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Wind power is developing rapidly all around the world and at present total installed capacity is about 120,000 MW. Due to continuous improvements in turbine efficiency and increasing fuel prices, wind power is becoming economically competitive compared to conventional power generation. Combined economic/emission dispatch (CEED) involves the simultaneous optimization of two conflicting objectives namely...
This paper presents a fuzzy controlled parallel particle swarm optimization approach based decomposed network (FCP-PSO) to solving the large economic power dispatch with non-smooth cost fuel functions. The proposed approach combines practical experience extracted from global database formulated in fuzzy rules, the adaptive PSO executed in parallel based in decomposed network procedure as a local search...
Energy management of CHP-based microgrid is largely dependent on optimal deployment of distributed energy resources (DERs), where optimal bus-locations, capacity-sizes, and types are three major points to be considered in a microgrid planning. Investment and O&M cost, including fuel cost, are solely dependent on types of DERs. Present paper searches a way-out of how a electrical tracking demand...
This paper proposed multi-objective fuzzy particle swarm optimization (MOFPSO) for the Proton Exchange Membrane Fuel Cells (PEMFC) generation system. The PEM fuel cell generation system efficiency decreases as its output power increases. Thus, an optimum efficiency should exist and should result in a cost-effective PEM fuel cell generation system. In the optimization approach, the efficient and economic...
The dynamic economic dispatch (DED) is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. Social foraging behavior of Escherichia coli bacteria has been explored to develop a novel...
This paper describes secant method combined with particle swarm optimization for solving economic dispatch (ED) problem with prohibited operating zones. Two stages are involved in the proposed approach to solve the ED problem with prohibited operating zones. First, the range of output powers near to the global optimal solution is determined by secant method without considering prohibited zones and...
This paper presents particle swarm optimization (PSO) technique to solve economic dispatch of valve-point loaded generating units considering emission constraint. This problem has gained recent attention due to the deregulation of power industry and environmental regulations. Minimizing operating cost can no longer be the only criterion for dispatching electric power due to increasing concern over...
The paper presents an improved method for a 24-hour load forecasting in the power system by using self organizing map (SOM) of Kohonen neural network .In this paper two models are compared with each other. The main difference between these models is about determining the training patterns procedure. In the first basic model, the training of neural networks performs in similar patterns with the most...
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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