The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.04 - July-Aug. (2013 vol.28)
pp: 43-51
Pedro Faria , Polytechnic of Porto
Zita Vale , Polytechnic of Porto
Joao Soares , Polytechnic of Porto
Judite Ferreira , Polytechnic of Porto
ABSTRACT
Price-based demand response is applied to electric power systems. Demand elasticity and consumer response enables load reduction. The methodology is implemented in the DemSi demand response simulator.
INDEX TERMS
Load management, Electricity, Load modeling, Elasticity, Power systems, Optimization, Particle swarm optimization,simulation, Load management, Electricity, Load modeling, Elasticity, Power systems, Optimization, Particle swarm optimization, intelligent systems, demand response, distribution network, electricity markets, particle swarm optimization, power systems
CITATION
Pedro Faria, Zita Vale, Joao Soares, Judite Ferreira, "Demand Response Management in Power Systems Using Particle Swarm Optimization", IEEE Intelligent Systems, vol.28, no. 4, pp. 43-51, July-Aug. 2013, doi:10.1109/MIS.2011.35
REFERENCES
1. Z. Vale et al., “Mascem—Electricity Markets Simulation with Strategically Acting Players,” IEEE Intelligent Systems, vol. 26, no. 2, 2011, pp. 9-17.
2. Y. Guan and M. Kezunovic, “Grid Monitoring and Market Risk Management,” IEEE Intelligent Systems, vol. 26, no. 2, 2011, pp. 18-21.
3. J. Ferreira et al., “A Data-Mining-Based Methodology for Transmission Expansion Planning,” IEEE Intelligent Systems, vol. 26, no. 2, 2011, pp. 28-37.
4. F. Rahimi and A. Ipakchi, “Overview of Demand Response under the Smart Grid and Market Paradigms,” Proc. Innovative Smart Grid Technologies, IEEE, 2010; doi:10.1109/ISGT.2010.5434754.
5. Z. Vale, H. Morais, and H. Khodr, “Intelligent Multi-Player Smart Grid Management Considering Distributed Energy Resources and Demand Response,” Proc. IEEE Power and Energy Society General Meeting, IEEE, 2010, pp. 1, 7, 25-29; doi:10.1109/PES.2010.5590170.
6. K.Y. Lee and M.A. El-Sharkawi, Modern Heuristic Optimization Techniques: Theory and Applications to Power Systems, Wiley-Interscience, 2008.
7. C. Ramos and C. Liu, “Intelligent Systems in Power Systems and Energy Markets,” IEEE Intelligent Systems, vol. 26, no. 2, 2011, pp. 5-8.
8. J. Kennedy and R.C. Eberhart, “Particle Swarm Optimization,” Proc. IEEE Int'l Conf. Neural Networks, vol. 4, IEEE, 1995, pp. 1942-1948.
9. E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence: From Natural to Artificial Systems, Oxford Univ. Press, 1999.
10. M.R. Al-Rashidi and M.E. El-Hawary, “A Survey of Particle Swarm Optimization Applications in Electric Power Systems,” IEEE Trans. Evolutionary Computation, vol. 13, no. 4, 2009, pp. 913-918.
11. D.S. Kirschen, “Demand-Side View of Electricity Markets,” IEEE Trans. Power Systems, vol. 18, no. 2, 2003, pp. 520-527.
12. P.R. Thimmapuram et al., “Modeling and Simulation of Price Elasticity of Demand Using an Agent-Based Model,” Proc. Innovative Smart Grid Technologies, IEEE, 2010.
13. L. Stuntz, Keeping the Lights On in a New World, tech. report, US DOE Electricity Advisory Committee, Jan. 2009.
14. Z. Vale et al., “The Role of Demand Response in Fuvture Power Systems,” Proc. Transmission and Distribution Conf. & Exposition: Asia and Pacific, IEEE, 2009; doi:10.1109/TD-ASIA.2009.5356902.
15. R.A. Arnold, Economics, 9th ed., South-Western College Pub, 2008.
16. M.H. Albadi and E.F. El-Saadany, “A Summary of Demand Response in Electricity Markets,” Electric Power Systems Research, vol. 78, no. 11, 2008, pp. 1989-1996.
17. J. Bushnell, B. Hobbs, and F. Wolak, “When It Comes to Demand Response, Is FERC Its Own Worst Enemy?” The Electricity J., vol. 22, no. 8, 2009, pp. 9-18.
18. L.A. Greening, “Demand Response Resources: Who Is Responsible for Implementation in a Deregulated Market?” Energy, vol. 35, no. 4, 2010, pp. 1518-1525.
19. K. Hamilton and N. Gulhar, “Taking Demand Response to the Next Level,” IEEE Power and Energy, vol. 8, no. 3, 2010, pp. 60-65.
20. S. Chua-Liang and D. Kirschen, “Quantifying the Effect of Demand Response on Electricity Markets,” IEEE Trans. Power Systems, vol. 24, no. 3, 2009, pp. 1199-1207.
21. A. Engelbrecht, Computational Intelligence: An Introduction, John Wiley & Sons, 2007.
22. M. Baran and F. Wu, “Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing,” IEEE Trans. Power Delivery, vol. 4, no. 2, 1989, pp.1401-1407.
23. P. Faria, Z. Vale, and J. Ferreira, “DemSi—A Demand Response Simulator in the Context of Intensive Use of Distributed Generation,” Proc. IEEE Int'l Conf. Systems, Man, and Cybernetics (SMC), IEEE, 2010, pp. 2025-2032.
64 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool