Virtual Power Plant for Residential Demand Response

This report presents the progress done in the first 1.5 years in relation to the PhD project “Virtual Power Plant for Residential Demand Response”. The PhD project aims to gain insight on demand response provision in residential buildings by using a Virtual Power Plant (VPP) in a smart grid scenario. The document shows an architectural overview of the designed VPP and a prototype of the latter based on industrial automation equipment. Furthermore, the report introduces the control strategy of the VPP. This strategy is based on a model predictive control approach to locally optimize energy resources and to provide demand response to an aggregator. In addition, an initial study on prediction models for electricity consumption of residential buildings is presented. Load forecasting models like the ones described are used by the intelligence of the VPP for decision making. The report concludes by outlining the future work together with the planed publications that will lead to timely completion of the PhD study.

[1]  Bernhard Jansen,et al.  Architecture and Communication of an Electric Vehicle Virtual Power Plant , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[2]  Kevin M. Smith,et al.  Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy , 2014 .

[3]  Mohammed H. Albadi,et al.  Demand Response in Electricity Markets: An Overview , 2007, 2007 IEEE Power Engineering Society General Meeting.

[4]  Victor M. Zavala,et al.  PROACTIVE ENERGY MANAGEMENT FOR NEXT-GENERATION BUILDING SYSTEMS , 2010 .

[5]  Karl Aberer,et al.  Electricity load forecasting for residential customers: Exploiting aggregation and correlation between households , 2013, 2013 Sustainable Internet and ICT for Sustainability (SustainIT).

[6]  D. Kolokotsa,et al.  Predictive control techniques for energy and indoor environmental quality management in buildings , 2009 .

[7]  H. Saboori,et al.  Virtual Power Plant (VPP), Definition, Concept, Components and Types , 2011, 2011 Asia-Pacific Power and Energy Engineering Conference.

[8]  Xi Fang,et al.  3. Full Four-channel 6.3-gb/s 60-ghz Cmos Transceiver with Low-power Analog and Digital Baseband Circuitry 7. Smart Grid — the New and Improved Power Grid: a Survey , 2022 .

[9]  Zhen Yu,et al.  Hierarchical fuzzy control of low-energy building systems , 2010 .

[10]  M Morari,et al.  Energy efficient building climate control using Stochastic Model Predictive Control and weather predictions , 2010, Proceedings of the 2010 American Control Conference.

[11]  Tao Hong,et al.  Energy Forecasting: Past, Present, and Future , 2013 .

[12]  L. H. Hansen,et al.  Value of flexible consumption in the electricity markets , 2014 .

[13]  C. Goldman.  Coordination of Energy Efficiency and Demand Response , 2010 .

[14]  Marjolein van Werven,et al.  The changing role of distribution system operators in liberalised and decentralising electricity markets , 2005, 2005 International Conference on Future Power Systems.

[15]  Luis Lino Ferreira,et al.  The ENCOURAGE ICT architecture for heterogeneous smart grids , 2013, Eurocon 2013.

[16]  Nicola Labanca,et al.  Energy Efficiency Status Report 2012 , 2012 .

[17]  Shihab S Asfour,et al.  Short-Term Electrical Peak Demand Forecasting in a Large Government Building Using Artificial Neural Networks , 2014 .

[18]  David Nestle,et al.  Individual customers' influence on the operation of virtual power plants , 2009, 2009 IEEE Power & Energy Society General Meeting.

[19]  Pedro José Marrón,et al.  NOBEL - A Neighborhood Oriented Brokerage ELectricity and Monitoring System , 2010, ICST E-Energy.

[20]  Stjepan Sucic,et al.  Utilizing SOA-ready devices for virtual power plant control in semantic-enabled Smart Grid Analyzing IEC 61850 and OPC UA integration methodology , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[21]  Danny Pudjianto,et al.  Virtual power plant and system integration of distributed energy resources , 2007 .

[22]  John Ward,et al.  Beyond comfort - Managing the impact of HVAC control on the outside world , 2008 .

[23]  Slobodan Lukovic,et al.  Virtual Power Plant As a Bridge between Distributed Energy Resources and Smart Grid , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[24]  Henrik W. Bindner,et al.  An aggregation model for households connected in the low-voltage grid using a VPP interface , 2013, IEEE PES ISGT Europe 2013.

[25]  Palle Andersen,et al.  An intuitive definition of demand flexibility in direct load control , 2013, 2013 IEEE International Conference on Control Applications (CCA).

[26]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[27]  Lynne E. Parker,et al.  Energy and Buildings , 2012 .

[28]  Nico Keyaerts,et al.  Shift, not drift : towards active demand response and beyond , 2013 .

[29]  Saifur Rahman,et al.  Demand Response as a Load Shaping Tool in an Intelligent Grid With Electric Vehicles , 2011, IEEE Transactions on Smart Grid.

[30]  Shi You.  Developing Virtual Power Plant for Optimized Distributed Energy Resources Operation and Integration , 2010 .