TY - JOUR
T1 - Day-ahead Risk-constrained Stochastic Scheduling of Multi-energy System
AU - Yin, Yue
AU - Liu, Tianqi
AU - Wu, Lei
AU - He, Chuan
AU - Liu, Yikui
N1 - Publisher Copyright:
© 2013 State Grid Electric Power Research Institute.
PY - 2021/7
Y1 - 2021/7
N2 - As an increasing penetration of renewable energy sources can potentially impact voltage profile and compromise system security, the security continues to be the most critical concern in power system operations. A risk-constrained stochastic scheduling model is proposed to leverage the latent scheduling capacity of a multi-energy system to seek an economic operation solution while maintaining system operation risk level against uncertain renewable generation. Overvoltage risk constraints, as compared to the straightforward voltage boundary limits, are incorporated into the stochastic scheduling model to guarantee the operation security and economics. Linearized AC power flow model is applied to enable overvoltage risk assessment within the coordinated scheduling model. The proposed stochastic scheduling model is tackled via the improved progressive hedging approach with an enhanced relax-round-polish process, which overcomes the convergence issues of the traditional progressive hedging in handling nonconvex stochastic scheduling model with binary variables on both stages. Numerical simulation results of IEEE 30-bus system and IEEE 118-bus system illustrate the efficacy of the proposed model in ensuring voltage security and improving economic operation of systems.
AB - As an increasing penetration of renewable energy sources can potentially impact voltage profile and compromise system security, the security continues to be the most critical concern in power system operations. A risk-constrained stochastic scheduling model is proposed to leverage the latent scheduling capacity of a multi-energy system to seek an economic operation solution while maintaining system operation risk level against uncertain renewable generation. Overvoltage risk constraints, as compared to the straightforward voltage boundary limits, are incorporated into the stochastic scheduling model to guarantee the operation security and economics. Linearized AC power flow model is applied to enable overvoltage risk assessment within the coordinated scheduling model. The proposed stochastic scheduling model is tackled via the improved progressive hedging approach with an enhanced relax-round-polish process, which overcomes the convergence issues of the traditional progressive hedging in handling nonconvex stochastic scheduling model with binary variables on both stages. Numerical simulation results of IEEE 30-bus system and IEEE 118-bus system illustrate the efficacy of the proposed model in ensuring voltage security and improving economic operation of systems.
KW - AC power flow
KW - multi-energy coordination
KW - overvoltage risk constraint
KW - renewable energy
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U2 - 10.35833/MPCE.2020.000375
DO - 10.35833/MPCE.2020.000375
M3 - Article
AN - SCOPUS:85111648103
SN - 2196-5625
VL - 9
SP - 720
EP - 733
JO - Journal of Modern Power Systems and Clean Energy
JF - Journal of Modern Power Systems and Clean Energy
IS - 4
M1 - 9433490
ER -