering can take place. At some point no additional clustering and no addi-tional PV systems would be possible without affecting the existing clusters respectively. Such a roadmap would also need to consider the geographical distribution of the clusters. Fur-thermore, the creation of clusters could be refined by looking at additional loads (such as e.g. houses with relatively large electrical consumers or flexible loads such as identified in project GAVE) allowing for an holistic picture of potentials in the municipality.
The results and performed research addressing the heat plant could influence future plans of extending the district heating grid and renewing the heating plant. Even more, a detailed evaluation and validation of necessary energy management solutions would be of interest, in order to enable existing heat management potentials. This could be realized through plan-ning of a new and large building close to the existing heating network. Detached from the research question of this project it would be interesting to compare the clustering also with the measure of installing an additional thermal storage, also from an economical point of view.
GF Josef Bruckner - Sonnenplatz Großschönau GmbH