DocumentCode
3262337
Title
Decentralised heat pumps and small electricity storages as active components in a virtual power plant for smart grid services
Author
Pietruschka, Dirk ; Brennenstuhl, Marcus ; Matthiss, Benjamin ; Binder, Jann
Author_Institution
Hochschule fur Tech., zafh.net, Stuttgart, Germany
fYear
2015
fDate
10-13 June 2015
Firstpage
737
Lastpage
741
Abstract
Within the national funded project EnVisaGe (www.envisage-wuestenrot.de) a small Plus-Energy district mainly with single-family homes is built in Wüstenrot, Germany. A novel district heating system based on a cold-water heating grid supplies low temperature heat from a near surface geothermal system to the heat pumps with hot water storages in the connected buildings of the district. To reach the Plus-Energy level, highly energy efficient buildings close to passive house standard are built and equipped with large PV systems for onsite solar electricity generation. Some buildings are also equipped with electricity storages providing a capacity between 3 and 5 kWh each. Heat pumps with hot water storage offer the opportunity to shift electricity loads e.g. to periods with high solar radiation. Combined with the small electricity storages, this can significantly increase the PV self-consumption / self-sufficiency rate and help to reduce peak feed-in power to improve the grid compatibility [1] [2]. This complex energy management task requires innovative MPC (model based predictive control) schemes implemented in an appropriate monitoring and control system, which is developed and tested within the project. Apart from this local optimization on a single building level, decentralised heat pumps and batteries in a larger cluster can also deliver controllable electricity sinks as smart grid applications for electricity providers. To test these additional opportunities within the project, the heat pumps and batteries are connected to the virtual power plant of Vattenfall. Within the paper, the developed cloud-based data collection and management system is presented together with the MPC based system. Additionally, monitoring and simulation results are shown.
Keywords
buildings (structures); cloud computing; district heating; energy conservation; energy management systems; geothermal power stations; heat pumps; optimisation; passive solar buildings; power engineering computing; power system control; predictive control; smart power grids; virtualisation; EnVisaGe; Germany; MPC based system; MPC schemes; PV self-consumption-self-sufficiency rate; PV systems; Vattenfall; Wustenrot; batteries; building level; cloud-based data collection; cold-water heating grid; control system; decentralised heat pumps; district heating system; electricity loads; electricity providers; electricity sinks; electricity storages; energy efficient buildings; energy management; hot water storages; local optimization; management system; model based predictive control; monitoring system; near surface geothermal system; onsite solar electricity generation; passive house standard; plus-energy district; single-family homes; smart grid applications; smart grid services; solar radiation; virtual power plant; Batteries; Brain modeling; Buildings; Heat pumps; Power generation; Resistance heating; Water heating; load management; model based predictive control; smart grid; virtual power plant;
fLanguage
English
Publisher
ieee
Conference_Titel
Environment and Electrical Engineering (EEEIC), 2015 IEEE 15th International Conference on
Conference_Location
Rome
Print_ISBN
978-1-4799-7992-9
Type
conf
DOI
10.1109/EEEIC.2015.7165256
Filename
7165256
Link To Document