Abstract
This paper proposes a self-organizing hierarchical particle swarm optimization (SOHPSO) with time-varying acceleration coefficients (TVAC) for solving security constrained optimal power flow (SCOPF) problem. The SCOPF is to minimize a total generation cost while satisfying generator operational constraints and network security constraints in which the minimum severity index is used to alleviate line loading. The proposed SOHPSO-TVAC re-initializes particle velocities whenever the population stagnates at local optima during the search and TVAC is used to enhance convergence to the global optimum solution. Test results on the IEEE 30 and 118 bus systems indicate that the proposed SCOPF renders a lower total generation cost in a faster convergence rate than the other heuristic methods, which is favorable for online implementation.
Highlights
Optimal power flow (OPF) has been widely used for economic and secure power system operation
The improved Particle swarm optimization (PSO)-based contingency constrained economic load dispatch (ELD) (CCELD) solution gives the optimal setting of all controllable variables for a static power setting loading condition [3]
The proposed self-organizing hierarchical particle swarm optimization (SOHPSO)-Time-Varying Acceleration Coefficients (TVAC) for security-constrained optimal power flow (SCOPF) problem is tested on the IEEE 30-bus system [7] and IEEE 118-bus system [8]
Summary
Optimal power flow (OPF) has been widely used for economic and secure power system operation. Several techniques have been proposed to solve the OPF problem including Newton-based techniques, nonlinear programming, quadratic programming, linear programming and interior point methods [1]. These methods rely on convex and continuous fuel-cost function to obtain the optimum solution. They may face some difficulty when non-convex characteristics of generator fuel-cost function are considered [2] To overcome these barriers, many heuristic algorithms such as genetic algorithm (GA), tabu search (TS), hybrid tabu search and simulated annealing (TS/SA) and evolutionary programming (EP), which are used to solve security-constrained optimal power flow (SCOPF) problems, have been proposed to solve the OPF problem. For EP-based security constrained economic load dispatch (ELD), the contingency constraints are not taken into account [5]
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