Grid integration of distributed renewables through coordinated demand response

Mahnoosh Alizadeh, Tsung Hui Chang, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

There is a growing interest in developing solutions to facilitate large scale integration of distributed renewable energy resources and, in particular, contain the adverse effects of their volatility. In this paper, we introduce a neighborhood-level demand response program that aims at coordinating the Home Energy Management Systems (HEMS) of residential customers in order to opportunistically consume spikes of locally generated renewable energy. We refer to this technique as Coordinated Home Energy Management (CoHEM). Our model predictive control technique modulates the aggregate load to follow a dynamically forecasted generation supply. Both centralized and decentralized deployments of CoHEM are considered. The decentralized version requires a more demanding communication backbone to connect individual HEMS but, it is more resilient to failures of individual computational units or communication links and, compared to the centralized model, it preserves consumers privacy. In our numerical results section, we compare the scenario where individual HEMS optimize their energy use selfishly, under a hypothetical dynamic pricing program, to the performance of the centralized and decentralized versions of our proposed CoHEM architecture. The results highlight the advantages of using the CoHEM model in absorbing the fluctuations in the generation output of distributed renewables.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
Pages3666-3671
Number of pages6
DOIs
StatePublished - 2012
Externally publishedYes
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

Other

Other51st IEEE Conference on Decision and Control, CDC 2012
CountryUnited States
CityMaui, HI
Period12/10/1212/13/12

Fingerprint

Energy Management
Energy management
Energy management systems
Grid
Decentralized
Renewable Energy
Renewable energy resources
LSI circuits
Model predictive control
Telecommunication links
Dynamic Pricing
Model Predictive Control
Demand
Backbone
Spike
Absorbing
Communication
Volatility
Privacy
Customers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

Alizadeh, M., Chang, T. H., & Scaglione, A. (2012). Grid integration of distributed renewables through coordinated demand response. In Proceedings of the IEEE Conference on Decision and Control (pp. 3666-3671). [6426122] https://doi.org/10.1109/CDC.2012.6426122

Grid integration of distributed renewables through coordinated demand response. / Alizadeh, Mahnoosh; Chang, Tsung Hui; Scaglione, Anna.

Proceedings of the IEEE Conference on Decision and Control. 2012. p. 3666-3671 6426122.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alizadeh, M, Chang, TH & Scaglione, A 2012, Grid integration of distributed renewables through coordinated demand response. in Proceedings of the IEEE Conference on Decision and Control., 6426122, pp. 3666-3671, 51st IEEE Conference on Decision and Control, CDC 2012, Maui, HI, United States, 12/10/12. https://doi.org/10.1109/CDC.2012.6426122
Alizadeh M, Chang TH, Scaglione A. Grid integration of distributed renewables through coordinated demand response. In Proceedings of the IEEE Conference on Decision and Control. 2012. p. 3666-3671. 6426122 https://doi.org/10.1109/CDC.2012.6426122
Alizadeh, Mahnoosh ; Chang, Tsung Hui ; Scaglione, Anna. / Grid integration of distributed renewables through coordinated demand response. Proceedings of the IEEE Conference on Decision and Control. 2012. pp. 3666-3671
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