Optimal Active and Reactive Power Dispatch for Power System using AI
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In this book, an optimal active and reactive power dispatch problem is solved using swarm-intelligence based, bio-inspired algorithms. A new approach using cuckoo search (CS) algorithm is proposed for solving optimal power flow (OPF) problem by optimal setting of control variables. The standard objective functions pertaining to optimal active & reactive power flow, viz. Minimization of total cost of generation and active power loss. Cuckoo search is a bio-inspired algorithm, based on brooding behavior of cuckoo birds. This algorithm can search for a global solution using multiple paths. The si...
In this book, an optimal active and reactive power dispatch problem is solved using swarm-intelligence based, bio-inspired algorithms. A new approach using cuckoo search (CS) algorithm is proposed for solving optimal power flow (OPF) problem by optimal setting of control variables. The standard objective functions pertaining to optimal active & reactive power flow, viz. Minimization of total cost of generation and active power loss. Cuckoo search is a bio-inspired algorithm, based on brooding behavior of cuckoo birds. This algorithm can search for a global solution using multiple paths. The simulation results of the proposed approach are compared to other swarm intelligence technique i.e. Modified particle swarm optimization (MPSO). Problem is tested on standard IEEE 30-bus 6 generator system. The power flow equations and load balance equation are considered as equality constraints. The performance analysis of this OPF problem using the cuckoo search algorithm is carried out by checking various combinations of values of the associated parameters. Effectiveness of proposed approach is also tested for a multi-objective problem.
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