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Optimal demand response programs for improving the efficiency of day-ahead electricity markets using a multi attribute decision making approach

M. Shafie-khah, D. Fitiwi, M.H. Shoreh, P. Siano, G. Osório, J. Lujano-Rojas, J.P.S. Catalão

IEEE International Energy Conference - ENERGYCON 2016, Lovaina (Bélgica). 04-08 abril 2016


Resumen:

In this paper, an agent-based model is proposed to improve market efficiency by using different Demand Response Programs (DRPs) in the day-ahead electricity market. To this end, both incentive-based and price-based DRPs are considered. On this basis, time of use, real time pricing, emergency demand response program, interruptible/curtailable services and critical peak pricing are investigated. The tariffs of the considered price-based programs and the amount of incentive in the incentive-based programs are optimized through the proposed model. Furthermore, a market power index, i.e., Share Weighted Average Lerner Index (SWALI) and the operation cost are used to evaluate the market efficiency and the market power. The proposed model optimizes the DRPs to improve the electricity market efficiency by using a multi-attribute decision-making approach. The results show that the market operator can mitigate the potential occurrence of market power in a power system by finding the optimal DRP.


Palabras clave: Demand response programs (DRPs), Electricity market, Multi-attribute decision-making (MADM), Marketpower.


DOI: DOI icon 10.1109/ENERGYCON.2016.7513998

Fecha de publicación: abril 2016.



Cita:
Shafie-khah, M., Fitiwi, D., Shoreh, M.H., Siano, P., Osório, G., Lujano-Rojas, J., Catalão, J.P.S., Optimal demand response programs for improving the efficiency of day-ahead electricity markets using a multi attribute decision making approach, IEEE International Energy Conference - ENERGYCON 2016, Lovaina (Bélgica). 04-08 abril 2016.


    Líneas de investigación:
  • *Smart grids
  • *Green energy integration
  • *Planificación táctica a medio plazo
  • *Análisis de estrategia a largo plazo

IIT-16-184A

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