A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Principal Component Analysis of Price Fluctuation in the Smart Grid Electricity Market
Large price fluctuations have become a significant character and impede resource allocation in the electricity market. Negative prices and peak load spike prices coexist and represent over-supply and over-demand, respectively. It is important to interpret the impact of these extreme prices on sustainable power management from the perspective of economics. In this paper, we build a principal component analysis (PCA) to assess the impact of the two opposite phenomena on the smart grid electricity system. We perform a big-data study using intra-day data from the Pennsylvania, New Jersey, and Maryland (PJM) electricity system with over 11,000 transmission lines. As the contribution, this paper (1) measures the price fluctuations from the perspective of economics, (2) captures and observes the full-length behavior of negative and spike pricing in a modern smart grid system with multi-transmission lines and high-frequency price updates, and (3) employs methods with distinctive advantages to bring more in-depth findings to interpret the smart grid system. We find that spike prices hold the principal explanatory power for electricity market fluctuation in all the transmission lines. The results are consistent with previous studies about resolutions such as electrical energy storage, transmission capacity upgrade, and demand response.
Principal Component Analysis of Price Fluctuation in the Smart Grid Electricity Market
Large price fluctuations have become a significant character and impede resource allocation in the electricity market. Negative prices and peak load spike prices coexist and represent over-supply and over-demand, respectively. It is important to interpret the impact of these extreme prices on sustainable power management from the perspective of economics. In this paper, we build a principal component analysis (PCA) to assess the impact of the two opposite phenomena on the smart grid electricity system. We perform a big-data study using intra-day data from the Pennsylvania, New Jersey, and Maryland (PJM) electricity system with over 11,000 transmission lines. As the contribution, this paper (1) measures the price fluctuations from the perspective of economics, (2) captures and observes the full-length behavior of negative and spike pricing in a modern smart grid system with multi-transmission lines and high-frequency price updates, and (3) employs methods with distinctive advantages to bring more in-depth findings to interpret the smart grid system. We find that spike prices hold the principal explanatory power for electricity market fluctuation in all the transmission lines. The results are consistent with previous studies about resolutions such as electrical energy storage, transmission capacity upgrade, and demand response.
Principal Component Analysis of Price Fluctuation in the Smart Grid Electricity Market
Kun Li (author) / Joseph D. Cursio (author) / Yunchuan Sun (author)
2018
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Iberian electricity market ontology to enable smart grid market simulation
| BASE | 2018
Iberian electricity market ontology to enable smart grid market simulation
| BASE | 2018
Principal component analysis of electricity use in office buildings
| Online Contents | 2008
Principal component analysis of electricity use in office buildings
| Elsevier | 2007
Principal component analysis of electricity use in office buildings
| Online Contents | 2008