TY - GEN
T1 - Graphical Modeling for Analysis of Hourly Electricity Demand and Market Price
AU - Kaneko, Nanae
AU - Fujimoto, Yu
AU - Hayashi, Yasuhiro
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - Recent changes in power system, e.g. large-scale penetration of renewable energy source, have led to change the behavior of the electricity demand and market price drastically; this behavior is also influenced by various factors such as weather and economic conditions. The factors that affect such demand and price are complex and the analysis of these factors enables stakeholders to construct an electricity business strategy. Therefore, a framework is needed to analyze and interpret the relationships among these demand, price, and factors. Construction of a graphical model is an attractive approach to describe the statistical relationships among these factors; the directed graphical model flexibly visualizes the direct/indirect factors affecting the demand and price. In this study, the authors applied a graphical modeling scheme using the sparse partially linear additive models for factor analysis of electricity demand and price. The scheme is applied to a real-world dataset and discussed from the viewpoint of interpretability.
AB - Recent changes in power system, e.g. large-scale penetration of renewable energy source, have led to change the behavior of the electricity demand and market price drastically; this behavior is also influenced by various factors such as weather and economic conditions. The factors that affect such demand and price are complex and the analysis of these factors enables stakeholders to construct an electricity business strategy. Therefore, a framework is needed to analyze and interpret the relationships among these demand, price, and factors. Construction of a graphical model is an attractive approach to describe the statistical relationships among these factors; the directed graphical model flexibly visualizes the direct/indirect factors affecting the demand and price. In this study, the authors applied a graphical modeling scheme using the sparse partially linear additive models for factor analysis of electricity demand and price. The scheme is applied to a real-world dataset and discussed from the viewpoint of interpretability.
KW - Graphical modeling
KW - hourly electric power demand
KW - machine learning
KW - partially linear additive model
KW - sparse modeling
KW - spot price
UR - http://www.scopus.com/inward/record.url?scp=85094843107&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85094843107&partnerID=8YFLogxK
U2 - 10.1109/EEM49802.2020.9221986
DO - 10.1109/EEM49802.2020.9221986
M3 - Conference contribution
AN - SCOPUS:85094843107
T3 - International Conference on the European Energy Market, EEM
BT - 2020 17th International Conference on the European Energy Market, EEM 2020
PB - IEEE Computer Society
T2 - 17th International Conference on the European Energy Market, EEM 2020
Y2 - 16 September 2020 through 18 September 2020
ER -
