TY - JOUR
T1 - Distributionally Robust Economic Dispatch Using IDM for Integrated Electricity-heat-gas Microgrid Considering Wind Power
AU - Liu, Yang
AU - Chen, Xianbang
AU - Wu, Lei
AU - Ye, Yanli
N1 - Publisher Copyright:
© 2015 CSEE.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Multi-energy microgrids, such as integrated electricity-heat-gas microgrids (IEHS-MG), have been widely recognized as one of the most convenient ways to connect wind power (WP). However, the inherent intermittency and uncertainty of WP still render serious power curtailment in the operation. To this end, this paper presents an IEHS-MG model equipped with power-to-gas technology, thermal storage, electricity storage, and an electrical boiler for improving WP utilization efficiency. Moreover, a two-stage distributionally robust economic dispatch model is constructed for the IEHS-MG, with the objective of minimizing total operational costs. The first stage determines the day-ahead decisions including on/off state and set-point decisions. The second stage adjusts the day-ahead decision according to real-time WP realization. Furthermore, WP uncertainty is characterized through an Imprecise Dirichlet model (IDM) based ambiguity set. Finally, Column-and-Constraints Generation method is utilized to solve the model, which provides a day-ahead economic dispatch strategy that immunizes against the worst-case WP distributions. Case studies demonstrate the presented IEHS-MG model outperforms traditional IEHS-MG model in terms of WP utilization and dispatch economics, and that distributionally robust optimization can handle uncertainty effectively.
AB - Multi-energy microgrids, such as integrated electricity-heat-gas microgrids (IEHS-MG), have been widely recognized as one of the most convenient ways to connect wind power (WP). However, the inherent intermittency and uncertainty of WP still render serious power curtailment in the operation. To this end, this paper presents an IEHS-MG model equipped with power-to-gas technology, thermal storage, electricity storage, and an electrical boiler for improving WP utilization efficiency. Moreover, a two-stage distributionally robust economic dispatch model is constructed for the IEHS-MG, with the objective of minimizing total operational costs. The first stage determines the day-ahead decisions including on/off state and set-point decisions. The second stage adjusts the day-ahead decision according to real-time WP realization. Furthermore, WP uncertainty is characterized through an Imprecise Dirichlet model (IDM) based ambiguity set. Finally, Column-and-Constraints Generation method is utilized to solve the model, which provides a day-ahead economic dispatch strategy that immunizes against the worst-case WP distributions. Case studies demonstrate the presented IEHS-MG model outperforms traditional IEHS-MG model in terms of WP utilization and dispatch economics, and that distributionally robust optimization can handle uncertainty effectively.
KW - Data-driven
KW - day-ahead economic dispatch
KW - distributionally robust optimization
KW - imprecise dirichlet model
KW - integrated electricity-heat-gas microgrid
KW - wind power
UR - http://www.scopus.com/inward/record.url?scp=85147025568&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147025568&partnerID=8YFLogxK
U2 - 10.17775/CSEEJPES.2021.03940
DO - 10.17775/CSEEJPES.2021.03940
M3 - Article
AN - SCOPUS:85147025568
SN - 2096-0042
VL - 9
SP - 1182
EP - 1192
JO - CSEE Journal of Power and Energy Systems
JF - CSEE Journal of Power and Energy Systems
IS - 3
ER -