A data-driven approach to identifying system pattern regions in market operations
Published in IEEE Power & Energy Society General Meeting (PESGM), 2015
Recommended citation: [bib file] Geng, Xinbo, and Le Xie. "A data-driven approach to identifying system pattern regions in market operations." In Power & Energy Society General Meeting, 2015 IEEE, pp. 1-5. IEEE, 2015. https://ieeexplore.ieee.org/abstract/document/7285827/
This paper studies the fundamental coupling between individual load levels and locational marginal prices in security constrained economic dispatch. The concepts of system pattern and system pattern region (SPR) are introduced for the analysis. Theoretical investigation suggests that SPRs are disjoint, convex, and separable sets and there exists separating hyperplanes among SPRs. Furthermore, the total number of SPRs is finite and the SPRs are one-to-one mapped with vectors of LMPs. Monte-Carlo simulation results provide solid support of the theoretical analysis and reveal more characteristics of system patterns and SPRs. Based on the theoretical analysis, a data-driven approach to identifying the separating hyperplanes among SPRs is proposed. This approach suggests the potential use of historical load/price data for understanding and predicting system status and prices. One promising feature of the proposed approach is that the vector of LMPs at all the buses can be successfully pinpointed given a load vector without the information of system topology. Case studies in IEEE 24 bus system illustrate the potential value of this approach in operational planning and energy trading.
Recommended citation: bib.