TY - JOUR
T1 - Evaluation for Maximum Hosting Capacity of Distributed Generation considering Active Network Management
AU - Ikeda, Shunnosuke
AU - Ohmori, Hiromitsu
N1 - Publisher Copyright:
© 2018 Int. J. Elec. & Elecn. Eng. & Telcomm.
PY - 2018/7/1
Y1 - 2018/7/1
N2 - With the increasing penetration of renewable Distributed Generation (DG), it is important to assess the Maximum Hosting Capacity (MHC) in active distribution networks. Active Network Management (ANM) such as coordinated voltage control, reactive power compensation, DG curtailment, DG power factor control, network reconfiguration and demand response can play an important role in increasing the MHC. The MHC evaluation problem considering all the above elements of ANM can be formulated as a mixed integer nonlinear programming model. However, this original nonconvex model cannot guarantee convergence to optimality. This paper proposes the mixed integer second-order cone programming model for evaluating the MHC, by using exact linearization and second-order cone relaxation. The modified IEEE 33-bus test system is used to demonstrate the effectiveness of the proposed model and analyze the effect of each ANM element on the MHC increase. The results show that when considering all the above elements of ANM, the gain of the MHC is greater than 62%.
AB - With the increasing penetration of renewable Distributed Generation (DG), it is important to assess the Maximum Hosting Capacity (MHC) in active distribution networks. Active Network Management (ANM) such as coordinated voltage control, reactive power compensation, DG curtailment, DG power factor control, network reconfiguration and demand response can play an important role in increasing the MHC. The MHC evaluation problem considering all the above elements of ANM can be formulated as a mixed integer nonlinear programming model. However, this original nonconvex model cannot guarantee convergence to optimality. This paper proposes the mixed integer second-order cone programming model for evaluating the MHC, by using exact linearization and second-order cone relaxation. The modified IEEE 33-bus test system is used to demonstrate the effectiveness of the proposed model and analyze the effect of each ANM element on the MHC increase. The results show that when considering all the above elements of ANM, the gain of the MHC is greater than 62%.
KW - Active network management
KW - Distributed generation
KW - Maximum hosting capacity
KW - Mixed integer second-order cone programming
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U2 - 10.18178/ijeetc.7.3.96-102
DO - 10.18178/ijeetc.7.3.96-102
M3 - Article
AN - SCOPUS:85049188937
SN - 2319-2518
VL - 7
SP - 96
EP - 102
JO - International Journal of Electrical and Electronic Engineering and Telecommunications
JF - International Journal of Electrical and Electronic Engineering and Telecommunications
IS - 3
ER -