TY - JOUR
T1 - Water-Energy Nexus Management for Power Systems
AU - Zhao, Pengfei
AU - Gu, Chenghong
AU - Cao, Zhidong
AU - Ai, Qian
AU - Xiang, Yue
AU - Ding, Tao
AU - Lu, Xi
AU - Chen, Xinlei
AU - Li, Shuangqi
N1 - Publisher Copyright:
© 1969-2012 IEEE.
PY - 2021/5
Y1 - 2021/5
N2 - The water system management problem has been widely investigated. However, the interdependencies between water and energy systems are significant and the effective co-optimization is required considering strong interconnections. This paper proposes a two-stage distributionally robust operation model for integrated water-energy nexus systems including power, gas and water systems networked with energy hub systems at a distribution level considering wind uncertainty. The presence of wind power uncertainty inevitably leads to risks in the optimization model. Accordingly, a coherent risk measure, i.e., conditional value-at-risk, is combined with the optimization objective to determine risk-averse operation schemes. This two-stage mean-risk distributionally robust optimization is solved by Bender's decomposition method. Both the day-ahead and real-time operation cost are minimized with an optimal set of scheduling the multi-energy infrastructures. Case studies focus on investigating the strong interdependencies among the four interconnected energy systems. Numerical results validate the economic effectiveness of IES through optimally coordinating the multi-energy infrastructures. The proposed model can provide system operators a powerful two-stage operation scheme to minimise operation cost under water-energy nexus considering risk caused by renewable uncertainties, thus benefiting customers with lower utility bills.
AB - The water system management problem has been widely investigated. However, the interdependencies between water and energy systems are significant and the effective co-optimization is required considering strong interconnections. This paper proposes a two-stage distributionally robust operation model for integrated water-energy nexus systems including power, gas and water systems networked with energy hub systems at a distribution level considering wind uncertainty. The presence of wind power uncertainty inevitably leads to risks in the optimization model. Accordingly, a coherent risk measure, i.e., conditional value-at-risk, is combined with the optimization objective to determine risk-averse operation schemes. This two-stage mean-risk distributionally robust optimization is solved by Bender's decomposition method. Both the day-ahead and real-time operation cost are minimized with an optimal set of scheduling the multi-energy infrastructures. Case studies focus on investigating the strong interdependencies among the four interconnected energy systems. Numerical results validate the economic effectiveness of IES through optimally coordinating the multi-energy infrastructures. The proposed model can provide system operators a powerful two-stage operation scheme to minimise operation cost under water-energy nexus considering risk caused by renewable uncertainties, thus benefiting customers with lower utility bills.
KW - Integrated energy system
KW - mean-risk optimization
KW - power-to-gas
KW - renewable uncertainty
KW - water-energy nexus
UR - https://www.scopus.com/pages/publications/85098777330
U2 - 10.1109/TPWRS.2020.3038076
DO - 10.1109/TPWRS.2020.3038076
M3 - 文章
AN - SCOPUS:85098777330
SN - 0885-8950
VL - 36
SP - 2542
EP - 2554
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 3
M1 - 9259109
ER -