TY - GEN
T1 - Hybrid energy storage and generation planning with large renewable penetration
AU - Yang, Peng
AU - Nehorai, Arye
PY - 2013
Y1 - 2013
N2 - Energy storage is important in a power grid with high penetration of renewable energy, especially for isolated grids or micro-grids. Considering the different characteristics of energy storage devices and the different availability of renewable energy sources, planning a good portfolio of them is important for efficient system operation and investment cost minimization. In this paper we consider the planning problem as a chance-constrained optimization problem and solve the problem using scenario approximation. To reduce the computational time, we formulate the original problem as a consensus problem, and employ the alternating directional method of multipliers to solve the optimization problem in a distributed manner. The results potentially help make decisions on energy storage and renewable generation planning, and guide policy making related to renewable energy sources.
AB - Energy storage is important in a power grid with high penetration of renewable energy, especially for isolated grids or micro-grids. Considering the different characteristics of energy storage devices and the different availability of renewable energy sources, planning a good portfolio of them is important for efficient system operation and investment cost minimization. In this paper we consider the planning problem as a chance-constrained optimization problem and solve the problem using scenario approximation. To reduce the computational time, we formulate the original problem as a consensus problem, and employ the alternating directional method of multipliers to solve the optimization problem in a distributed manner. The results potentially help make decisions on energy storage and renewable generation planning, and guide policy making related to renewable energy sources.
UR - https://www.scopus.com/pages/publications/84894192514
U2 - 10.1109/CAMSAP.2013.6714107
DO - 10.1109/CAMSAP.2013.6714107
M3 - Conference contribution
AN - SCOPUS:84894192514
SN - 9781467331463
T3 - 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
SP - 460
EP - 463
BT - 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
T2 - 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
Y2 - 15 December 2013 through 18 December 2013
ER -