TY - GEN
T1 - Two-Stage Distributed Energy Resources Scheduling via Chance-Constrained AC Optimal Power Flow
T2 - 2020 IEEE Power and Energy Society General Meeting, PESGM 2020
AU - He, Mingyue
AU - Soltani, Zahra
AU - Khorsand, Mojdeh
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/8/2
Y1 - 2020/8/2
N2 - The penetration of distributed energy resources (DERs) is increasing dramatically. Due to the uncertainty of DERs, the operation of the distribution system is facing higher risks and challenges. To overcome such challenges, a two-stage chance-constrained convex AC optimal power flow (ACOPF) model is proposed in this paper, which can increase the economic efficiency of distribution system operation and manage the intermittency of DERs. In the first stage, a convex second-order cone programming (SOCP)-based ACOPF model is proposed in which the detailed models and limitations of DER, namely, demand response (DR), energy storage units, and rooftop PV systems are modeled to obtain participation ratio of DERs. In the second stage, Monte Carlo simulation is utilized to model the uncertainties of DERs. A probability violation index is introduced to make a trade-off between scheduling more DERs and imposing a higher risk to the distribution system. In this stage, power flow analysis is conducted for each scenario to determine the probability violation index of system. Then, a modified SOCP-based ACOPF is proposed to satisfy the system probability violation criterion. Simulation results illustrate that the proposed two-stage chance-constrained model improves economic efficiency and reliability of real-time operation of the distribution system.
AB - The penetration of distributed energy resources (DERs) is increasing dramatically. Due to the uncertainty of DERs, the operation of the distribution system is facing higher risks and challenges. To overcome such challenges, a two-stage chance-constrained convex AC optimal power flow (ACOPF) model is proposed in this paper, which can increase the economic efficiency of distribution system operation and manage the intermittency of DERs. In the first stage, a convex second-order cone programming (SOCP)-based ACOPF model is proposed in which the detailed models and limitations of DER, namely, demand response (DR), energy storage units, and rooftop PV systems are modeled to obtain participation ratio of DERs. In the second stage, Monte Carlo simulation is utilized to model the uncertainties of DERs. A probability violation index is introduced to make a trade-off between scheduling more DERs and imposing a higher risk to the distribution system. In this stage, power flow analysis is conducted for each scenario to determine the probability violation index of system. Then, a modified SOCP-based ACOPF is proposed to satisfy the system probability violation criterion. Simulation results illustrate that the proposed two-stage chance-constrained model improves economic efficiency and reliability of real-time operation of the distribution system.
KW - AC optimal power flow (ACOPF)
KW - Chance-constraint
KW - Convex relaxation
KW - Distributed energy resources
KW - Stochastic optimization
UR - http://www.scopus.com/inward/record.url?scp=85099161252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099161252&partnerID=8YFLogxK
U2 - 10.1109/PESGM41954.2020.9281795
DO - 10.1109/PESGM41954.2020.9281795
M3 - Conference contribution
AN - SCOPUS:85099161252
T3 - IEEE Power and Energy Society General Meeting
BT - 2020 IEEE Power and Energy Society General Meeting, PESGM 2020
PB - IEEE Computer Society
Y2 - 2 August 2020 through 6 August 2020
ER -