In a power system, a price-based demand-response program offers end electricity users time-varying prices, incentivizing them to shift demand from high-price hours to low-price hours during a day. Heating/cooling (H/C) loads are typical flexible loads to be shifted. Specifically, end users optimize the hourly H/C load to balance electricity costs and comfort. In this paper, a two-time-scale neurodynamic optimization approach is applied for this multi-objective optimization problem. As a result, optimal use of H/C loads is derived that yields significant savings and acceptable comfort. A case study of the Houston City is presented to show the effectiveness of the proposed neurodynamic approach.
CITATION STYLE
Le, X., Chen, S., Zheng, Y., & Xi, J. (2017). A multiple-objective neurodynamic optimization to electric load management under demand-response program. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10262 LNCS, pp. 169–177). Springer Verlag. https://doi.org/10.1007/978-3-319-59081-3_21
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