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Economic power dispatch problem plays an important role in the operation of the power systems. The objective of economic dispatch problem is to schedule output of the committed units such that the total fuel cost is minimized while meeting a set of operating constraints. In this paper, two modified particle swarm optimization algorithms with one of the accelerating coefficients being constant are...
An automatic Vehicle-to-Grid (V2G) technology can contribute to the utility grid. V2G technology has drawn great interest in the recent years. Success of the sophisticated automatic V2G research depends on efficient scheduling of gridable vehicles in constrained parking lots. Parking lots have constraints of space and current limits for V2G. However, V2G can reduce dependencies on small expensive...
Vehicle-to-Grid (V2G) technology has drawn great interest in the recent years. Success of the V2G research depends on efficient scheduling of gridable vehicles in limited parking lots. V2G can reduce dependencies on small expensive units in the existing power systems as energy storage that can decrease running costs. It can efficiently manage load fluctuation, peak load; however, it increases spinning...
This paper proposes a new hybrid meta-heuristic method for profit-based unit commitment (PBUC) that considers units with nonlinear cost function. The proposed method aims at global optimization to carry out profit maximization under competitive environment. The objective of the traditional UC is to minimize operation-cost while satisfying the constraints. However, power system operation needs reformulate...
Landing on distant planets is always a challenging task due to the distance and hostile environments found. In the design of autonomous hazard avoidance systems we find the particularly relevant task of landing site selection, that has to operate in real-time as the lander approaches the planet's surface. Seeking to improve the computational complexity of previous approaches to this problem, we propose...
This paper presents a multi-population binary clustered particle swarm optimization (BCPSO) algorithm to solve short term thermal generation scheduling problem. The potential solution schedules are distributed among several clusters based on their corresponding fitness values. Each cluster contains a cluster best schedule. Each solution of a particular population then flies through to its cluster...
This paper proposes a particle swarm optimization (PSO) method for solving the economic dispatch (ED) problem in power systems. Many nonlinear characteristics of the generator are considered for practical generator operation, such as ramp rates, prohibited operating zones, and non-smooth cost functions. The feasibility of the proposed method is demonstrated for two different systems, and is Compared...
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