TY - JOUR
T1 - Optimal Allocation of ESSs for Mitigating Fluctuation in Active Distribution Network
AU - Wang, Shouxiang
AU - Wang, Kai
AU - Teng, Fei
AU - Strbac, Goran
AU - Wu, Lei
N1 - Publisher Copyright:
© 2017 The Authors. Published by Elsevier Ltd.
PY - 2017
Y1 - 2017
N2 - As distributed generations (DGs) are occupying an increasing proportion in active distribution network, the fluctuation of bus voltage becomes severe because of their intermittent and stochastic characteristics. Energy Storage System (ESS) can be adopted as an effective means to mitigate this fluctuation. This paper proposes a methodology for the optimal allocation of ESSs based on the novel optimal affine power flow (OAPF) approach. Affine models of wind turbine generation (WTG), photovoltaic (PV) system, and ESS are built while considering uncertainty characters of their power outputs. The objective function is set to minimize the capital investment of ESSs and the penalty costs of bus voltage fluctuations. The complex affine arithmetic based distribution power flow is used to ensure that constraints on power flow limits, voltage limits, and ESS operational limits are satisfied. The optimization problem is solved by an improved immune genetic algorithm (IIGA). The proposed approach is verified via a modified IEEE 33-bus system with a high penetration of DGs. Results show that the optimal allocation of ESSs can satisfy both the technical and economic requirements under such an uncertain environment.
AB - As distributed generations (DGs) are occupying an increasing proportion in active distribution network, the fluctuation of bus voltage becomes severe because of their intermittent and stochastic characteristics. Energy Storage System (ESS) can be adopted as an effective means to mitigate this fluctuation. This paper proposes a methodology for the optimal allocation of ESSs based on the novel optimal affine power flow (OAPF) approach. Affine models of wind turbine generation (WTG), photovoltaic (PV) system, and ESS are built while considering uncertainty characters of their power outputs. The objective function is set to minimize the capital investment of ESSs and the penalty costs of bus voltage fluctuations. The complex affine arithmetic based distribution power flow is used to ensure that constraints on power flow limits, voltage limits, and ESS operational limits are satisfied. The optimization problem is solved by an improved immune genetic algorithm (IIGA). The proposed approach is verified via a modified IEEE 33-bus system with a high penetration of DGs. Results show that the optimal allocation of ESSs can satisfy both the technical and economic requirements under such an uncertain environment.
KW - Active distribution network
KW - distributed generation
KW - energy storage system
KW - fluctuation mitigation
KW - optimal affine power flow
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U2 - 10.1016/j.egypro.2017.12.247
DO - 10.1016/j.egypro.2017.12.247
M3 - Conference article
AN - SCOPUS:85041512348
SN - 1876-6102
VL - 142
SP - 3572
EP - 3577
JO - Energy Procedia
JF - Energy Procedia
T2 - 9th International Conference on Applied Energy, ICAE 2017
Y2 - 21 August 2017 through 24 August 2017
ER -