A new particle swarm optimization for non-convex economic dispatch

Abstract

SUMMARYThis paper proposes a novel heuristic optimization approach for a constrained economic dispatch (ED) problem using the new adaptive particle swarm optimization (NAPSO) algorithm. The proposed algorithm easily takes care of different constraints, such as transmission losses and prohibited operating zones, and also accounts for non-smooth/non-convex cost functions due to valve point loading effects. Particle swarm optimization (PSO) can be used to solve static ED problems. However, appropriate tuning of its parameters is cumbersome and usually converges to local solutions. To overcome the drawbacks of the original PSO algorithm, this paper presents the NAPSO algorithm. In the proposed algorithm, the inertia weight is tuned by using fuzzy IF/THEN rules and the cognitive and the social parameters are self-adaptively adjusted. In addition, to improve the global searching capability and prevent the convergence to local minima, a new mutation is proposed. To achieve the actual economic operation, the proposed algorithm is tested on a number of sample systems with units possessing prohibited zones and valve-point loading effects. The results reveal that the proposed approach is computationally efficient and would be a competent method for solving economic load dispatch problems.

Opposition-based krill herd algorithm applied to economic load dispatch problem

“…The optimal generation scheduling of all six generators obtained by the proposed OKHA approach along with those obtained by other optimization techniques such as IPSO-TVAC [12], BFO [19], MTS [49], NPSO-LRS [54], GA [54], PSO [54], IPSO [55], NAPSO [56], SOH-PSO [57] and HHS [58] is listed in Table 2. It is observed from the simulation results that all system constraints such as the ramp rate limits and prohibited operating zones limits are satisfied.…”

Fuzzy Adaptive Modified PSO-Algorithm Assisted to Design of Photonic Crystal Fiber Raman Amplifier

“…So, a proper selection provides a compromise between the local and the global searches. In many works, the selected w was big at first and after an initial search, this value would be lowered; a linearized model [17]. c 1 and c 2 are the best private and global positions, respectively.…”

“…The results show that these characteristics cannot obtain optimal results in some cases. So in this paper, these coefficients are computed as follows [17].…”

Solving the combined economic load and emission dispatch problems using new heuristic algorithm

“…in case of power plants [1]. Many methods such as analytical technique [2], intelligent techniques such as genetic algorithm (GA) [3][4][5][6], particle swarm optimization (PSO) [7][8][9][10][11][12][13][14], simulated annealing (SA) annealing [15], evolutionary programming (EP) [16,17] tabu search [18,19], harmony search [20,21], differential evolution [1,22], gravitational search [23] and other [24][25][26] have been applied to solving this problem. Some of mentioned methods are explained in following:…”