publication . Article . 2018

A Network Flow Model for Price-Responsive Control of Deferrable Load Profiles

Camargo, Juliano; Spiessens, Fred; Hermans, Chris;
Open Access English
  • Published: 09 Mar 2018
Abstract
This paper describes a minimum cost network flow model for the aggregated control of deferrable load profiles. The load aggregator responds to indicative energy price information and uses this model to formulate and submit a flexibility bid to a high-resolution real-time balancing market, as proposed by the SmartNet project. This bid represents the possibility of the cluster of deferrable loads to deviate from the scheduled consumption, in case the bid is accepted. When formulating this bid, the model is able to take into account the discretized power profiles of the individual loads. The solution of this type of aggregation problems is necessary for the partici...
Subjects
free text keywords: demand response, real-time balancing market, elastic demand bids, shiftable loads, Technology, T, General Computer Science, Flow network, Scalable algorithms, Scalability, Engineering, business.industry, business, Discretization, News aggregator, computer.software_genre, computer, Discrete optimization problem, Mathematical optimization, Control engineering, Operator (computer programming)
Funded by
EC| SmartNet
Project
SmartNet
Smart TSO-DSO interaction schemes, market architectures and ICT Solutions for the integration of ancillary services from demand side management and distributed generation
  • Funder: European Commission (EC)
  • Project Code: 691405
  • Funding stream: H2020 | RIA
Download fromView all 4 versions
ZENODO
Article . 2018
Provider: ZENODO
Energies
Article . 2018
Energies
Article . 2018
Provider: Crossref
Energies
Article
Provider: UnpayWall
19 references, page 1 of 2

1. Eurelectric. Designing Fair and Equitable Market Rules for Demand Response Aggregation; Eurelectric: Brussels, Belgium, 2015; pp. 1-24.

2. Albadi, M.H.; El-Saadany, E.F. Demand response in electricity markets: An overview. In Proceedings of the 2007 IEEE Power Engineering Society General Meeting, PES, Tampa, FL, USA, 24-28 June 2007; pp. 1-5. [OpenAIRE]

3. ERCOT. Load Participation in the ERCOT Nodal Market; ERCOT: Austin, TX, USA, 2015.

4. Ashouri, A.; Sels, P.; Leclercq, G.; Devolder, O.; Geth, F.; D'hulst, R. SmartNet-Network and Market Models: Preliminary Report (D2.4), 2017. Available online: http://smartnet-project.eu/wp-content/uploads/2016/ 03/D2.4_Preliminary.pdf (accessed on 21 December 2017).

5. Gerard, H.; Energyville, V.; Rivero, E.; Energyville, V.; Six, D.; Energyville, V. Basic Schemes for TSO-DSO Coordination and Ancillary Services Provision, 2017. Available online: http://smartnet-project.eu/wpcontent/uploads/2016/12/D1.3_20161202_V1.0.pdf (accessed on 21 December 2017).

6. Dzamarija, M.; Plecas, M.; Jimeno, J.; Marthinsen, H.; Camargo, J.; Sánchez, D.; Spiessens, F.; Leclercq, G.; Vardanyan, Y.; Morch, A.; et al. SmartNet-Smart TSO-DSO Interaction Schemes, Market Architectures and ICT Solutions for the Integration of Ancillary Services from Demand Side Management and Distributed Generation Aggregation Models: Preliminary Report, 2017. Available online: http://smartnet-project.eu/ wp-content/uploads/2017/06/D2.3_20170616_V1.0.pdf (accessed on 21 December 2017).

7. Mohsenian-Rad, H. Optimal demand bidding for time-shiftable loads. IEEE Trans. Power Syst. 2015, 30, 939-951. [OpenAIRE]

8. Pipattanasomporn, M.; Kuzlu, M.; Rahman, S.; Teklu, Y. Load profiles of selected major household appliances and their demand response opportunities. IEEE Trans. Smart Grid 2014, 5, 742-750.

9. Cardinaels, W.; Borremans, I. Demand Responde for Families-LINEAR Final Report; EnergyVille: Genk, Belgium, 2014.

10. Vlachos, A.G.; Biskas, P.N. Demand Response in a Real-Time Balancing Market Clearing with Pay-As-Bid Pricing. IEEE Trans. Smart Grid 2013, 4, 1966-1975. [OpenAIRE]

11. Kirschen, D.S.; Strbac, G. Fundamentals of Power System Economics; John Wiley & Sons: Chichester, UK, 2004. [OpenAIRE]

12. Faria, P.; Vale, Z. Demand response in electrical energy supply: An optimal real time pricing approach. Energy 2011, 36, 5374-5384.

13. Bushnell, J.; Hobbs, B.F.; Wolak, F.A. When it comes to Demand Response, is FERC its Own Worst Enemy? Electr. J. 2009, 22, 9-18.

14. Ottesen, S.O.; Tomasgard, A. A stochastic model for scheduling energy flexibility in buildings. Energy 2015, 88, 364-376.

15. Chen, Z.; Wu, L.; Fu, Y. Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization. IEEE Trans. Smart Grid 2012, 3, 1822-1831.

19 references, page 1 of 2
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue