TY - GEN
T1 - Joint optimal sizing and placement of renewable distributed generation and energy storage for energy loss minimization
AU - Kalkhambkar, Vaiju
AU - Kumar, Rajesh
AU - Bhakar, Rohit
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/22
Y1 - 2017/8/22
N2 - Large integration of renewable distributed generation (RDG) and energy storage (ES) in distribution networks provides an opportunity for energy loss minimization. This paper proposes a method for joint optimum allocation of RDG and distributed ES for energy loss minimization. The main contribution of the paper is formulation of probabilistic generation model and ES model to perform a combined optimization. Also, it presents integration of generation model, storage model, and load model into an optimal power flow to obtain loss minimization. A highly competitive algorithm called Grey Wolf Optimizer (GWO) is implemented to solve the nonlinear constrained optimization. The results are also compared with other heuristic algorithms, i.e., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Symbiotic Organisms Search Algorithm (SOS) and Firefly Algorithm (FFA). Two cases studies for joint optimal sizing and placement of RDG (i.e., solar RDG-ES and wind RDG-ES) are presented.
AB - Large integration of renewable distributed generation (RDG) and energy storage (ES) in distribution networks provides an opportunity for energy loss minimization. This paper proposes a method for joint optimum allocation of RDG and distributed ES for energy loss minimization. The main contribution of the paper is formulation of probabilistic generation model and ES model to perform a combined optimization. Also, it presents integration of generation model, storage model, and load model into an optimal power flow to obtain loss minimization. A highly competitive algorithm called Grey Wolf Optimizer (GWO) is implemented to solve the nonlinear constrained optimization. The results are also compared with other heuristic algorithms, i.e., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Symbiotic Organisms Search Algorithm (SOS) and Firefly Algorithm (FFA). Two cases studies for joint optimal sizing and placement of RDG (i.e., solar RDG-ES and wind RDG-ES) are presented.
KW - energy storage
KW - Grey Wolf Optimizer
KW - loss minimization
KW - optimum allocation
KW - probability density function
KW - Renewable distributed generation
UR - http://www.scopus.com/inward/record.url?scp=85030241343&partnerID=8YFLogxK
U2 - 10.1109/ICACCS.2017.8014596
DO - 10.1109/ICACCS.2017.8014596
M3 - Conference contribution
AN - SCOPUS:85030241343
T3 - 2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017
BT - 2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017
Y2 - 6 January 2017 through 7 January 2017
ER -